Lambda vs Vast.ai

Ide

1. developerOpen Jupyter or connect my IDE (VS Code/Cursor) to the instance in one step

   weight 1 · round to Lambda
   Lambda~partialclaimed6/10

   Lambda instances ship with a preinstalled JupyterLab server and SSH access out of the box, letting a developer open Jupyter or SSH in with no extra setup (docs-3, docs-7). However, there's no explicit documentation of a one-step VS Code/Cursor Remote-SSH or dev-container integration — only generic SSH connectivity is mentioned, requiring the developer to manually configure their IDE's remote connection. Missing for 10: explicit VS Code/Cursor connection docs or one-click IDE integration, independent confirmation that IDE remote-attach works smoothly.

   • [claimed-docs] “each ODC instance provides a JupyterLab installation for creating and managing Jupyter notebooks”
   • [claimed-docs] “You can connect to your On-Demand Cloud (ODC) instances directly through SSH or by using the preinstalled JupyterLab server.”
   • [claimed-docs] “On-Demand Cloud (ODC) provides on-demand access to Linux-based, GPU-backed virtual machine instances.”

   proof ↗⚑ flag

   Vast.ai~partialclaimed5/10

   Vast.ai documents secure SSH access to instances (key-based auth, run commands, transfer files) and one-click template launches that could include Jupyter environments, which together enable IDE remote-connection workflows (e.g., VS Code Remote-SSH). However, the evidence never explicitly names Jupyter notebook access or a documented one-step VS Code/Cursor connection flow. Missing for 10: explicit Jupyter launch/access docs, explicit VS Code/Cursor remote-connect guide or extension support, and any hands-on confirmation of a true 'one step' connect experience.

   • [claimed-docs] “Vast.ai instances are configured to accept keys only - Password authentication is disabled for improved security.”
   • [claimed-docs] “Log in securely, Run commands remotely, Transfer files without exposing your data”
   • [claimed-docs] “SSH (Secure Shell) is a protocol for safely connecting to remote servers. It encrypts your connection so you can: Log in securely, Run comma…”
   • [claimed-docs] “Launch prebuilt or custom templates with one click.”
   • [claimed-docs] “A template is how Vast helps you launch an instance, setting up your rented machine with whatever software and formatting you need.”
   • [claimed-docs] “Build a template - Package your environment so any GPU can run it with one click.”

   proof ↗⚑ flag

Networking

1. developerExpose ports to serve applications from my instance and connect instances over private networking

   weight 1 · round to Vast.ai
   Lambda~partialclaimed5/10

   Lambda's docs show port-level control via Firewall rules restricting incoming traffic (docs-11/18) and SSH/JupyterLab access (docs-7), and high-performance private networking (GPUDirect RDMA) exists within 1-Click Clusters and Managed Kubernetes for GPU node interconnect (docs-36, docs-12/33). However, there's no explicit documentation of a general-purpose private networking/VPC feature connecting arbitrary On-Demand instances, nor clear guidance on opening/exposing custom application ports beyond firewall restriction rules. Missing for 10: explicit port-exposure/ingress configuration for serving apps, dedicated private networking (VPC/VLAN) between standard instances outside of 1CC/K8s clusters, and independent confirmation of these networking features working in practice.

   • [claimed-docs] “You can restrict incoming traffic to the instances in a workspace... by creating firewall rules on the Firewall page”
   • [claimed-docs] “You can restrict incoming traffic to the instances in a workspace...by creating firewall rules on the [Firewall page]”
   • [claimed-docs] “You can connect to your On-Demand Cloud (ODC) instances directly through SSH or by using the preinstalled JupyterLab server.”
   • [claimed-docs] “1-Click Clusters (1CC) are high-performance clusters composed of both GPU and CPU nodes, featuring 16 to 512 NVIDIA H100 or B200 SXM Tensor …”
   • [claimed-docs] “MK8s provides a Kubernetes environment with GPU and InfiniBand (RDMA) support, and shared persistent storage across all nodes in a 1CC.”
   • [claimed-docs] “MK8s provides a Kubernetes environment with GPU and InfiniBand (RDMA) support, and shared persistent storage across all nodes in a 1CC. Clus…”

   proof ↗⚑ flag

   Vast.ai✓fullclaimed7/10

   Docs explicitly describe exposing ports (search filter `direct_port_count>=1`, SSH access) and creating private overlay networks so instances on different machines can share a virtual LAN for multi-node workloads, directly matching both halves of the story. Missing for 10: independent/hands-on confirmation of port-forwarding for arbitrary web apps beyond SSH, and more detail on overlay network setup/limitations.

   • [claimed-docs] “Vast now supports creating *overlay* networks for instances, allowing client instances on different machines on the same physical LAN to sha…”
   • [claimed-docs] “Vast now supports creating overlay networks for instances, allowing client instances on different machines on the same physical LAN to share…”
   • [claimed-docs] “vastai search offers 'gpu_name=RTX_4090 num_gpus=1 verified=true direct_port_count>=1 rentable=true' -o 'dlperf_usd-'”
   • [claimed-docs] “Vast.ai instances are configured to accept keys only - Password authentication is disabled for improved security.”
   • [claimed-docs] “SSH (Secure Shell) is a protocol for safely connecting to remote servers. It encrypts your connection so you can: Log in securely, Run comma…”

   proof ↗⚑ flag

Ssh

1. developerSSH into my GPU instance with my own keys and get root-level control of the environment

   weight 3 · round to Lambda
   Lambda✓fullcommunity8/10

   Docs confirm direct SSH access to GPU instances with user-controlled base images (GPU Base minimal Ubuntu image for high control), cloud-init customization, and API/CLI provisioning, implying standard root SSH access typical of cloud VM instances. Community evidence (unofficial CLI/MCP tool) corroborates real-world SSH-based workflows for launching and connecting to instances. Missing for 10: explicit first-party documentation confirming root/sudo privileges once SSH'd in, and independent hands-on confirmation of key management specifics.

   • [claimed-docs] “You can connect to your On-Demand Cloud (ODC) instances directly through SSH or by using the preinstalled JupyterLab server.”
   • [claimed-docs] “GPU Base: An image based on Ubuntu Server that includes a minimal set of key AI/ML tools and drivers... Use if: You want a minimal working s…”
   • [claimed-docs] “you can add launch-time configuration instructions using [cloud-init]”
   • [claimed-docs] “the API allows you to use a different base image for your instance”
   • [community] “A developer built an unofficial CLI and MCP server for Lambda cloud GPU instances, enabling AI agents to find, launch, and terminate Lambda …”

   proof ↗⚑ flag

   Vast.ai~partialclaimed6/10

   Docs confirm SSH access is key-based only (password auth disabled) and lets you log in securely, run commands remotely, and transfer files, which implies developer control of the instance. However, the evidence pack never explicitly confirms root-level privileges or documents the workflow for adding a user's own SSH key. Missing for 10: explicit documentation of root/sudo access inside instances, and details on uploading/managing your own SSH keys.

   • [claimed-docs] “Vast.ai instances are configured to accept keys only - Password authentication is disabled for improved security.”
   • [claimed-docs] “Log in securely, Run commands remotely, Transfer files without exposing your data”
   • [claimed-docs] “SSH (Secure Shell) is a protocol for safely connecting to remote servers. It encrypts your connection so you can: Log in securely, Run comma…”

   proof ↗⚑ flag

Agent access

1. ai-native userPoint an agent at llms.txt or agent-oriented docs

   weight 2 · round to Vast.ai
   Lambda—none0/10

   A direct probe of https://docs.lambda.ai/llms.txt returned HTTP 404, and there is no other evidence of an llms.txt file or agent-oriented documentation format anywhere in the pack; the OpenAPI spec is a REST API description, not agent-native docs guidance.

   • [probe] “PROBE llms.txt: HTTP 404 at https://docs.lambda.ai/llms.txt”

   proof ↗⚑ flag

   Vast.ai✓fullprobed9/10

   Vast.ai publishes a live llms.txt at docs.vast.ai/llms.txt (confirmed via probe returning HTTP 200 with structured doc links) and additionally ships an explicit agent-oriented guide/skill ('vastai agent skill') documenting how AI coding assistants can drive the platform directly. This directly satisfies pointing an agent at llms.txt or agent-oriented docs. Missing for 10: no independent/community corroboration of agents actually consuming llms.txt in practice.

   • [probe] “PROBE llms.txt: HTTP 200 at https://docs.vast.ai/llms.txt # Vast.ai Documentation: Affordable GPU Cloud Marketplace - [Welcome](https://doc…”
   • [claimed-docs] “The `vastai` agent skill lets AI coding assistants drive Vast.ai on your behalf — create instances, deploy endpoints, manage SSH keys, check…”
   • [claimed-docs] “The vastai agent skill lets AI coding assistants drive Vast.ai on your behalf — create instances, deploy endpoints, manage SSH keys, check b…”
   • [claimed-docs] “The vastai agent skill lets AI coding assistants drive Vast.ai on your behalf — create instances, deploy endpoints, manage SSH keys, check b…”

   proof ↗⚑ flag

2. ai-native userRun the product headlessly / in CI for automation

   weight 2 · round to Vast.ai
   Lambda✓fullprobed7/10

   Lambda's On-Demand Cloud exposes a full REST API for programmatically launching/terminating GPU instances, with cloud-init for launch-time automation, confirmed live and key-gated by a runtime probe — enabling headless/CI-driven provisioning of GPU workloads without any UI interaction. Missing for 10: an official first-party CLI/SDK or CI/CD templates (only an unofficial community-built CLI/MCP server exists) and documented CI examples (e.g., GitHub Actions) from Lambda itself.

   • [claimed-docs] “You can also launch instances programmatically by using the Lambda Cloud API.”
   • [claimed-docs] “You can also launch instances programmatically by using the Lambda Cloud API. For details, see Launch instances”
   • [claimed-docs] “If you're launching your instance with the Lambda Cloud API, you can add launch-time configuration instructions using cloud-init”
   • [claimed-docs] “The Lambda Cloud API provides a set of REST API endpoints you can use to create and manage your Lambda Cloud resources.”
   • [probe] “PROBE runtime (recorded 2026-09-05): https://cloud.lambda.ai/api/v1/openapi.json serves the full Lambda Cloud API OpenAPI 3.1 spec (title 'L…”
   • [community] “A developer built an unofficial CLI and MCP server for Lambda cloud GPU instances, enabling AI agents to find, launch, and terminate Lambda …”

   proof ↗⚑ flag

   Vast.ai✓fullprobed8/10

   Vast.ai offers a full CLI and REST API for scriptable, non-interactive control of the entire instance lifecycle (search, create, destroy), confirmed by both docs and hands-on runtime probes running keylessly. Scoped API keys are explicitly recommended for CI/CD and shared tooling, and the CLI was verified to run headlessly via uvx with no login. Missing for 10: no explicit CI pipeline example (e.g., GitHub Actions workflow) or third-party case study of running it in an automated CI pipeline.

   • [claimed-docs] “The Vast.ai CLI gives you command-line access to the entire platform, authentication, GPU search, instance lifecycle, templates, volumes, se…”
   • [claimed-docs] “You can also create scoped keys with limited permissions using `vastai create api-key`, useful for CI/CD or shared tooling.”
   • [claimed-docs] “For shared tooling, CI/CD, or automation, create a scoped key with only the permissions that workload needs.”
   • [claimed-docs] “Automate with the CLI or SDK ... `vastai` from the shell or Python. Same operations, different syntax.”
   • [probe] “PROBE runtime (recorded 2026-09-05): the official Vast.ai CLI (pypi `vastai`) installed via uvx and ran keylessly — `vastai --help` prints t…”
   • [probe] “PROBE runtime (recorded 2026-09-05): `vastai search offers 'gpu_name=RTX_4090 num_gpus=1' -o dph` searched the LIVE GPU marketplace with NO …”
   • [probe] “PROBE runtime (recorded 2026-09-05): a bare keyless GET to https://console.vast.ai/api/v0/bundles/ returned live marketplace offers as JSON …”

   proof ↗⚑ flag

3. ai-native userConnect an agent via an official MCP server

   weight 3 · round drawn
   Lambda—none0/10

   Only an unofficial, community-built CLI/MCP server for Lambda GPU instances is documented; there is no evidence of an official first-party MCP server from Lambda itself.

   • [community] “A developer built an unofficial CLI and MCP server for Lambda cloud GPU instances, enabling AI agents to find, launch, and terminate Lambda …”

   proof ↗⚑ flag

   Vast.ai—none0/10

   Vast.ai documents a CLI, REST API, Python SDK, and an 'agent skill' file for coding assistants, but no evidence anywhere describes an official MCP server or MCP integration. Since Vast.ai is a platform/service (not itself an agent), the MCP-server axis applies, and its absence from the evidence pack means the story is unmet.

   • [claimed-docs] “The `vastai` agent skill lets AI coding assistants drive Vast.ai on your behalf — create instances, deploy endpoints, manage SSH keys, check…”
   • [claimed-docs] “The vastai agent skill lets AI coding assistants drive Vast.ai on your behalf — create instances, deploy endpoints, manage SSH keys, check b…”
   • [claimed-docs] “The vastai agent skill lets AI coding assistants drive Vast.ai on your behalf — create instances, deploy endpoints, manage SSH keys, check b…”
   • [claimed-docs] “The Vast.ai CLI gives you command-line access to the entire platform, authentication, GPU search, instance lifecycle, templates, volumes, se…”
   • [claimed-docs] “The Vast.ai REST API gives you programmatic control over the entire platform. It's the foundation that the CLI and SDK are built on.”

   proof ↗⚑ flag

4. ai-native userUse an official CLI

   weight 2 · round to Vast.ai
   Lambda—none0/10

   Evidence shows only a REST API (openapi.json) and cloud-init/SSH access, with no first-party CLI tool documented; the only CLI mentioned is an unofficial third-party CLI/MCP server built by a community developer for AI agents, not an official Lambda offering.

