OpenRouter vs Requesty

Agent access

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

   weight 2 · round to OpenRouter
   OpenRouter✓fullprobed9/10

   OpenRouter serves a working llms.txt at openrouter.ai/llms.txt (HTTP 200, agent-oriented summary), plus an OpenAPI spec and MCP server that expose docs/data programmatically to agents. This directly satisfies pointing an agent at llms.txt or agent-oriented docs. Missing for 10: independent/community confirmation that agents successfully consume llms.txt in practice.

   • [probe] “PROBE llms.txt: HTTP 200 at https://openrouter.ai/llms.txt # OpenRouter > A unified API for every major LLM. One endpoint, hundreds of mode…”
   • [probe] “PROBE openapi: HTTP 200 at https://openrouter.ai/openapi.json — contains "openapi" key”
   • [probe] “official MCP server documented at https://openrouter.ai/docs/guides/overview/mcp-server.md”
   • [claimed-docs] “The OpenRouter MCP server plugs OpenRouter into the AI tools you already use. Once connected, your assistant can pull live OpenRouter data (…”

   proof ↗⚑ flag

   Requesty✓fullprobed8/10

   Requesty's docs site serves a working llms.txt (HTTP 200) with a structured index, plus .md variants of docs pages that explicitly point agents to llms.txt for the full documentation index, directly enabling an agent to be pointed at agent-oriented docs. missing for 10: no independent/third-party confirmation of agents actually consuming this successfully, and no dedicated docs page describing the llms.txt feature itself.

   • [probe] “PROBE llms.txt: HTTP 200 at https://docs.requesty.ai/llms.txt # Requesty > Requesty is a unified LLM gateway and OpenAI-compatible API for …”
   • [probe] “PROBE docs-md: HTTP 200 at https://docs.requesty.ai/quickstart.md > ## Documentation Index > Fetch the complete documentation index at: http…”

   proof ↗⚑ flag

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

   weight 2 · round to OpenRouter
   OpenRouter✓fullprobed7/10

   OpenRouter is fundamentally a headless REST API (single endpoint, OpenAI-SDK compatible, streaming, programmatic API key management) that requires no UI and can be called from any script or pipeline, making it inherently suited to CI/automation use; the keyless models endpoint and management API keys reinforce programmatic, non-interactive use. Missing for 10: no explicit CI/CD pipeline examples (e.g., GitHub Actions), no dedicated 'headless/automation' documentation section, and no independent report of someone running it in a CI pipeline.

   • [claimed-docs] “OpenRouter provides endpoints to programmatically manage your API keys, enabling key creation and management for applications that need to d…”
   • [claimed-docs] “You can also use the OpenAI SDK pointed at OpenRouter as a drop-in replacement.”
   • [claimed-docs] “You can also use the [OpenAI SDK](#using-the-openai-sdk) pointed at OpenRouter as a drop-in replacement.”
   • [claimed-docs] “The OpenRouter API allows streaming responses from any model. This is useful for building chat interfaces or other applications where the UI…”
   • [probe] “PROBE keyless-endpoint: GET https://openrouter.ai/api/v1/models returned HTTP 200 application/json with 426 models (unauthenticated) - live …”
   • [probe] “PROBE openapi: HTTP 200 at https://openrouter.ai/openapi.json — contains "openapi" key”

   proof ↗⚑ flag

   Requesty~partialclaimed6/10

   Requesty is an OpenAI-compatible API gateway accessed via simple base_url swap, meaning any script or CI pipeline using the OpenAI SDK can call it headlessly without a UI, and BYOK/API-key auth supports non-interactive use. However, there is no explicit documentation or example showing CI/automation setup (e.g., GitHub Actions, headless auth flow, or CLI for pipelines). Missing for 10: explicit CI/automation docs or examples, headless auth/token provisioning guidance, independent confirmation of CI usage.

   • [claimed-docs] “If you're already using the OpenAI SDK, point it at Requesty and you're done. No SDK changes, no new client to learn.”
   • [claimed-docs] “base_url="https://router.requesty.ai/v1", # was: https://api.openai.com/v1”
   • [claimed-docs] “Bring Your Own Keys (BYOK) allows you to use your personal API keys from various providers with Requesty.”

   proof ↗⚑ flag

3. ai-native userPlug MCP servers into this product so it can use their tools

   weight 3 · round to Requesty
   OpenRouter—none0/10

   Evidence only shows OpenRouter publishing its own MCP server so external AI tools/editors can pull OpenRouter data (docs-14, docs-26, docs-34, probe-3) — this is OpenRouter acting as an MCP server for other clients, not OpenRouter itself consuming/plugging in external MCP servers to gain their tools. There is no evidence that OpenRouter's API or platform lets a user attach third-party MCP servers so OpenRouter-routed models can call their tools; the standardized tool-calling docs (docs-5) refer to generic function-calling, not MCP integration specifically.

   • [claimed-docs] “The OpenRouter MCP server plugs OpenRouter into the AI tools you already use. Once connected, your assistant can pull live OpenRouter data (…”
   • [claimed-docs] “The **OpenRouter MCP server** plugs OpenRouter into the AI tools you already use. Once connected, your assistant can pull live OpenRouter da…”
   • [claimed-docs] “Once connected, your assistant can pull live OpenRouter data (models, prices, your credits, rankings, and docs) and send quick test messages…”
   • [probe] “official MCP server documented at https://openrouter.ai/docs/guides/overview/mcp-server.md”
   • [claimed-docs] “OpenRouter standardizes the tool calling interface across models and providers, making it easy to integrate external tools with any supporte…”

   proof ↗⚑ flag

   Requesty✓fullclaimed7/10

   Requesty's MCP Gateway explicitly lets AI coding assistants (Claude Code, Cursor, Roo Code) connect to MCP servers through Requesty's unified API, directly matching the story. missing for 10: deeper documentation on configuring specific MCP servers and independent/hands-on corroboration of the gateway working in practice.