   • [claimed-docs] “The Lambda Cloud API provides a set of REST API endpoints you can use to create and manage your Lambda Cloud resources.”
   • [claimed-docs] “The Lambda Cloud API provides a set of REST API endpoints you can use to create\nand manage your Lambda Cloud resources.”
   • [community] “A developer built an unofficial CLI and MCP server for Lambda cloud GPU instances, enabling AI agents to find, launch, and terminate Lambda …”
   • [probe] “PROBE runtime (recorded 2026-09-05): https://cloud.lambda.ai/api/v1/openapi.json serves the full Lambda Cloud API OpenAPI 3.1 spec (title 'L…”

   proof ↗⚑ flag

   Vast.ai✓fullprobed9/10

   Vast.ai ships an official CLI (pypi `vastai`) with full documentation of the entire platform surface (search, instances, templates, volumes, serverless), and runtime probes confirm it installs and works keylessly for real marketplace queries. Missing for 10: independent third-party reviews specifically praising/critiquing the CLI's UX beyond vendor docs and probes.

   • [claimed-docs] “The Vast.ai CLI gives you command-line access to the entire platform, authentication, GPU search, instance lifecycle, templates, volumes, se…”
   • [claimed-docs] “vastai search offers 'gpu_name=RTX_4090 num_gpus=1 verified=true direct_port_count>=1 rentable=true' -o 'dlperf_usd-'”
   • [claimed-docs] “Automate with the CLI or SDK ... `vastai` from the shell or Python. Same operations, different syntax.”
   • [probe] “official CLI documented at https://docs.vast.ai/cli/hello-world”
   • [probe] “PROBE runtime (recorded 2026-09-05): the official Vast.ai CLI (pypi `vastai`) installed via uvx and ran keylessly — `vastai --help` prints t…”
   • [probe] “PROBE runtime (recorded 2026-09-05): `vastai search offers 'gpu_name=RTX_4090 num_gpus=1' -o dph` searched the LIVE GPU marketplace with NO …”

   proof ↗⚑ flag

5. ai-native userDrive the product through a documented public API

   weight 3 · round drawn
   Lambda✓fullprobed9/10

   Lambda publishes a documented public REST API (Lambda Cloud API) with a live OpenAPI 3.1 spec covering instance provisioning, cluster launch, filesystems, and firewall management, confirmed both in docs and via runtime probe returning the full spec and a key-gated endpoint. Community evidence further shows a third-party built a CLI/MCP server on top of this API enabling AI agents to launch/terminate GPU instances programmatically, corroborating real-world agentic usability. Missing for 10: an official first-party SDK/MCP server and an llms.txt (probe found 404), so slight extra integration work is needed.

   • [claimed-docs] “You can also launch instances programmatically by using the Lambda Cloud API.”
   • [claimed-docs] “You can also launch instances programmatically by using the Lambda Cloud API. For details, see Launch instances”
   • [claimed-docs] “The Lambda Cloud API provides a set of REST API endpoints you can use to create and manage your Lambda Cloud resources.”
   • [claimed-docs] “The Lambda Cloud API provides a set of REST API endpoints you can use to create\nand manage your Lambda Cloud resources.”
   • [probe] “PROBE runtime (recorded 2026-09-05): https://cloud.lambda.ai/api/v1/openapi.json serves the full Lambda Cloud API OpenAPI 3.1 spec (title 'L…”
   • [community] “A developer built an unofficial CLI and MCP server for Lambda cloud GPU instances, enabling AI agents to find, launch, and terminate Lambda …”

   proof ↗⚑ flag

   Vast.ai✓fullprobed9/10

   Vast.ai publishes a documented REST API (with live OpenAPI spec) and CLI/SDK built on top of it, explicitly positioned for programmatic/agentic use, including scoped API keys for automation and a dedicated 'agent skill' for AI coding assistants. Runtime probes confirm the CLI and REST endpoints work keylessly for core operations like search/create/destroy instances, corroborating the documentation with hands-on evidence. Missing for 10: independent third-party developer reports specifically about API robustness/rate limits beyond docs and probes.

   • [claimed-docs] “The Vast.ai REST API gives you programmatic control over the entire platform. It's the foundation that the CLI and SDK are built on.”
   • [claimed-docs] “The Vast.ai REST API gives you programmatic control over the entire platform.”
   • [claimed-docs] “The Vast.ai CLI gives you command-line access to the entire platform, authentication, GPU search, instance lifecycle, templates, volumes, se…”
   • [claimed-docs] “The `vastai` agent skill lets AI coding assistants drive Vast.ai on your behalf — create instances, deploy endpoints, manage SSH keys, check…”
   • [claimed-docs] “The vastai agent skill lets AI coding assistants drive Vast.ai on your behalf — create instances, deploy endpoints, manage SSH keys, check b…”
   • [claimed-docs] “create a scoped key with only the permissions that workload needs”
   • [claimed-docs] “For shared tooling, CI/CD, or automation, create a scoped key with only the permissions that workload needs.”
   • [probe] “PROBE openapi: HTTP 200 at https://docs.vast.ai/api/openapi.json — contains "openapi" key”
   • [probe] “PROBE runtime (recorded 2026-09-05): the official Vast.ai CLI (pypi `vastai`) installed via uvx and ran keylessly — `vastai --help` prints t…”
   • [probe] “PROBE runtime (recorded 2026-09-05): `vastai search offers 'gpu_name=RTX_4090 num_gpus=1' -o dph` searched the LIVE GPU marketplace with NO …”
   • [probe] “PROBE runtime (recorded 2026-09-05): a bare keyless GET to https://console.vast.ai/api/v0/bundles/ returned live marketplace offers as JSON …”

   proof ↗⚑ flag

6. ai-native userIssue scoped/least-privilege API credentials for an agent

   weight 2 · round to Vast.ai
   Lambda—none0/10

   Lambda's Cloud API is key-gated (docs-31/39, probe-rt-1 confirms 401 without a key), but there is no evidence of scoped/least-privilege credential issuance (e.g., role-based permissions, read-only vs. write scopes, or per-agent restricted keys) — only that a single API key exists to access all account resources.

   • [claimed-docs] “The Lambda Cloud API provides a set of REST API endpoints you can use to create and manage your Lambda Cloud resources.”
   • [claimed-docs] “The Lambda Cloud API provides a set of REST API endpoints you can use to create\nand manage your Lambda Cloud resources.”
   • [probe] “PROBE runtime (recorded 2026-09-05): https://cloud.lambda.ai/api/v1/openapi.json serves the full Lambda Cloud API OpenAPI 3.1 spec (title 'L…”

   proof ↗⚑ flag

   Vast.ai✓fullclaimed8/10

   Docs explicitly describe creating scoped API keys with limited permissions for workloads/CI-CD/shared tooling via `vastai create api-key`, directly matching least-privilege agent credentialing, and this is reinforced by a dedicated api-keys reference page and the agent-skill docs describing agent-driven usage. Missing for 10: independent/hands-on verification of scope enforcement (e.g., testing that a scoped key actually blocks restricted actions) and detail on the granularity of available scopes.

   • [claimed-docs] “You can also create scoped keys with limited permissions using `vastai create api-key`, useful for CI/CD or shared tooling.”
   • [claimed-docs] “create a scoped key with only the permissions that workload needs”
   • [claimed-docs] “For shared tooling, CI/CD, or automation, create a scoped key with only the permissions that workload needs.”
   • [claimed-docs] “The `vastai` agent skill lets AI coding assistants drive Vast.ai on your behalf — create instances, deploy endpoints, manage SSH keys, check…”
   • [claimed-docs] “The vastai agent skill lets AI coding assistants drive Vast.ai on your behalf — create instances, deploy endpoints, manage SSH keys, check b…”

   proof ↗⚑ flag

7. ai-native userBuild against official SDKs

   weight 2 · round to Vast.ai
   Lambda~partialprobed3/10

   Lambda documents a public, key-gated REST/Cloud API with a full OpenAPI 3.1 spec that could underlie SDK development, but no official first-party SDK client libraries (Python/JS/etc.) are evidenced — only an unofficial third-party CLI/MCP server exists. Missing for 10: official SDK packages/libraries, first-party language bindings, docs referencing an 'SDK' rather than raw REST endpoints.

   • [claimed-docs] “You can also launch instances programmatically by using the Lambda Cloud API.”
   • [claimed-docs] “The Lambda Cloud API provides a set of REST API endpoints you can use to create and manage your Lambda Cloud resources.”
   • [probe] “PROBE runtime (recorded 2026-09-05): https://cloud.lambda.ai/api/v1/openapi.json serves the full Lambda Cloud API OpenAPI 3.1 spec (title 'L…”
   • [community] “A developer built an unofficial CLI and MCP server for Lambda cloud GPU instances, enabling AI agents to find, launch, and terminate Lambda …”

   proof ↗⚑ flag

   Vast.ai✓fullprobed9/10

   Vast.ai documents an official Python SDK (built alongside CLI) and REST API with OpenAPI spec, a documented migration path from the legacy vastai_sdk package, and runtime-probed confirmation that the CLI/SDK surface works live against the marketplace API. Documentation explicitly frames CLI/SDK as 'same operations, different syntax' with Python usage examples for serverless workflows, satisfying an AI-native builder's need for official SDK access. Missing for 10: independent (non-vendor) hands-on reports specifically validating the Python SDK's completeness/stability beyond CLI parity.

   • [claimed-docs] “The Vast.ai REST API gives you programmatic control over the entire platform. It's the foundation that the CLI and SDK are built on.”
   • [claimed-docs] “Automate with the CLI or SDK ... `vastai` from the shell or Python. Same operations, different syntax.”
   • [claimed-docs] “Interacting with Vast Serverless is made easy through a powerful python SDK.”
   • [github] “Migrating from vastai-sdk? The old import still works: from vastai_sdk import VastAI”
   • [probe] “PROBE openapi: HTTP 200 at https://docs.vast.ai/api/openapi.json — contains "openapi" key”
   • [probe] “PROBE runtime (recorded 2026-09-05): the official Vast.ai CLI (pypi `vastai`) installed via uvx and ran keylessly — `vastai --help` prints t…”
   • [probe] “PROBE runtime (recorded 2026-09-05): a bare keyless GET to https://console.vast.ai/api/v0/bundles/ returned live marketplace offers as JSON …”

   proof ↗⚑ flag

8. ai-native userSubscribe to events via webhooks

   weight 2 · round to Lambda
   Lambda~partialclaimed3/10

   Lambda's API docs mention webhook notifications only for support ticket events ('Lambda can send webhook notifications to your URL when support ticket events occur'), not for core compute/instance lifecycle events that an AI-native/agentic user would most want to subscribe to. missing for 10: webhook support for instance state changes or job/cluster events, first-party docs on webhook setup/payload schema, and independent confirmation of use in agentic workflows.

   • [claimed-docs] “Lambda can send webhook notifications to your URL when support ticket events occur,\nenabling near real-time integration with your systems.”

   proof ↗⚑ flag

   Vast.ai—none0/10

   No evidence of a webhook subscription mechanism anywhere in the docs, CLI, API reference, or probes; Vast.ai exposes REST API, CLI, and SDK for polling/imperative control but nothing describing event-driven push notifications or webhook callbacks. missing for 10: any documentation of webhook registration/endpoints, event types, or delivery/retry semantics.

   • [claimed-docs] “The Vast.ai REST API gives you programmatic control over the entire platform. It's the foundation that the CLI and SDK are built on.”
   • [claimed-docs] “The Vast.ai CLI gives you command-line access to the entire platform, authentication, GPU search, instance lifecycle, templates, volumes, se…”
   • [probe] “PROBE openapi: HTTP 200 at https://docs.vast.ai/api/openapi.json — contains "openapi" key”

   proof ↗⚑ flag

Agentic features

1. ai-native userSet up automations that run autonomously in the background

   weight 2 · round to Vast.ai
   Lambda—none0/10

   Lambda is GPU IaaS with an API, cloud-init for launch-time config, and webhooks for support tickets, but there is no native scheduler/automation service that runs workflows autonomously in the background; the only agentic automation (CLI/MCP server to launch/terminate instances via AI agents) is an unofficial third-party project, not a Lambda-native feature.

   • [claimed-docs] “The Lambda Cloud API provides a set of REST API endpoints you can use to create and manage your Lambda Cloud resources.”
   • [claimed-docs] “Lambda can send webhook notifications to your URL when support ticket events occur,\nenabling near real-time integration with your systems.”
   • [claimed-docs] “If you're launching your instance with the Lambda Cloud API, you can add launch-time configuration instructions using cloud-init”
   • [community] “A developer built an unofficial CLI and MCP server for Lambda cloud GPU instances, enabling AI agents to find, launch, and terminate Lambda …”

   proof ↗⚑ flag

   Vast.ai~partialprobed5/10

   Vast.ai exposes a CLI/SDK/REST API, scoped API keys for CI/CD, and an 'agent skill' letting AI coding assistants drive the platform (create instances, deploy endpoints, manage keys) — all usable to script automations, and Serverless endpoints let workloads run without manual GPU management. However, there is no evidence of a built-in scheduler, cron/trigger system, or persistent background job orchestration that runs autonomously without an external driver; automation depends on the user's own agent/script staying alive. Missing for 10: native scheduling/trigger mechanism, evidence of long-running autonomous background jobs, and independent confirmation of the agent-skill working unattended in production.

   • [claimed-docs] “The `vastai` agent skill lets AI coding assistants drive Vast.ai on your behalf — create instances, deploy endpoints, manage SSH keys, check…”
   • [claimed-docs] “The vastai agent skill lets AI coding assistants drive Vast.ai on your behalf — create instances, deploy endpoints, manage SSH keys, check b…”
   • [claimed-docs] “The vastai agent skill lets AI coding assistants drive Vast.ai on your behalf — create instances, deploy endpoints, manage SSH keys, check b…”
   • [claimed-docs] “You can also create scoped keys with limited permissions using `vastai create api-key`, useful for CI/CD or shared tooling.”
   • [claimed-docs] “create a scoped key with only the permissions that workload needs”
   • [claimed-docs] “For shared tooling, CI/CD, or automation, create a scoped key with only the permissions that workload needs.”
   • [claimed-docs] “Vast Serverless is an AI infrastructure platform that lets you run compute-intensive workloads without managing GPUs, paying for execution r…”
   • [claimed-docs] “Automate with the CLI or SDK ... `vastai` from the shell or Python. Same operations, different syntax.”
   • [probe] “PROBE runtime (recorded 2026-09-05): the official Vast.ai CLI (pypi `vastai`) installed via uvx and ran keylessly — `vastai --help` prints t…”

   proof ↗⚑ flag

2. ai-native userOperate the product with natural-language commands

   weight 2 · round to Vast.ai
   Lambda~partialprobed3/10

   Lambda itself only exposes a REST API (docs-1..41) with no first-party natural-language or agent interface; the only NL-command capability comes from a third-party developer's unofficial CLI/MCP server that lets AI agents launch/terminate instances via commands like 'launch an H100' (lambda-labs-comm-3). This is an extra, unofficial tool rather than a supported product feature. missing for 10: first-party NL/agent interface, official MCP server or chat-based control, documentation of natural-language command support.

   • [community] “A developer built an unofficial CLI and MCP server for Lambda cloud GPU instances, enabling AI agents to find, launch, and terminate Lambda …”
   • [claimed-docs] “The Lambda Cloud API provides a set of REST API endpoints you can use to create and manage your Lambda Cloud resources.”
   • [probe] “PROBE runtime (recorded 2026-09-05): https://cloud.lambda.ai/api/v1/openapi.json serves the full Lambda Cloud API OpenAPI 3.1 spec (title 'L…”

   proof ↗⚑ flag

   Vast.ai✓fullprobed7/10

   Vast.ai documents a dedicated 'vastai agent skill' explicitly designed so AI coding assistants can drive the platform on the user's behalf (create instances, deploy endpoints, manage keys, check balances) via natural-language-style interaction, backed by a full CLI/REST API surface. Missing for 10: independent or hands-on verification of the natural-language agent-skill flow itself (probes only confirm raw CLI/REST access, not NL interpretation), and no third-party account of an AI agent successfully using it end-to-end.

   • [claimed-docs] “The `vastai` agent skill lets AI coding assistants drive Vast.ai on your behalf — create instances, deploy endpoints, manage SSH keys, check…”
   • [claimed-docs] “The vastai agent skill lets AI coding assistants drive Vast.ai on your behalf — create instances, deploy endpoints, manage SSH keys, check b…”
   • [claimed-docs] “The vastai agent skill lets AI coding assistants drive Vast.ai on your behalf — create instances, deploy endpoints, manage SSH keys, check b…”
   • [claimed-docs] “The Vast.ai CLI gives you command-line access to the entire platform, authentication, GPU search, instance lifecycle, templates, volumes, se…”
   • [claimed-docs] “Automate with the CLI or SDK ... `vastai` from the shell or Python. Same operations, different syntax.”
   • [probe] “PROBE runtime (recorded 2026-09-05): the official Vast.ai CLI (pypi `vastai`) installed via uvx and ran keylessly — `vastai --help` prints t…”

   proof ↗⚑ flag

Api quality

1. ai-native userExplore an interactive API reference with runnable examples

   weight 2 · round to Vast.ai
   Lambda—none0/10

   Lambda exposes a raw OpenAPI 3.1 spec (cloud.lambda.ai/api/v1/openapi.json) and documents REST endpoints, but there is no evidence of an interactive, browsable API reference (e.g., Swagger UI, 'try it out' console) with runnable examples — probes for docs.lambda.ai/openapi.json, swagger.json, and llms.txt all 404.

   • [claimed-docs] “The Lambda Cloud API provides a set of REST API endpoints you can use to create and manage your Lambda Cloud resources.”
   • [claimed-docs] “The Lambda Cloud API provides a set of REST API endpoints you can use to create\nand manage your Lambda Cloud resources.”
   • [probe] “PROBE llms.txt: HTTP 404 at https://docs.lambda.ai/llms.txt”
   • [probe] “PROBE openapi: all candidate paths 404 (https://docs.lambda.ai/openapi.json, https://docs.lambda.ai/swagger.json, https://docs.lambda.ai/api…”
   • [probe] “PROBE runtime (recorded 2026-09-05): https://cloud.lambda.ai/api/v1/openapi.json serves the full Lambda Cloud API OpenAPI 3.1 spec (title 'L…”

   proof ↗⚑ flag

   Vast.ai~partialprobed4/10

   Vast.ai publishes a machine-readable OpenAPI spec and API-reference docs, and the CLI docs include copy-pasteable, runnable example commands that were verified to work live (search offers, create instance) without auth — showing some 'runnable example' quality. However there is no evidence of an interactive API console (e.g., embedded 'try it' Swagger-UI style playground) on the docs site itself. Missing for 10: an interactive in-browser API explorer/console, explicit 'try it now' runnable request execution within the API reference pages, and independent confirmation of such interactivity.

   • [claimed-docs] “The Vast.ai REST API gives you programmatic control over the entire platform. It's the foundation that the CLI and SDK are built on.”
   • [claimed-docs] “The Vast.ai REST API gives you programmatic control over the entire platform.”
   • [probe] “PROBE openapi: HTTP 200 at https://docs.vast.ai/api/openapi.json — contains "openapi" key”
   • [probe] “PROBE runtime (recorded 2026-09-05): the official Vast.ai CLI (pypi `vastai`) installed via uvx and ran keylessly — `vastai --help` prints t…”
   • [probe] “PROBE runtime (recorded 2026-09-05): `vastai search offers 'gpu_name=RTX_4090 num_gpus=1' -o dph` searched the LIVE GPU marketplace with NO …”

   proof ↗⚑ flag

2. ai-native userDownload a machine-readable API spec (OpenAPI or equivalent)

   weight 2 · round drawn
   Lambda✓fullprobed9/10

   Lambda publishes a live, machine-readable OpenAPI 3.1 spec for its Cloud API at https://cloud.lambda.ai/api/v1/openapi.json, confirmed both by docs references and a runtime probe that fetched the full spec keylessly. Minor gap: the probe found the docs.lambda.ai domain itself doesn't serve openapi.json at the expected conventional path (404s), requiring the correct subdomain. missing for 10: independent third-party confirmation of spec completeness/versioning beyond the runtime probe.

   • [claimed-docs] “The Lambda Cloud API provides a set of REST API endpoints you can use to create and manage your Lambda Cloud resources.”
   • [claimed-docs] “The Lambda Cloud API provides a set of REST API endpoints you can use to create\nand manage your Lambda Cloud resources.”
   • [probe] “PROBE runtime (recorded 2026-09-05): https://cloud.lambda.ai/api/v1/openapi.json serves the full Lambda Cloud API OpenAPI 3.1 spec (title 'L…”
   • [probe] “PROBE openapi: all candidate paths 404 (https://docs.lambda.ai/openapi.json, https://docs.lambda.ai/swagger.json, https://docs.lambda.ai/api…”

   proof ↗⚑ flag

   Vast.ai✓fullprobed9/10

   Vast.ai publishes a live OpenAPI spec at docs.vast.ai/api/openapi.json (verified HTTP 200 with an 'openapi' key), backed by a full REST API reference and CLI/SDK built on it. Missing for 10: no independent third-party confirmation that the spec is comprehensive/kept in sync beyond the probe check.

   • [probe] “PROBE openapi: HTTP 200 at https://docs.vast.ai/api/openapi.json — contains "openapi" key”
   • [claimed-docs] “The Vast.ai REST API gives you programmatic control over the entire platform. It's the foundation that the CLI and SDK are built on.”
   • [claimed-docs] “The Vast.ai REST API gives you programmatic control over the entire platform.”
   • [probe] “PROBE runtime (recorded 2026-09-05): a bare keyless GET to https://console.vast.ai/api/v0/bundles/ returned live marketplace offers as JSON …”

   proof ↗⚑ flag

3. ai-native userRely on versioned APIs with a documented deprecation policy

   weight 2 · round to Lambda
   Lambda~partialprobed3/10

   The Lambda Cloud API is clearly versioned (path-based v1, documented via a live OpenAPI 3.1 spec with rate limits), satisfying the 'versioned APIs' half of the story, but no evidence anywhere in the pack mentions a deprecation policy, versioning changelog, or sunset process for older API versions. Missing for 10: documented deprecation/versioning policy, changelog of breaking changes, migration guidance between API versions, independent confirmation of stability guarantees.

   • [claimed-docs] “The Lambda Cloud API provides a set of REST API endpoints you can use to create and manage your Lambda Cloud resources.”
   • [claimed-docs] “The Lambda Cloud API provides a set of REST API endpoints you can use to create\nand manage your Lambda Cloud resources.”
   • [probe] “PROBE runtime (recorded 2026-09-05): https://cloud.lambda.ai/api/v1/openapi.json serves the full Lambda Cloud API OpenAPI 3.1 spec (title 'L…”

   proof ↗⚑ flag

   Vast.ai—none0/10

   Evidence shows Vast.ai has a REST API, OpenAPI spec, and CLI/SDK, but there is no documentation of API versioning scheme or a deprecation policy anywhere in the pack; the only related signal is a backward-compatible import shim for the old SDK (vast-ai-gh-2), which is not a documented policy.

   • [claimed-docs] “The Vast.ai REST API gives you programmatic control over the entire platform. It's the foundation that the CLI and SDK are built on.”
   • [probe] “PROBE openapi: HTTP 200 at https://docs.vast.ai/api/openapi.json — contains "openapi" key”
   • [github] “Migrating from vastai-sdk? The old import still works: from vastai_sdk import VastAI”

   proof ↗⚑ flag

1. ai-native userPerform bulk operations across many items at once

   weight 2 · round to Vast.ai
   Lambda~partialprobed5/10

   Lambda supports large-scale provisioning (1-Click Clusters of 16–512+ GPUs, Slurm-based multi-node job scheduling) and a REST API for programmatic instance management, which lets an AI-native user manage many GPU resources at once. However, the documented API is rate-limited to 1 req/s (and launches limited per 12s), with no evidence of true bulk/batch endpoints for creating, updating, or deleting many items in a single call. Missing for 10: explicit bulk-create/bulk-delete API operations, batch job submission tooling beyond Slurm's node scheduling, and evidence of high-throughput automation without rate-limit friction.

   • [claimed-docs] “You can also launch instances programmatically by using the Lambda Cloud API.”
   • [claimed-docs] “1-Click Clusters (1CC) are high-performance clusters composed of both GPU and CPU nodes, featuring 16 to 512 NVIDIA H100 or B200 SXM Tensor …”
   • [claimed-docs] “Production-ready clusters from 16 to 2,000+ NVIDIA B200 or H100 GPUs.”
   • [claimed-docs] “Slurm automatically schedules workloads, maximizing cluster utilization while preventing resource contention.”
   • [probe] “PROBE runtime (recorded 2026-09-05): https://cloud.lambda.ai/api/v1/openapi.json serves the full Lambda Cloud API OpenAPI 3.1 spec (title 'L…”

   proof ↗⚑ flag

   Vast.ai~partialprobed6/10

   The CLI and REST API expose full programmatic control (search, create, destroy, manage keys) and are explicitly positioned for automation/scripting from shell or Python, which lets an AI-native user loop over many offers/instances (e.g., filtered searches returning many GPU offers at once). However, there is no documented native batch/bulk endpoint (e.g., one call to create or destroy N instances simultaneously) — only single-item CRUD operations that must be scripted in a loop. Missing for 10: explicit bulk/batch API endpoints or CLI flags for multi-item operations, and community/hands-on confirmation of bulk usage at scale.

   • [claimed-docs] “The Vast.ai CLI gives you command-line access to the entire platform, authentication, GPU search, instance lifecycle, templates, volumes, se…”
   • [claimed-docs] “The Vast.ai REST API gives you programmatic control over the entire platform. It's the foundation that the CLI and SDK are built on.”
   • [claimed-docs] “Automate with the CLI or SDK ... `vastai` from the shell or Python. Same operations, different syntax.”
   • [github] “vast.search_offers(query='gpu_name=RTX_4090 num_gpus>=4')”
   • [claimed-docs] “vastai search offers 'gpu_name=RTX_4090 num_gpus=1 verified=true direct_port_count>=1 rentable=true' -o 'dlperf_usd-'”
   • [probe] “PROBE runtime (recorded 2026-09-05): the official Vast.ai CLI (pypi `vastai`) installed via uvx and ran keylessly — `vastai --help` prints t…”
   • [probe] “PROBE runtime (recorded 2026-09-05): `vastai search offers 'gpu_name=RTX_4090 num_gpus=1' -o dph` searched the LIVE GPU marketplace with NO …”

   proof ↗⚑ flag

2. ai-native userDefine rules that trigger actions automatically on events

   weight 3 · round to Vast.ai
   Lambda—none0/10

   Lambda is a GPU IaaS provider; the only event-triggered mechanism found is webhook notifications for support-ticket events (docs-40) and cloud-init instructions applied only at launch time (docs-6, docs-24, docs-32) — neither constitutes a general rules/automation engine letting users define arbitrary triggers-to-actions. No autoscaling policies, alert-based actions, or rule-definition UI/API are documented. missing for 10: a general event-rule engine (define trigger conditions + arbitrary actions), autoscaling/alerting automation, and any first-party support beyond narrow support-ticket webhooks.

   • [claimed-docs] “Lambda can send webhook notifications to your URL when support ticket events occur,\nenabling near real-time integration with your systems.”
   • [claimed-docs] “you can add launch-time configuration instructions using [cloud-init]”
   • [claimed-docs] “If you're launching your instance with the Lambda Cloud API, you can add launch-time configuration instructions using cloud-init”

   proof ↗⚑ flag

   Vast.ai~partialclaimed4/10

   Vast.ai documents 'autobilling', an explicit event-triggered rule (balance drops low → auto top-up from saved card), which is genuine automation-on-event. Beyond that, evidence only shows generic CLI/SDK/API scripting and agent-skill hooks for manual automation, not a broader rules/trigger engine (no webhooks, alerts, or conditional actions for instance events like preemption, cost thresholds, or health failures). Missing for 10: a general-purpose event/trigger system (webhooks, alerting, conditional rules) beyond the single billing use case, and independent confirmation of its reliability.

   • [claimed-docs] “Use the autobilling feature to have the system automatically top up your account using a saved credit card when it runs low.”
   • [claimed-docs] “Autobilling keeps your balance positive to protect your instances from interruption or deletion.”
   • [claimed-docs] “Automate with the CLI or SDK ... `vastai` from the shell or Python. Same operations, different syntax.”
   • [claimed-docs] “For shared tooling, CI/CD, or automation, create a scoped key with only the permissions that workload needs.”

   proof ↗⚑ flag

3. ai-native userSchedule recurring jobs or workflows

   weight 2 · round drawn
   Lambda—none0/10

   Lambda offers Slurm-based job scheduling for HPC workloads and a REST API with cloud-init for launch-time configuration, but none of the evidence describes a mechanism for scheduling recurring/cron-like jobs or automated recurring workflows — Slurm here is described as scheduling submitted workloads, not recurring automation. missing for 10: any cron/recurring job scheduler, workflow orchestration triggers, or documentation of repeat/interval-based job execution.

   • [claimed-docs] “Slurm automatically schedules workloads, maximizing cluster utilization while preventing resource contention.”
   • [claimed-docs] “The quick start takes you from SSH to your first multi-node GPU job in minutes.”
   • [claimed-docs] “Lambda monitors and maintains the health of Slurm daemons such as slurmctld and slurmdbd.”
   • [claimed-docs] “Lambda monitors and maintains the health of Slurm daemons such as `slurmctld` and `slurmdbd`.”
   • [claimed-docs] “The Lambda Cloud API provides a set of REST API endpoints you can use to create and manage your Lambda Cloud resources.”

   proof ↗⚑ flag

   Vast.ai—none0/10

   Vast.ai's evidence covers CLI/API/SDK for instance and serverless management but contains no mention of a built-in scheduler, cron-like recurring job feature, or workflow orchestration; users would have to bring their own external scheduler to hit the API/CLI repeatedly, which isn't documented as a first-party capability.

   ⚑ flag

Availability

1. ml engineerSee real-time GPU availability by type and region before I try to provision, instead of discovering stockouts by failure

   weight 2 · round to Vast.ai
   Lambda—none0/10

   The evidence describes Lambda's instance types, API endpoints for launching/managing instances, and pricing, but nowhere shows a real-time GPU availability/capacity view by type and region that an engineer could check before provisioning. Docs even describe access as 'first-come' (docs-28), implying no visibility into stock levels, and no dashboard or API field for capacity-by-region is mentioned.

   • [claimed-docs] “ODC offers a variety of predefined instance types to support different workload requirements. Available GPUs include the state-of-the-art NV…”
   • [claimed-docs] “Deploy NVIDIA B200, H100, A100, or GH200 instances in minutes with self-serve, first-come access.”
   • [claimed-docs] “The Lambda Cloud API provides a set of REST API endpoints you can use to create and manage your Lambda Cloud resources.”
   • [claimed-docs] “The Lambda Cloud API provides a set of REST API endpoints you can use to create\nand manage your Lambda Cloud resources.”

   proof ↗⚑ flag

   Vast.ai✓fullprobed8/10

   Vast.ai's search/offers API and CLI let engineers query live marketplace inventory (GPU type, count, verified status, price) before renting, and this was independently confirmed via a keyless live probe against both the CLI and the public REST bundles endpoint returning real-time offers with reliability data. This directly satisfies seeing availability before provisioning rather than hitting a stockout on create. missing for 10: explicit region/geolocation filter documentation and evidence of real-time refresh/alerting for capacity changes.

   • [claimed-docs] “vastai search offers 'gpu_name=RTX_4090 num_gpus=1 verified=true direct_port_count>=1 rentable=true' -o 'dlperf_usd-'”
   • [claimed-docs] “The search page is the main portal for finding good machines and creating instances on them.”
   • [github] “vast.search_offers(query='gpu_name=RTX_4090 num_gpus>=4')”
   • [probe] “PROBE runtime (recorded 2026-09-05): `vastai search offers 'gpu_name=RTX_4090 num_gpus=1' -o dph` searched the LIVE GPU marketplace with NO …”
   • [probe] “PROBE runtime (recorded 2026-09-05): a bare keyless GET to https://console.vast.ai/api/v0/bundles/ returned live marketplace offers as JSON …”

   proof ↗⚑ flag

Hardware

1. ml engineerChoose from current-generation datacenter GPUs (H100/H200/B200 class) as well as cheaper previous-generation options

   weight 2 · round to Lambda
   Lambda✓fullcommunity9/10

   Lambda's docs clearly list current-gen H100/B200 (and GH200) options alongside older A100 in on-demand instances and clusters, covering both current and previous-generation GPU tiers with flexible on-demand access. Missing for 10: no explicit pricing comparison table or independent benchmark confirming actual availability/pricing tiers side-by-side.

   • [claimed-docs] “ODC offers a variety of predefined instance types to support different workload requirements. Available GPUs include the state-of-the-art NV…”
   • [claimed-docs] “Deploy NVIDIA B200, H100, A100, or GH200 instances in minutes with self-serve, first-come access.”
   • [claimed-docs] “1-Click Clusters (1CC) are high-performance clusters composed of both GPU and CPU nodes, featuring 16 to 512 NVIDIA H100 or B200 SXM Tensor …”
   • [claimed-docs] “Production-ready clusters from 16 to 2,000+ NVIDIA B200 or H100 GPUs.”
   • [community] “Lambda Labs dropped H100 on-demand GPU pricing to $1.99/GPU/Hour (announced via Twitter, June 2023).”

   proof ↗⚑ flag

   Vast.ai~partialprobed5/10

   Vast.ai's docs and CLI clearly support searching/filtering the marketplace by GPU model (e.g., `gpu_name=RTX_4090`) and offer tiered pricing (on-demand, reserved, interruptible) that would let an ML engineer pick pricier or cheaper GPU options, and 'Secure Cloud (Datacenter)' verification implies access to datacenter-grade hardware. However, none of the evidence explicitly confirms availability of current-generation H100/H200/B200-class GPUs alongside older cards — all concrete examples in the pack use RTX_4090 (a consumer card), not datacenter-tier flagship GPUs. Missing for 10: explicit documentation or listing showing H100/H200/B200 GPUs are actually rentable on the platform alongside cheaper previous-gen options.

   • [github] “vast.search_offers(query='gpu_name=RTX_4090 num_gpus>=4')”
   • [claimed-docs] “vastai search offers 'gpu_name=RTX_4090 num_gpus=1 verified=true direct_port_count>=1 rentable=true' -o 'dlperf_usd-'”
   • [claimed-docs] “Secure Cloud (Datacenter): These machines are verified and confirmed to be in a certified datacenter that meets our datacenter criteria.”
   • [claimed-docs] “Vast verifies that these machines are in a datacenter with a TIER 2/3 rating or ISO 27001. These offer cards have a blue label and are recom…”
   • [claimed-docs] “Reserved instances allow you to get significant discounts (up to 50%) by pre-paying for GPU time. You can convert any on-demand instance to …”
   • [claimed-docs] “Interruptible instances use a bidding system: **Lowest cost** (often 50%+ cheaper than on-demand)”
   • [probe] “PROBE runtime (recorded 2026-09-05): `vastai search offers 'gpu_name=RTX_4090 num_gpus=1' -o dph` searched the LIVE GPU marketplace with NO …”

   proof ↗⚑ flag

Quotas

1. platform engineerSee documented quotas and instance limits and raise them through a defined process

   weight 2 · round drawn
   Lambda—none0/10

   Evidence shows only generic API rate limits and a vague 'contact us for reserved capacity' pricing note, but no documented per-account instance/GPU quotas nor any defined process (e.g., support ticket workflow, quota dashboard) to request limit increases.

   • [claimed-docs] “Contact us for reserved capacity at our lowest prices.”
   • [probe] “PROBE runtime (recorded 2026-09-05): https://cloud.lambda.ai/api/v1/openapi.json serves the full Lambda Cloud API OpenAPI 3.1 spec (title 'L…”

   proof ↗⚑ flag

   Vast.ai—none0/10

   The evidence pack covers billing, autobilling, reserved/interruptible instance pricing, API keys, and CLI/SDK usage, but contains no documentation of account quotas, per-user instance limits, or a defined process to request limit increases. This axis is applicable to any capacity-oriented GPU marketplace, so absence of evidence yields 'none'. Missing for 10: documented quota/limit tables, a support/ticket process for raising limits, any mention of default instance caps or how to request more capacity.

   ⚑ flag

Clusters

1. ml engineerProvision a multi-node GPU cluster with fast interconnect for distributed training without a sales cycle

   weight 3 · round to Lambda
   Lambda✓fullprobed9/10

   Lambda offers self-serve 1-Click Clusters (16-512 H100/B200 GPUs) with GPUDirect RDMA up to 3200 Gb/s, launched instantly with no long-term commitment and no sales cycle mentioned, plus Managed Slurm/Kubernetes for orchestration and a live self-serve API confirmed by runtime probe. Community evidence corroborates self-serve on-demand access and even third-party tooling built on the API, though no independent hands-on report specifically confirms multi-node cluster provisioning experience. Missing for 10: independent/hands-on validation of the 1-Click Cluster provisioning flow itself and interconnect performance in practice.

   • [claimed-docs] “1-Click Clusters (1CC) are high-performance clusters composed of both GPU and CPU nodes, featuring 16 to 512 NVIDIA H100 or B200 SXM Tensor …”
   • [claimed-docs] “1-Click Clusters (1CC) are high-performance clusters composed of both GPU and CPU nodes, featuring 16 to 512 NVIDIA H100 or B200 SXM Tensor …”
   • [claimed-docs] “The quick start takes you from SSH to your first multi-node GPU job in minutes.”
   • [claimed-docs] “Production-ready clusters from 16 to 2,000+ NVIDIA B200 or H100 GPUs.”
   • [claimed-docs] “Deploy NVIDIA B200, H100, A100, or GH200 instances in minutes with self-serve, first-come access.”
   • [claimed-docs] “The Lambda Cloud API provides a set of REST API endpoints you can use to create and manage your Lambda Cloud resources.”
   • [probe] “PROBE runtime (recorded 2026-09-05): https://cloud.lambda.ai/api/v1/openapi.json serves the full Lambda Cloud API OpenAPI 3.1 spec (title 'L…”
   • [community] “A developer built an unofficial CLI and MCP server for Lambda cloud GPU instances, enabling AI agents to find, launch, and terminate Lambda …”

   proof ↗⚑ flag

   Vast.ai!disputedcontradicted5/10

   Docs describe self-service, no-sales-cycle provisioning (CLI/API/search offers for multi-GPU nodes) and an overlay-network feature specifically for multi-node NCCL/PyTorch training, which addresses the 'no sales cycle' and 'multi-node' parts of the story. However, independent hands-on reports describe bandwidth as 'lousy' and 'all over the place compared to what's listed in the console,' directly undercutting the 'fast interconnect' claim needed for distributed training performance. Missing for 10: documented interconnect specs (e.g. InfiniBand/NVLink bandwidth guarantees), benchmarked multi-node throughput, and independent confirmation that overlay networking delivers low-latency performance at scale.

   • [claimed-docs] “Vast now supports creating *overlay* networks for instances, allowing client instances on different machines on the same physical LAN to sha…”
   • [claimed-docs] “Vast now supports creating overlay networks for instances, allowing client instances on different machines on the same physical LAN to share…”
   • [github] “vast.search_offers(query='gpu_name=RTX_4090 num_gpus>=4')”
   • [claimed-docs] “search for a GPU, rent it, wait for it to boot, connect to it, copy data, and clean up”
   • [community] “Prices for compute were competitive, but most instances had lousy bandwidth. You don't need bandwidth to run bitcoin miners, apparently. The…”
   • [community] “As a client (renting GPUs) I've found it to be pretty unreliable. I've tried renting GPUs a handful of times and hosts, bandwidth, and perfo…”

   proof ↗⚑ flag

Orchestration

1. platform engineerSchedule jobs on managed Slurm or Kubernetes instead of building my own scheduler on raw nodes

   weight 2 · round to Lambda
   Lambda✓fullclaimed8/10

   Lambda offers Managed Slurm and Managed Kubernetes (MK8s) as first-party managed schedulers on top of 1-Click Clusters, with Slurm handling automatic job scheduling/utilization and daemon health monitoring, and MK8s providing preconfigured GPU/RDMA Kubernetes clusters ready for workload deployment — directly fulfilling the 'managed scheduler instead of building your own' story. Missing for 10: independent/hands-on validation of Slurm or K8s job scheduling in production (community evidence only covers billing and unofficial CLI tooling, not scheduler usage), and no detail on multi-tenancy/queue customization depth.

   • [claimed-docs] “MK8s provides a Kubernetes environment with GPU and InfiniBand (RDMA) support, and shared persistent storage across all nodes in a 1CC.”
   • [claimed-docs] “Lambda provides support according to the service level agreements (SLAs) in place with the customer.”
   • [claimed-docs] “The quick start takes you from SSH to your first multi-node GPU job in minutes.”
   • [claimed-docs] “Lambda monitors and maintains the health of Slurm daemons such as slurmctld and slurmdbd.”
   • [claimed-docs] “MK8s provides a Kubernetes environment with GPU and InfiniBand (RDMA) support, and shared persistent storage across all nodes in a 1CC. Clus…”
   • [claimed-docs] “Lmod for environment management: Use Lmod to dynamically load and unload software modules available on the cluster, such as HPC-X, Node.js, …”
   • [claimed-docs] “Slurm automatically schedules workloads, maximizing cluster utilization while preventing resource contention.”
   • [claimed-docs] “Lambda monitors and maintains the health of Slurm daemons such as `slurmctld` and `slurmdbd`.”

   proof ↗⚑ flag

   Vast.ai—none0/10

   Evidence shows Vast.ai provides raw GPU instance rental, templates, overlay networking for multi-node training, and CLI/API automation, but nothing about a managed Slurm or Kubernetes scheduling service — users would need to build their own scheduler on top of raw nodes. missing for 10: managed Slurm service, managed Kubernetes service, any orchestration layer beyond raw instance provisioning.

   • [claimed-docs] “Vast now supports creating *overlay* networks for instances, allowing client instances on different machines on the same physical LAN to sha…”
   • [claimed-docs] “Vast now supports creating overlay networks for instances, allowing client instances on different machines on the same physical LAN to share…”
   • [claimed-docs] “A template is how Vast helps you launch an instance, setting up your rented machine with whatever software and formatting you need.”
   • [claimed-docs] “The Vast.ai CLI gives you command-line access to the entire platform, authentication, GPU search, instance lifecycle, templates, volumes, se…”

   proof ↗⚑ flag

1. ai-native userDo everything through the API that I can do in the UI

   weight 2 · round to Vast.ai
   Lambda~partialprobed6/10

   Lambda publishes a live, documented REST API (OpenAPI spec, key-gated) covering core instance lifecycle actions (launch, list, terminate, cloud-init, custom images) that mirror UI capabilities for On-Demand Cloud instances, and third parties have built agent-facing CLIs/MCP wrappers on top of it. However, evidence doesn't show API parity for other UI-managed features like firewall rules, filesystem management, 1-Click Cluster/Slurm cluster provisioning, or usage/billing dashboards. Missing for 10: documented API endpoints for firewalls, filesystems, 1CC/Slurm cluster lifecycle, and usage/billing views; independent confirmation of full UI-API parity.

   • [claimed-docs] “You can also launch instances programmatically by using the Lambda Cloud API.”
   • [claimed-docs] “You can also launch instances programmatically by using the Lambda Cloud API. For details, see Launch instances”
   • [claimed-docs] “the API allows you to use a different base image for your instance”
   • [claimed-docs] “The Lambda Cloud API provides a set of REST API endpoints you can use to create and manage your Lambda Cloud resources.”
   • [claimed-docs] “The Lambda Cloud API provides a set of REST API endpoints you can use to create\nand manage your Lambda Cloud resources.”
   • [probe] “PROBE runtime (recorded 2026-09-05): https://cloud.lambda.ai/api/v1/openapi.json serves the full Lambda Cloud API OpenAPI 3.1 spec (title 'L…”
   • [community] “A developer built an unofficial CLI and MCP server for Lambda cloud GPU instances, enabling AI agents to find, launch, and terminate Lambda …”

   proof ↗⚑ flag

   Vast.ai✓fullprobed9/10

   Vast.ai's REST API is explicitly documented as the foundation underlying both the CLI and SDK, giving full programmatic control over the entire platform (search, instance lifecycle, templates, volumes, serverless endpoints), and this is corroborated by a live OpenAPI spec and runtime probes showing the CLI/API perform the same search/rent/manage operations available in the UI, including a dedicated agent skill for AI assistants to drive the platform. Minor gap: no explicit UI-vs-API feature parity audit exists confirming literally every UI-only setting (e.g., some billing/account UI screens) has an API equivalent. Missing for 10: an explicit parity matrix or independent confirmation that 100% of UI actions (not just core lifecycle) are API-exposed.

   • [claimed-docs] “The Vast.ai CLI gives you command-line access to the entire platform, authentication, GPU search, instance lifecycle, templates, volumes, se…”
   • [claimed-docs] “The Vast.ai REST API gives you programmatic control over the entire platform. It's the foundation that the CLI and SDK are built on.”
   • [claimed-docs] “The Vast.ai REST API gives you programmatic control over the entire platform.”
   • [claimed-docs] “Automate with the CLI or SDK ... `vastai` from the shell or Python. Same operations, different syntax.”
   • [claimed-docs] “The vastai agent skill lets AI coding assistants drive Vast.ai on your behalf — create instances, deploy endpoints, manage SSH keys, check b…”
   • [probe] “PROBE openapi: HTTP 200 at https://docs.vast.ai/api/openapi.json — contains "openapi" key”
   • [probe] “PROBE runtime (recorded 2026-09-05): the official Vast.ai CLI (pypi `vastai`) installed via uvx and ran keylessly — `vastai --help` prints t…”
   • [probe] “PROBE runtime (recorded 2026-09-05): `vastai search offers 'gpu_name=RTX_4090 num_gpus=1' -o dph` searched the LIVE GPU marketplace with NO …”
   • [probe] “PROBE runtime (recorded 2026-09-05): a bare keyless GET to https://console.vast.ai/api/v0/bundles/ returned live marketplace offers as JSON …”

   proof ↗⚑ flag

2. ai-native userExport all of my data in open formats and leave

   weight 3 · round to Lambda
   Lambda~partialclaimed6/10

   Lambda's filesystems support S3-compatible tools like rclone and s5cmd, letting users copy datasets and files out in standard, open formats rather than being locked into a proprietary export mechanism, and the Cloud API allows programmatic access to resource metadata. However, there's no explicit documentation of a full account-data export (billing, usage history, configs) or a one-click 'export everything and leave' workflow. Missing for 10: explicit full-account data export/portability guarantee, documentation of exporting non-file data (billing/usage/API keys), independent verification that egress is unrestricted or free of lock-in fees.

   • [claimed-docs] “This adapter allows you to use S3-compatible tools like rclone and s5cmd to copy files to and from your filesystems and perform common file …”
   • [claimed-docs] “This adapter allows you to use S3-compatible tools like `rclone` and `s5cmd` to copy files to and from your filesystems”
   • [claimed-docs] “A filesystem is a high-capacity regional file store you can attach to your instance to store datasets and back up system state.”
   • [claimed-docs] “The Lambda Cloud API provides a set of REST API endpoints you can use to create and manage your Lambda Cloud resources.”

   proof ↗⚑ flag

   Vast.ai~partialclaimed3/10

   Vast.ai instances run standard Linux with SSH access explicitly described as supporting file transfer ('Transfer files without exposing your data') and volumes are persistent, detachable storage, implying no proprietary lock-in on user data — but there is no explicit documentation of a bulk data-export feature, open-format guarantee, or account-closure data portability process. missing for 10: explicit data-export/portability documentation, statement on open formats, and evidence of full account data extraction on leaving.

   • [claimed-docs] “Log in securely, Run commands remotely, Transfer files without exposing your data”
   • [claimed-docs] “SSH (Secure Shell) is a protocol for safely connecting to remote servers. It encrypts your connection so you can: Log in securely, Run comma…”
   • [claimed-docs] “Volumes provide persistent storage that survives instance destruction and can be reattached to new instances.”

   proof ↗⚑ flag

Billing

1. platform engineerPull usage and billing breakdowns programmatically to attribute GPU spend by team or workload

   weight 2 · round to Vast.ai
   Lambda—none0/10

   Lambda's docs describe billing by hourly/minute increments and a web 'Usage page' with an Instances tab for viewing monthly usage (lambda-labs-docs-10, lambda-labs-docs-20), but this is UI-only, not a programmatic API. The published Lambda Cloud API (lambda-labs-docs-31/39, confirmed live via probe) covers instance provisioning/management, not billing or usage export, and no team/workload cost-attribution tagging or billing API endpoint is documented anywhere in the evidence.

   • [claimed-docs] “ODC prices instances by hourly usage and bills in one-minute increments.”
   • [claimed-docs] “To view your monthly usage, navigate to the [Usage page]...and then click the **Instances** tab.”
   • [claimed-docs] “The Lambda Cloud API provides a set of REST API endpoints you can use to create and manage your Lambda Cloud resources.”
   • [claimed-docs] “The Lambda Cloud API provides a set of REST API endpoints you can use to create\nand manage your Lambda Cloud resources.”
   • [probe] “PROBE runtime (recorded 2026-09-05): https://cloud.lambda.ai/api/v1/openapi.json serves the full Lambda Cloud API OpenAPI 3.1 spec (title 'L…”

   proof ↗⚑ flag

   Vast.ai~partialclaimed4/10

   Vast.ai's REST API and CLI provide general programmatic access to the platform, including account balance checks and billing pages (autobilling, credit top-up), and scoped API keys can be created per workload/team for CI/CD use, which could support some cost attribution. However there is no explicit evidence of a dedicated usage/billing breakdown endpoint, cost tagging, or per-team/workload spend reporting API. missing for 10: dedicated billing/usage export API, cost tagging or labels for spend attribution, documented reports/analytics endpoint for team-level breakdowns.

   • [claimed-docs] “The Vast.ai REST API gives you programmatic control over the entire platform. It's the foundation that the CLI and SDK are built on.”
   • [claimed-docs] “Use the autobilling feature to have the system automatically top up your account using a saved credit card when it runs low.”
   • [claimed-docs] “create a scoped key with only the permissions that workload needs”
   • [claimed-docs] “For shared tooling, CI/CD, or automation, create a scoped key with only the permissions that workload needs.”
   • [claimed-docs] “Autobilling keeps your balance positive to protect your instances from interruption or deletion.”

   proof ↗⚑ flag

2. ml engineerI am billed at per-second or per-minute granularity and only while my instance is actually running

   weight 3 · round to Lambda
   Lambda✓fullcommunity8/10

   Lambda's docs explicitly state ODC instances are priced hourly but billed in one-minute increments, and billing only accrues while an instance is running/attached — corroborated by a community report where a user was billed for the full duration their instance remained running (idle counted as running, confirming billing follows instance lifecycle rather than usage activity). Missing for 10: true per-second billing granularity (only per-minute is documented), and independent/user confirmation that billing precisely matches the one-minute increment claim.

   • [claimed-docs] “ODC prices instances by hourly usage and bills in one-minute increments.”
   • [community] “User left a Lambda Labs GH200 instance running after brief testing and was billed $583 for 391 hours. Lambda's support said: 'Lambda does no…”

   proof ↗⚑ flag

   Vast.ai—none0/10

   Evidence shows Vast.ai quotes prices as hourly rates (dph/dph_total) and discusses reserved/interruptible pricing models and autobilling, but nowhere does the evidence pack confirm sub-hour (per-second or per-minute) billing granularity or explicitly state billing stops precisely when an instance is not running.

   ⚑ flag

Discovery

1. ai agentQuery the GPU catalog with live pricing and availability from a public or documented endpoint before committing any spend

   weight 2 · round to Vast.ai
   Lambda~partialprobed6/10

   Lambda publishes a full OpenAPI 3.1 spec for its Cloud API keylessly (lambda-labs-probe-rt-1), and docs confirm the API is used to create/manage instances programmatically (lambda-labs-docs-5, lambda-labs-docs-23, lambda-labs-docs-31/39), with a separate public pricing page (lambda-labs-docs-41). An unofficial MCP/CLI already lets agents launch/terminate Lambda GPUs (lambda-labs-comm-3), implying some catalog query capability exists. However, actual provisioning calls (e.g. /instances) require an API key (401 per probe), and no evidence explicitly shows a documented, unauthenticated 'instance-types/catalog' endpoint returning live pricing+availability distinct from the static marketing pricing page. Missing for 10: explicit documentation of a public catalog/instance-types endpoint with live pricing+availability, and independent confirmation an agent can query it pre-spend without a key.

   • [probe] “PROBE runtime (recorded 2026-09-05): https://cloud.lambda.ai/api/v1/openapi.json serves the full Lambda Cloud API OpenAPI 3.1 spec (title 'L…”
   • [claimed-docs] “The Lambda Cloud API provides a set of REST API endpoints you can use to create and manage your Lambda Cloud resources.”
   • [claimed-docs] “The Lambda Cloud API provides a set of REST API endpoints you can use to create\nand manage your Lambda Cloud resources.”
   • [claimed-docs] “Clear, straightforward pricing for Instances, 1-Click Clusters™, and Superclusters.”
   • [community] “A developer built an unofficial CLI and MCP server for Lambda cloud GPU instances, enabling AI agents to find, launch, and terminate Lambda …”
   • [claimed-docs] “You can also launch instances programmatically by using the Lambda Cloud API.”

   proof ↗⚑ flag

   Vast.ai✓fullprobed9/10

   Vast.ai provides both a documented public REST endpoint (bundles/offers) and CLI (`vastai search offers`) that return live GPU pricing, specs, and availability without requiring an account or API key, verified via runtime probes. This directly matches the story of an agent querying the catalog before committing spend; missing for 10: independent third-party corroboration beyond vendor docs/probes and no explicit rate-limit/auth-tier documentation for heavy automated querying.

   • [probe] “PROBE runtime (recorded 2026-09-05): `vastai search offers 'gpu_name=RTX_4090 num_gpus=1' -o dph` searched the LIVE GPU marketplace with NO …”
   • [probe] “PROBE runtime (recorded 2026-09-05): a bare keyless GET to https://console.vast.ai/api/v0/bundles/ returned live marketplace offers as JSON …”
   • [claimed-docs] “vastai search offers 'gpu_name=RTX_4090 num_gpus=1 verified=true direct_port_count>=1 rentable=true' -o 'dlperf_usd-'”
   • [github] “vast.search_offers(query='gpu_name=RTX_4090 num_gpus>=4')”
   • [probe] “PROBE openapi: HTTP 200 at https://docs.vast.ai/api/openapi.json — contains "openapi" key”

   proof ↗⚑ flag

Pricing

1. platform engineerLock in reserved or committed-use discounts for sustained GPU capacity

   weight 1 · round to Vast.ai
   Lambda~partialclaimed4/10

   Lambda explicitly advertises a path to reserved/committed capacity pricing ('Contact us for reserved capacity at our lowest prices') and also offers Private Cloud for large single-tenant multi-year deployments, confirming the capability exists. However, this is sales-assisted only — there's no self-service reservation mechanism, no published discount tiers/terms, and on-demand pages emphasize 'No long-term commitments,' contrasting with the reserved offering. Missing for 10: self-service reservation/commitment workflow, published discount rates or contract terms, and independent evidence of actual reserved pricing outcomes.

   • [claimed-docs] “Contact us for reserved capacity at our lowest prices.”
   • [claimed-docs] “Private Cloud is the ideal solution for organizations requiring a single-tenant cluster with 1,000+ GPUs. Private Cloud customers have low-l…”
   • [claimed-docs] “Launch 16x to 512x NVIDIA H100 or B200 GPU clusters instantly, or start with a single-node instance. No long-term commitments.”

   proof ↗⚑ flag

   Vast.ai✓fullclaimed7/10

   Vast.ai documents Reserved Instances that let users pre-pay for GPU time to lock in up to 50% discounts, convertible from any on-demand instance at any time, directly matching the committed-use discount story. Missing for 10: no independent/community corroboration of reserved-instance pricing behavior, no detail on commitment duration/terms flexibility, and no evidence of longer-term (e.g. multi-month/annual) contractual reserved capacity beyond simple pre-payment conversion.

   • [claimed-docs] “Reserved instances allow you to get significant discounts (up to 50%) by pre-paying for GPU time. You can convert any on-demand instance to …”
   • [claimed-docs] “You can convert any on-demand instance to a reserved instance at any time.”
   • [claimed-docs] “You can convert an on-demand instance into a reserved instance with a lower hourly rate by pre-paying.”
   • [claimed-docs] “Reserved instances allow you to get significant discounts (up to 50%) by pre-paying for GPU time.”

   proof ↗⚑ flag

2. ml engineerSee the published per-GPU-hour price for every GPU type on a public pricing page without talking to sales

   weight 3 · round to Lambda
   Lambda✓fullcommunity8/10

   Lambda publishes a public pricing page (lambda.ai/pricing) with clear per-GPU-hour pricing and explicitly states 'Clear, straightforward pricing for Instances, 1-Click Clusters, and Superclusters' without requiring sales contact for on-demand instances; community evidence corroborates historical public per-GPU pricing announcements (e.g., $1.99/GPU/Hour H100). Missing for 10: independent third-party confirmation that ALL current GPU types' per-hour rates are listed publicly (reserved/private cloud capacity explicitly requires contacting sales per docs-35), and no direct evidence snippet showing the actual price table contents.

   • [claimed-docs] “Clear, straightforward pricing for Instances, 1-Click Clusters™, and Superclusters.”
   • [claimed-docs] “Production-ready clusters from 16 to 2,000+ NVIDIA B200 or H100 GPUs.”
   • [claimed-docs] “Contact us for reserved capacity at our lowest prices.”
   • [community] “Lambda Labs dropped H100 on-demand GPU pricing to $1.99/GPU/Hour (announced via Twitter, June 2023).”

   proof ↗⚑ flag

   Vast.ai~partialprobed7/10

   The marketplace search page and public REST/CLI endpoints let anyone see live per-GPU-hour prices without an account or contacting sales (vast-ai-docs-41, vast-ai-probe-rt-2, vast-ai-probe-rt-3), which covers the core of the story. However, there's no dedicated static 'pricing page' listing every GPU type's rate at a glance—pricing is discovered via a dynamic search/filter interface, and a community user explicitly complained about the number of clicks needed to find even an approximate price (vast-ai-comm-3). Missing for 10: a single canonical pricing table/page enumerating all GPU types' rates, and stronger independent corroboration that pricing is easy to find without friction.

   • [claimed-docs] “The search page is the main portal for finding good machines and creating instances on them.”
   • [probe] “PROBE runtime (recorded 2026-09-05): `vastai search offers 'gpu_name=RTX_4090 num_gpus=1' -o dph` searched the LIVE GPU marketplace with NO …”
   • [probe] “PROBE runtime (recorded 2026-09-05): a bare keyless GET to https://console.vast.ai/api/v0/bundles/ returned live marketplace offers as JSON …”
   • [community] “As a potential user, I'm disliking how many clicks it takes to find even an approximate price. Prices should be easiest to find.”
   • [claimed-docs] “Vast typically delivers more competitive pricing than traditional cloud providers. The marketplace model creates natural price competition”

   proof ↗⚑ flag

Spot

1. ml engineerRent spot or interruptible GPU capacity at a deep discount with clearly documented preemption semantics

   weight 3 · round to Vast.ai
   Lambda—none0/10

   Lambda's docs describe only on-demand, reserved, and private-cloud pricing tiers; there is no mention of spot/interruptible/preemptible instances or any preemption semantics. The billing evidence even highlights that Lambda bills continuously for any running instance regardless of use, reinforcing the absence of a spot/interruptible model.

   • [claimed-docs] “ODC prices instances by hourly usage and bills in one-minute increments.”
   • [claimed-docs] “Contact us for reserved capacity at our lowest prices.”
   • [claimed-docs] “Clear, straightforward pricing for Instances, 1-Click Clusters™, and Superclusters.”
   • [community] “User left a Lambda Labs GH200 instance running after brief testing and was billed $583 for 391 hours. Lambda's support said: 'Lambda does no…”

   proof ↗⚑ flag

   Vast.ai~partialcommunity6/10

   Vast.ai clearly documents an interruptible/bidding instance type offering 50%+ discounts vs on-demand (vast-ai-docs-7/17/22/35/44), which satisfies the 'deep discount' part of the story. However, the evidence pack gives only the pricing angle and doesn't detail concrete preemption mechanics (notice period, how bidding/eviction actually triggers, restart behavior) — missing for 10: explicit preemption trigger/notice documentation, and independent confirmation that discount/preemption behavior matches docs (community notes reliability variance, e.g. vast-ai-comm-6, but this isn't a concrete dispute of interruptible semantics specifically).

   • [claimed-docs] “Interruptible instances use a bidding system: **Lowest cost** (often 50%+ cheaper than on-demand)”
   • [claimed-docs] “Lowest cost (often 50%+ cheaper than on-demand)”
   • [claimed-docs] “Interruptible instances use a bidding system: Lowest cost (often 50%+ cheaper than on-demand)”
   • [claimed-docs] “Interruptible instances use a bidding system... Lowest cost (often 50%+ cheaper than on-demand)”
   • [claimed-docs] “Vast.ai offers three instance types with different priority levels and pricing models to match your workload requirements and budget.”
   • [community] “As a client (renting GPUs) I've found it to be pretty unreliable. I've tried renting GPUs a handful of times and hosts, bandwidth, and perfo…”

   proof ↗⚑ flag

1. ai-native userChoose where my data is stored (region/residency)

   weight 2 · round drawn
   Lambda—none0/10

   Lambda's docs mention that filesystems are a 'regional' store (implying infrastructure regions exist) but provide no evidence of user-facing controls to select a specific region or data-residency zone for compliance/privacy purposes. Missing for 10: explicit region-selection UI/API, documented list of available regions, and any data-residency/compliance guarantees.

   • [claimed-docs] “A filesystem is a high-capacity regional file store you can attach to your instance to store datasets and back up system state.”
   • [claimed-docs] “A _filesystem_ is a high-capacity regional file store you can attach to your instance to store datasets and back up system state.”

   proof ↗⚑ flag

   Vast.ai—none0/10

   The evidence pack shows Vast.ai lets users search/filter GPU offers by attributes like GPU model and reliability, and it distinguishes 'Secure Cloud' verified datacenters, but nowhere documents an explicit region/country selection or data-residency guarantee for where data is stored. A community report even flags a case where a host's advertised location (US) was misrepresented (actually China), undermining confidence that location can be reliably chosen or verified.

   • [claimed-docs] “Secure Cloud (Datacenter): These machines are verified and confirmed to be in a certified datacenter that meets our datacenter criteria.”
   • [claimed-docs] “Vast verifies that these machines are in a datacenter with a TIER 2/3 rating or ISO 27001. These offer cards have a blue label and are recom…”
   • [community] “Discussion flagged a Chinese host on vast.ai masquerading as a US host, raising concerns about where rented GPU compute is actually located.”

   proof ↗⚑ flag

2. ai-native userControl data retention and deletion

   weight 2 · round to Vast.ai
   Lambda—none0/10

   Lambda is a GPU cloud infrastructure provider (compute instances, clusters, filesystems, API); there is no evidence of any data retention/deletion controls, data lifecycle policies, or privacy dashboard for AI-native users to manage what data is stored or deleted. The evidence covers filesystems for storage and billing/usage tracking but nothing about retention limits or deletion mechanisms. missing for 10: documented data retention policy, deletion/opt-out controls, data lifecycle settings, any privacy-posture documentation.

   • [claimed-docs] “A filesystem is a high-capacity regional file store you can attach to your instance to store datasets and back up system state.”
   • [claimed-docs] “A _filesystem_ is a high-capacity regional file store you can attach to your instance to store datasets and back up system state.”
   • [claimed-docs] “To view your monthly usage, navigate to the [Usage page]...and then click the **Instances** tab.”

   proof ↗⚑ flag

   Vast.ai~partialprobed3/10

   Evidence shows users can destroy instances and volumes (which otherwise persist across instance destruction) via CLI/API, giving basic control over deletion of compute resources and data, but there is no explicit documentation of data retention policies, data-deletion guarantees, or privacy controls beyond simply terminating instances/volumes. missing for 10: explicit data retention/deletion policy docs, guarantees on backend data purge after deletion, account-level data deletion controls, independent verification of deletion behavior.

   • [claimed-docs] “Volumes provide persistent storage that survives instance destruction and can be reattached to new instances.”
   • [claimed-docs] “search for a GPU, rent it, wait for it to boot, connect to it, copy data, and clean up”
   • [probe] “PROBE runtime (recorded 2026-09-05): the official Vast.ai CLI (pypi `vastai`) installed via uvx and ran keylessly — `vastai --help` prints t…”

   proof ↗⚑ flag

Agent ops

1. ai agentProvision a GPU, monitor it, run a workload, and tear it down end to end through documented APIs, CLI, or MCP without a human in the console

   weight 3 · round to Vast.ai
   Lambda~partialprobed6/10

   Lambda documents a full REST API for provisioning, launching, and managing on-demand instances/clusters (with cloud-init for workload setup and a live, key-gated OpenAPI endpoint confirmed by probe), plus usage/monitoring pages and GPU dashboards — enabling non-human, API-driven lifecycle management. However, there is no official CLI and no first-party MCP server; the only MCP integration found is a third-party/unofficial community-built CLI+MCP wrapper, and monitoring is oriented toward billing/usage dashboards rather than a documented job-status API for agents. missing for 10: official CLI, first-party MCP server, and a documented workload-monitoring/job-status API distinct from usage billing.

   • [claimed-docs] “You can also launch instances programmatically by using the Lambda Cloud API.”
   • [claimed-docs] “You can also launch instances programmatically by using the Lambda Cloud API. For details, see Launch instances”
   • [claimed-docs] “The Lambda Cloud API provides a set of REST API endpoints you can use to create and manage your Lambda Cloud resources.”
   • [claimed-docs] “The Lambda Cloud API provides a set of REST API endpoints you can use to create\nand manage your Lambda Cloud resources.”
   • [probe] “PROBE runtime (recorded 2026-09-05): https://cloud.lambda.ai/api/v1/openapi.json serves the full Lambda Cloud API OpenAPI 3.1 spec (title 'L…”
   • [claimed-docs] “you can add launch-time configuration instructions using [cloud-init]”
   • [claimed-docs] “To view your monthly usage, navigate to the [Usage page]...and then click the **Instances** tab.”
   • [community] “A developer built an unofficial CLI and MCP server for Lambda cloud GPU instances, enabling AI agents to find, launch, and terminate Lambda …”

   proof ↗⚑ flag

   Vast.ai✓fullprobed8/10

   Vast.ai documents a full REST API, CLI, and Python SDK covering the entire instance lifecycle (search offers, create/rent, connect, destroy), confirmed by runtime probes showing the CLI and API working keylessly for search and an OpenAPI spec being live. It also ships a dedicated 'vastai agent skill' explicitly for AI coding assistants to create instances, deploy endpoints, and manage keys without human console interaction, plus scoped API keys for automation/CI. Missing for 10: no independent hands-on evidence of a full agent-driven create→monitor→run→teardown cycle end-to-end (only search was probed live), and no first-party MCP server confirmed beyond the 'agent skill' framing.

   • [claimed-docs] “The Vast.ai CLI gives you command-line access to the entire platform, authentication, GPU search, instance lifecycle, templates, volumes, se…”
   • [claimed-docs] “The Vast.ai REST API gives you programmatic control over the entire platform. It's the foundation that the CLI and SDK are built on.”
   • [claimed-docs] “The `vastai` agent skill lets AI coding assistants drive Vast.ai on your behalf — create instances, deploy endpoints, manage SSH keys, check…”
   • [claimed-docs] “The vastai agent skill lets AI coding assistants drive Vast.ai on your behalf — create instances, deploy endpoints, manage SSH keys, check b…”
   • [claimed-docs] “For shared tooling, CI/CD, or automation, create a scoped key with only the permissions that workload needs.”
   • [claimed-docs] “search for a GPU, rent it, wait for it to boot, connect to it, copy data, and clean up”
   • [probe] “PROBE openapi: HTTP 200 at https://docs.vast.ai/api/openapi.json — contains "openapi" key”
   • [probe] “PROBE runtime (recorded 2026-09-05): the official Vast.ai CLI (pypi `vastai`) installed via uvx and ran keylessly — `vastai --help` prints t…”
   • [probe] “PROBE runtime (recorded 2026-09-05): `vastai search offers 'gpu_name=RTX_4090 num_gpus=1' -o dph` searched the LIVE GPU marketplace with NO …”
   • [probe] “PROBE runtime (recorded 2026-09-05): a bare keyless GET to https://console.vast.ai/api/v0/bundles/ returned live marketplace offers as JSON …”

   proof ↗⚑ flag

Manage

1. ml engineerSet auto-shutdown timers or spend limits so a forgotten instance can't silently run up a huge bill

   weight 2 · round drawn
   Lambda—none0/10

   No documentation or feature evidence shows auto-shutdown timers, idle detection, or spend-limit controls; on the contrary, community evidence explicitly states Lambda 'does not distinguish between idle and in use instance states' and a user was billed $583 for 391 hours of an idle GH200 instance, confirming the absence of this safeguard.

   • [community] “User left a Lambda Labs GH200 instance running after brief testing and was billed $583 for 391 hours. Lambda's support said: 'Lambda does no…”

   proof ↗⚑ flag

   Vast.ai—none0/10

   The evidence pack documents autobilling (auto top-up to keep instances running), reserved/interruptible instance pricing, and scoped API keys, but none of these are auto-shutdown timers or spend caps — autobilling in fact works against this story by automatically refilling balance to prevent instance interruption rather than capping spend. No mention of idle-timeout, max-runtime, or budget-limit features exists anywhere in the pack.

   • [claimed-docs] “Use the autobilling feature to have the system automatically top up your account using a saved credit card when it runs low.”
   • [claimed-docs] “Autobilling keeps your balance positive to protect your instances from interruption or deletion.”
   • [claimed-docs] “Reserved instances allow you to get significant discounts (up to 50%) by pre-paying for GPU time. You can convert any on-demand instance to …”
   • [claimed-docs] “create a scoped key with only the permissions that workload needs”

   proof ↗⚑ flag

2. developerStart, stop, restart, and terminate instances programmatically and keep paying only for what is running

   weight 2 · round to Vast.ai
   Lambda!disputedcontradicted6/10

   Lambda's API and docs support programmatic launch/terminate of instances with per-minute billing (lambda-labs-docs-5, -10, -23, -31, -39, runtime probe confirms live REST API), but there's no documented stop/start (pause) capability distinct from terminate, and a hands-on community report shows billing continues for idle-but-running instances regardless of usage, contradicting 'pay only for what is running' in the sense of active workload — user was billed $583 for an idle instance because Lambda 'does not distinguish between idle and in use instance states' (lambda-labs-comm-1). missing for 10: documented stop/pause (vs. terminate) lifecycle action, confirmation that idle time is excluded from billing, independent corroboration beyond one HN anecdote.

   • [claimed-docs] “You can also launch instances programmatically by using the Lambda Cloud API.”
   • [claimed-docs] “ODC prices instances by hourly usage and bills in one-minute increments.”
   • [claimed-docs] “You can also launch instances programmatically by using the Lambda Cloud API. For details, see Launch instances”
   • [claimed-docs] “The Lambda Cloud API provides a set of REST API endpoints you can use to create and manage your Lambda Cloud resources.”
   • [probe] “PROBE runtime (recorded 2026-09-05): https://cloud.lambda.ai/api/v1/openapi.json serves the full Lambda Cloud API OpenAPI 3.1 spec (title 'L…”
   • [community] “User left a Lambda Labs GH200 instance running after brief testing and was billed $583 for 391 hours. Lambda's support said: 'Lambda does no…”

   proof ↗⚑ flag

   Vast.ai✓fullprobed8/10

   Vast.ai's CLI and REST API provide documented commands/endpoints for the full instance lifecycle (search, create, destroy) confirmed by runtime probes, plus billing docs (autobilling, per-hour pricing, reserved/interruptible discounts) demonstrate pay-only-for-what-runs. Community feedback corroborates cost savings but also notes reliability variance, which is a secondary concern rather than a lifecycle-control failure. Missing for 10: explicit documented 'stop'/'restart' CLI subcommands beyond create/destroy in the evidence, and independent hands-on confirmation of stop/restart specifically (only create/destroy verified at runtime).

   • [claimed-docs] “The Vast.ai CLI gives you command-line access to the entire platform, authentication, GPU search, instance lifecycle, templates, volumes, se…”
   • [claimed-docs] “The Vast.ai REST API gives you programmatic control over the entire platform. It's the foundation that the CLI and SDK are built on.”
   • [probe] “PROBE runtime (recorded 2026-09-05): the official Vast.ai CLI (pypi `vastai`) installed via uvx and ran keylessly — `vastai --help` prints t…”
   • [probe] “PROBE runtime (recorded 2026-09-05): `vastai search offers 'gpu_name=RTX_4090 num_gpus=1' -o dph` searched the LIVE GPU marketplace with NO …”
   • [probe] “PROBE runtime (recorded 2026-09-05): a bare keyless GET to https://console.vast.ai/api/v0/bundles/ returned live marketplace offers as JSON …”
   • [claimed-docs] “Use the autobilling feature to have the system automatically top up your account using a saved credit card when it runs low.”
   • [claimed-docs] “Autobilling keeps your balance positive to protect your instances from interruption or deletion.”
   • [claimed-docs] “Reserved instances allow you to get significant discounts (up to 50%) by pre-paying for GPU time. You can convert any on-demand instance to …”
   • [claimed-docs] “Interruptible instances use a bidding system: **Lowest cost** (often 50%+ cheaper than on-demand)”
   • [community] “Absolutely incredible how cheap the compute power is on this platform. Vast has saved me tens of thousands of dollars running ML experiments…”

   proof ↗⚑ flag

Provision

1. developerProvision an on-demand GPU instance from the console or API and be running code on it within minutes

   weight 3 · round to Lambda
   Lambda✓fullprobed8/10

   Lambda's docs and live API confirm on-demand GPU provisioning via console or REST API, with cloud-init, SSH, and JupyterLab access enabling immediate code execution, and pricing pages claim deployment 'in minutes.' A community-built CLI/MCP tool also independently confirms real users launching and SSHing into instances quickly. Missing for 10: independent benchmark/timing evidence validating the 'minutes' claim and first-hand confirmation of no friction in provisioning flow.

   • [claimed-docs] “Launch 16x to 512x NVIDIA H100 or B200 GPU clusters instantly, or start with a single-node instance. No long-term commitments.”
   • [claimed-docs] “You can also launch instances programmatically by using the Lambda Cloud API.”
   • [claimed-docs] “you can add launch-time configuration instructions using [cloud-init]”
   • [claimed-docs] “You can connect to your On-Demand Cloud (ODC) instances directly through SSH or by using the preinstalled JupyterLab server.”
   • [claimed-docs] “On-Demand Cloud (ODC) provides on-demand access to Linux-based, GPU-backed virtual machine instances.”
   • [claimed-docs] “Deploy NVIDIA B200, H100, A100, or GH200 instances in minutes with self-serve, first-come access.”
   • [probe] “PROBE runtime (recorded 2026-09-05): https://cloud.lambda.ai/api/v1/openapi.json serves the full Lambda Cloud API OpenAPI 3.1 spec (title 'L…”
   • [community] “A developer built an unofficial CLI and MCP server for Lambda cloud GPU instances, enabling AI agents to find, launch, and terminate Lambda …”

   proof ↗⚑ flag

   Vast.ai✓fullprobed7/10

   Docs and runtime probes show the full quickstart flow — search offers via CLI/API keylessly, one-click templates, instance creation, SSH access with password auth disabled, and REST/CLI parity for automation — matching the 'search, rent, boot, connect' workflow described in vast-ai-docs-34. Community reviews largely corroborate ease and cost savings, though some flag friction/hoops versus AWS/GCP and inconsistent reliability, which tempers but doesn't contradict the core provisioning claim. Missing for 10: an independent hands-on timing test confirming actual boot-to-running-code within minutes, and resolution of community complaints about setup friction/reliability variance.

   • [claimed-docs] “This Quickstart will guide you through setting up your Vast.ai account and running your first instance in just a few steps.”
   • [claimed-docs] “search for a GPU, rent it, wait for it to boot, connect to it, copy data, and clean up”
   • [claimed-docs] “The search page is the main portal for finding good machines and creating instances on them.”
   • [claimed-docs] “Launch prebuilt or custom templates with one click.”
   • [claimed-docs] “The Vast.ai CLI gives you command-line access to the entire platform, authentication, GPU search, instance lifecycle, templates, volumes, se…”
   • [claimed-docs] “The Vast.ai REST API gives you programmatic control over the entire platform. It's the foundation that the CLI and SDK are built on.”
   • [claimed-docs] “SSH (Secure Shell) is a protocol for safely connecting to remote servers. It encrypts your connection so you can: Log in securely, Run comma…”
   • [probe] “PROBE runtime (recorded 2026-09-05): the official Vast.ai CLI (pypi `vastai`) installed via uvx and ran keylessly — `vastai --help` prints t…”
   • [probe] “PROBE runtime (recorded 2026-09-05): `vastai search offers 'gpu_name=RTX_4090 num_gpus=1' -o dph` searched the LIVE GPU marketplace with NO …”
   • [probe] “PROBE runtime (recorded 2026-09-05): a bare keyless GET to https://console.vast.ai/api/v0/bundles/ returned live marketplace offers as JSON …”
   • [community] “Absolutely incredible how cheap the compute power is on this platform. Vast has saved me tens of thousands of dollars running ML experiments…”
   • [community] “While they've done a pretty good job considering with their software stack it's still kind of a pain to use with significant limitations and…”

   proof ↗⚑ flag

Serverless

1. developerDeploy code to autoscaling serverless GPU workers that scale to zero, instead of managing always-on instances

   weight 2 · round to Vast.ai
   Lambda—none0/10

   Lambda's documented products are on-demand VMs, 1-Click Clusters, Managed Kubernetes, and Managed Slurm — all provisioned/billed as running instances, not autoscaling serverless GPU functions. Community evidence explicitly confirms Lambda 'does not distinguish between idle and in use instance states' and bills continuously even when idle, the opposite of scale-to-zero behavior. No docs mention a serverless endpoint product or autoscale-to-zero deployment model.

   • [claimed-docs] “On-Demand Cloud (ODC) provides on-demand access to Linux-based, GPU-backed virtual machine instances.”
   • [claimed-docs] “ODC prices instances by hourly usage and bills in one-minute increments.”
   • [community] “User left a Lambda Labs GH200 instance running after brief testing and was billed $583 for 391 hours. Lambda's support said: 'Lambda does no…”

   proof ↗⚑ flag

   Vast.ai~partialclaimed6/10

   Vast.ai explicitly ships 'Vast Serverless', described as letting users run compute-intensive workloads 'without managing GPUs, paying for execution rather than GPU rental time,' with a Python SDK and CLI support for deploying endpoints — matching the pay-per-execution serverless model a developer would want instead of always-on instances. However, the evidence never explicitly confirms autoscaling behavior or scale-to-zero semantics, nor gives hands-on/independent corroboration of how workers scale under load. Missing for 10: explicit autoscaling/scale-to-zero documentation, independent or hands-on validation of serverless endpoint behavior, and details on cold-start/latency tradeoffs.

   • [claimed-docs] “Vast Serverless is an AI infrastructure platform that lets you run compute-intensive workloads without managing GPUs, paying for execution r…”
   • [claimed-docs] “Interacting with Vast Serverless is made easy through a powerful python SDK.”
   • [claimed-docs] “The vastai agent skill lets AI coding assistants drive Vast.ai on your behalf — create instances, deploy endpoints, manage SSH keys, check b…”
   • [claimed-docs] “The `vastai` agent skill lets AI coding assistants drive Vast.ai on your behalf — create instances, deploy endpoints, manage SSH keys, check…”

   proof ↗⚑ flag

Data movement

1. developerMove data in and out efficiently — S3-compatible endpoints, cloud-storage sync, or documented transfer tooling

   weight 2 · round to Lambda
   Lambda✓fullprobed8/10

   Lambda documents an S3-compatible adapter for its filesystems, explicitly supporting rclone and s5cmd for copying data in/out, plus a REST Cloud API and cloud-init for programmatic/automated data and instance management. Missing for 10: no independent hands-on verification of transfer performance/reliability and no native cloud-storage sync service beyond the S3-compatible adapter.

   • [claimed-docs] “This adapter allows you to use S3-compatible tools like rclone and s5cmd to copy files to and from your filesystems and perform common file …”
   • [claimed-docs] “This adapter allows you to use S3-compatible tools like `rclone` and `s5cmd` to copy files to and from your filesystems”
   • [claimed-docs] “A filesystem is a high-capacity regional file store you can attach to your instance to store datasets and back up system state.”
   • [claimed-docs] “The Lambda Cloud API provides a set of REST API endpoints you can use to create and manage your Lambda Cloud resources.”
   • [probe] “PROBE runtime (recorded 2026-09-05): https://cloud.lambda.ai/api/v1/openapi.json serves the full Lambda Cloud API OpenAPI 3.1 spec (title 'L…”

   proof ↗⚑ flag

   Vast.ai~partialcommunity5/10

   Vast.ai documents SSH-based secure file transfer to/from instances and a CLI workflow that includes 'copy data' as a step, plus persistent Volumes for data that survives instance destruction. However there is no evidence of S3-compatible endpoints or native cloud-storage (S3/GCS/Azure Blob) sync tooling, and a community comment notes persistent-disk workflows are still cumbersome over time. Missing for 10: S3-compatible storage endpoint, built-in cloud-storage sync/mirroring tooling, independent hands-on validation of transfer throughput/performance.

   • [claimed-docs] “Log in securely, Run commands remotely, Transfer files without exposing your data”
   • [claimed-docs] “SSH (Secure Shell) is a protocol for safely connecting to remote servers. It encrypts your connection so you can: Log in securely, Run comma…”
   • [claimed-docs] “search for a GPU, rent it, wait for it to boot, connect to it, copy data, and clean up”
   • [claimed-docs] “Volumes provide persistent storage that survives instance destruction and can be reattached to new instances.”
   • [community] “Love vast.ai. Only wish is for it to be easier to work with persistent disks over time. I only use it for one off expensive jobs now.”

   proof ↗⚑ flag

Storage

1. developerAttach persistent network storage that survives instance teardown, so datasets and checkpoints outlive any single GPU rental

   weight 3 · round to Lambda
   Lambda✓fullclaimed8/10

   Lambda's docs explicitly describe attachable persistent filesystems ('high-capacity regional file store you can attach to your instance to store datasets and back up system state') that exist independently of any instance, plus S3-compatible tooling (rclone/s5cmd) for moving data in/out, directly matching the story of datasets/checkpoints surviving GPU teardown. missing for 10: no independent/hands-on confirmation of persistence across teardown or details on durability guarantees/pricing for the filesystem.

   • [claimed-docs] “A filesystem is a high-capacity regional file store you can attach to your instance to store datasets and back up system state.”
   • [claimed-docs] “A _filesystem_ is a high-capacity regional file store you can attach to your instance to store datasets and back up system state.”
   • [claimed-docs] “This adapter allows you to use S3-compatible tools like rclone and s5cmd to copy files to and from your filesystems and perform common file …”
   • [claimed-docs] “This adapter allows you to use S3-compatible tools like `rclone` and `s5cmd` to copy files to and from your filesystems”

   proof ↗⚑ flag

   Vast.ai~partialcommunity6/10

   Vast.ai docs explicitly describe 'Volumes' as persistent storage that survives instance destruction and can be reattached to new instances, directly matching the story. However, a community user notes wishing it were 'easier to work with persistent disks over time' and now avoids it for anything but one-off jobs, indicating real friction in practice. Missing for 10: independent hands-on verification of volume reattachment reliability, docs detailing size/performance limits, and broader community corroboration beyond a single anecdotal complaint.

   • [claimed-docs] “Volumes provide persistent storage that survives instance destruction and can be reattached to new instances.”
   • [community] “Love vast.ai. Only wish is for it to be easier to work with persistent disks over time. I only use it for one off expensive jobs now.”

   proof ↗⚑ flag

Images

1. developerRun my own Docker image or custom machine template with my exact environment

   weight 2 · round to Vast.ai
   Lambda~partialclaimed6/10

   Lambda's docs show real support for custom environments: the Cloud API lets you launch instances with 'a different base image' (custom machine template) and cloud-init for launch-time configuration, plus GPU Base images for full control over the Python environment. Containerized workloads (i.e., running an actual Docker image) are supported via Managed Kubernetes (MK8s) rather than as a first-class ODC instance feature. Missing for 10: explicit first-party documentation of directly launching a Docker image as an ODC instance (vs. VM base image), a custom-image/AMI gallery, and independent hands-on confirmation that custom base images work as claimed.

   • [claimed-docs] “the API allows you to use a different base image for your instance”
   • [claimed-docs] “you can add launch-time configuration instructions using [cloud-init]”
   • [claimed-docs] “If you're launching your instance with the Lambda Cloud API, you can add launch-time configuration instructions using cloud-init”
   • [claimed-docs] “GPU Base: An image based on Ubuntu Server that includes a minimal set of key AI/ML tools and drivers... Use if: You want a minimal working s…”
   • [claimed-docs] “MK8s provides a Kubernetes environment with GPU and InfiniBand (RDMA) support, and shared persistent storage across all nodes in a 1CC.”
   • [claimed-docs] “MK8s provides a Kubernetes environment with GPU and InfiniBand (RDMA) support, and shared persistent storage across all nodes in a 1CC. Clus…”

   proof ↗⚑ flag

   Vast.ai✓fullclaimed8/10

   Vast.ai's template system explicitly lets developers package their own Docker environment ('Package your environment so any GPU can run it with one click') and launch prebuilt or custom templates with one click, backed by CLI/API/SDK automation for creating and managing instances from these templates. Documentation confirms templates configure the rented machine with whatever software/formatting is needed, directly matching the story. missing for 10: no independent/hands-on confirmation of building and running a fully custom Docker image end-to-end (community evidence focuses on pricing/reliability, not template customization).

   • [claimed-docs] “Build a template - Package your environment so any GPU can run it with one click.”
   • [claimed-docs] “A template is how Vast helps you launch an instance, setting up your rented machine with whatever software and formatting you need.”
   • [claimed-docs] “Launch prebuilt or custom templates with one click.”
   • [claimed-docs] “PyTorch, vLLM, ComfyUI, agents, and more. Real deployments you can copy.”
   • [claimed-docs] “Automate with the CLI or SDK ... `vastai` from the shell or Python. Same operations, different syntax.”

   proof ↗⚑ flag

Templates

1. developerLaunch from pre-built ML templates (PyTorch, CUDA, vLLM, ComfyUI) instead of assembling an environment from scratch

   weight 2 · round to Vast.ai
   Lambda~partialclaimed5/10

   Lambda's ODC instances preinstall 'Lambda Stack' (AI/ML drivers, tools, frameworks) and offer a 'GPU Base' minimal image, which covers PyTorch/CUDA-style ready environments, plus JupyterLab for quick start. However, there's no evidence of named pre-built templates for vLLM or ComfyUI specifically, only generic 'AI/ML tools and frameworks'. missing for 10: explicit vLLM template/image, explicit ComfyUI template/image, a documented template gallery/catalog beyond Lambda Stack and GPU Base.

   • [claimed-docs] “Lambda also preinstalls Lambda Stack, a standard set of AI/ML-related drivers, tools, and frameworks, on the instance”
   • [claimed-docs] “GPU Base: An image based on Ubuntu Server that includes a minimal set of key AI/ML tools and drivers.”
   • [claimed-docs] “GPU Base: An image based on Ubuntu Server that includes a minimal set of key AI/ML tools and drivers... Use if: You want a minimal working s…”
   • [claimed-docs] “each ODC instance provides a JupyterLab installation for creating and managing Jupyter notebooks”

   proof ↗⚑ flag

   Vast.ai✓fullclaimed8/10

   Vast.ai's docs explicitly describe templates as a first-class launch mechanism ('Launch prebuilt or custom templates with one click', 'A template is how Vast helps you launch an instance') and directly name PyTorch, vLLM, and ComfyUI as available prebuilt templates ('PyTorch, vLLM, ComfyUI, agents, and more. Real deployments you can copy'). CUDA support is implied through GPU offer filtering and template packaging but not explicitly named as its own template. missing for 10: independent/hands-on confirmation of launching a specific named template (e.g., a community post describing a ComfyUI or vLLM template launch), and explicit CUDA-template documentation rather than inferred CUDA support.

   • [claimed-docs] “Launch prebuilt or custom templates with one click.”
   • [claimed-docs] “PyTorch, vLLM, ComfyUI, agents, and more. Real deployments you can copy.”
   • [claimed-docs] “A template is how Vast helps you launch an instance, setting up your rented machine with whatever software and formatting you need.”
   • [claimed-docs] “Build a template - Package your environment so any GPU can run it with one click.”

   proof ↗⚑ flag

Compliance

1. platform engineerVerify the provider's security and compliance posture (SOC 2, data handling, datacenter tiers) before putting proprietary models on it

   weight 2 · round to Vast.ai
   Lambda—none0/10

   No evidence in the pack addresses SOC 2 certification, compliance attestations, data handling policies, or datacenter tier ratings for Lambda's cloud offerings; the docs focus entirely on GPU provisioning, clusters, filesystems, and API usage. This is a fair, applicable question for any cloud infrastructure provider hosting proprietary models, but no supporting documentation exists in the evidence pack.

   ⚑ flag

   Vast.ai!disputedcontradicted4/10

   Vast.ai docs claim some infrastructure verification — 'Secure Cloud' machines are checked for TIER 2/3 datacenter rating or ISO 27001 certification (vast-ai-docs-14, vast-ai-docs-28) — but there is no mention of SOC 2 attestation, data-handling/privacy policies, or compliance documentation anywhere in the pack. Community evidence directly undercuts trust in these verifications: a host was found masquerading as US-based while actually located in China (vast-ai-comm-10), and another thread questions whether running consumer GPUs at scale even complies with Nvidia's own terms (vast-ai-comm-9) — concrete contradictions of the 'verified' security posture platform engineers would need to rely on. Missing for 10: SOC 2 or equivalent third-party compliance attestation, explicit data-handling/retention policy, and independent audit corroborating the datacenter tier claims.

   • [claimed-docs] “Secure Cloud (Datacenter): These machines are verified and confirmed to be in a certified datacenter that meets our datacenter criteria.”
   • [claimed-docs] “Vast verifies that these machines are in a datacenter with a TIER 2/3 rating or ISO 27001. These offer cards have a blue label and are recom…”
   • [community] “Running a fleet of RTX3090's on demand does not sound at all compliant with what little I know of NVidia's terms of use. There's surprisingl…”
   • [community] “Discussion flagged a Chinese host on vast.ai masquerading as a US host, raising concerns about where rented GPU compute is actually located.”

   proof ↗⚑ flag

Governance

1. platform engineerManage team members with roles and scoped API keys so credentials and spend stay controlled

   weight 1 · round to Vast.ai
   Lambda—none0/10

   The evidence pack documents instance provisioning, filesystems, firewalls, and a key-gated REST API, but contains no mention of team/member management, role-based access control, or scoped/restricted API keys for spend control. The billing complaint (lambda-labs-comm-1) actually highlights a lack of granular usage controls rather than confirming governance features.

   • [claimed-docs] “The Lambda Cloud API provides a set of REST API endpoints you can use to create and manage your Lambda Cloud resources.”
   • [probe] “PROBE runtime (recorded 2026-09-05): https://cloud.lambda.ai/api/v1/openapi.json serves the full Lambda Cloud API OpenAPI 3.1 spec (title 'L…”
   • [community] “User left a Lambda Labs GH200 instance running after brief testing and was billed $583 for 391 hours. Lambda's support said: 'Lambda does no…”

   proof ↗⚑ flag

   Vast.ai~partialclaimed4/10

   Vast.ai documents scoped API keys with limited permissions for CI/CD and shared tooling use cases (create api-key, per-workload scoping), which addresses the credential-control half of the story. However, there is no evidence of team/organization member management, role assignment, or multi-user account governance — the evidence pack only covers individual scoped keys, not team-based RBAC. Missing for 10: team member invitation/management, role definitions (admin/viewer/etc.), org-level spend controls tied to roles, and any audit trail for team activity.

   • [claimed-docs] “You can also create scoped keys with limited permissions using `vastai create api-key`, useful for CI/CD or shared tooling.”
   • [claimed-docs] “create a scoped key with only the permissions that workload needs”
   • [claimed-docs] “For shared tooling, CI/CD, or automation, create a scoped key with only the permissions that workload needs.”

   proof ↗⚑ flag