   • [claimed-docs] “The MCP (Model Context Protocol) Gateway enables AI coding assistants like Claude Code, Cursor, and Roo Code to securely connect to MCP serv…”

   proof ↗⚑ flag

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

   weight 3 · round to OpenRouter
   OpenRouter✓fullprobed8/10

   OpenRouter publishes an official MCP server that lets AI assistants/agents connect and pull live OpenRouter data (models, prices, credits, rankings, docs) directly from within the editor, confirmed both in docs and via a live probe of the documentation page. Missing for 10: independent/hands-on community validation of the MCP server's real-world reliability beyond first-party docs.

   • [claimed-docs] “The OpenRouter MCP server plugs OpenRouter into the AI tools you already use. Once connected, your assistant can pull live OpenRouter data (…”
   • [claimed-docs] “The **OpenRouter MCP server** plugs OpenRouter into the AI tools you already use. Once connected, your assistant can pull live OpenRouter da…”
   • [claimed-docs] “Once connected, your assistant can pull live OpenRouter data (models, prices, your credits, rankings, and docs) and send quick test messages…”
   • [probe] “official MCP server documented at https://openrouter.ai/docs/guides/overview/mcp-server.md”

   proof ↗⚑ flag

   Requesty✓fullclaimed7/10

   Requesty is a gateway/router (not itself an agent), and it documents an official 'MCP Gateway' that lets AI coding assistants like Claude Code, Cursor, and Roo Code securely connect to MCP servers through Requesty's unified API, directly matching the story. Missing for 10: independent/hands-on corroboration beyond first-party docs and more detail on setup/config specifics.

   • [claimed-docs] “The MCP (Model Context Protocol) Gateway enables AI coding assistants like Claude Code, Cursor, and Roo Code to securely connect to MCP serv…”
   • [claimed-docs] “Using the Requesty integration, you can: Use 300+ models while coding, giving you flexibility to choose the best model for each task.”

   proof ↗⚑ flag

5. ai-native userUse an official CLI

   weight 2 · round drawn
   OpenRouter—none0/10

   OpenRouter is an API/model-routing platform for which an official CLI would be a plausible ecosystem tool, but the evidence pack contains no mention of any official OpenRouter CLI — only SDK compatibility, REST API, MCP server, and web UI are documented.

   ⚑ flag

   Requesty—none0/10

   Requesty is presented as a unified LLM gateway/router with SDK compatibility and integrations (Claude Code, Cursor, etc.), but no evidence mentions an official Requesty CLI tool. Evidence only covers API routing, policies, MCP gateway, and dashboard features—no CLI is documented or probed.

   ⚑ flag

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

   weight 3 · round to OpenRouter
   OpenRouter✓fullprobed10/10

   OpenRouter is fundamentally an API product: extensive first-party docs cover the unified chat completions endpoint, streaming, tool calling, model routing/fallbacks, key management, and an OpenAPI spec plus a live, keyless /api/v1/models endpoint confirm a documented, programmatically accessible public API. Community evidence corroborates real-world programmatic use (switching models, key minting, billing caps) reinforcing that it is driven via API in production.

   • [claimed-docs] “OpenRouter gives you access to hundreds of AI models through a single API endpoint.”
   • [claimed-docs] “The OpenRouter API allows streaming responses from any model. This is useful for building chat interfaces or other applications where the UI…”
   • [claimed-docs] “OpenRouter standardizes the tool calling interface across models and providers, making it easy to integrate external tools with any supporte…”
   • [claimed-docs] “Browse the full catalog at openrouter.ai/models, or list every available slug programmatically via the GET /api/v1/models endpoint.”
   • [probe] “PROBE llms.txt: HTTP 200 at https://openrouter.ai/llms.txt # OpenRouter > A unified API for every major LLM. One endpoint, hundreds of mode…”
   • [probe] “PROBE openapi: HTTP 200 at https://openrouter.ai/openapi.json — contains "openapi" key”
   • [probe] “PROBE keyless-endpoint: GET https://openrouter.ai/api/v1/models returned HTTP 200 application/json with 426 models (unauthenticated) - live …”
   • [community] “Happy for the OpenRouter team... the ability to run any AI model with the same api key and same request has been great to experiment with ne…”
   • [community] “One thing that OpenRouter makes easy is the ability to manage API keys (mint new ones, expiry/limits per key, etc.) that I wish other provid…”

   proof ↗⚑ flag

   Requesty✓fullprobed8/10

   Requesty exposes a documented, OpenAI-compatible public API (base_url swap, quickstart docs) plus a rich set of documented API-level features (fallback policies, load balancing, caching, structured outputs, BYOK) that let an AI-native user drive the product programmatically. missing for 10: an actual OpenAPI/swagger spec (probe found all candidate spec paths 404) and independent third-party corroboration of API robustness.

   • [claimed-docs] “If you're already using the OpenAI SDK, point it at Requesty and you're done. No SDK changes, no new client to learn.”
   • [claimed-docs] “base_url="https://router.requesty.ai/v1", # was: https://api.openai.com/v1”
   • [claimed-docs] “Fallback Policies automatically retry your requests with different models if one fails, ensuring your application stays reliable even when i…”
   • [claimed-docs] “Load Balancing Policies distribute your requests across multiple models based on weights you define. Perfect for A/B testing, gradual rollou…”
   • [claimed-docs] “Requesty makes every supported model speak structured JSON — from simple json_object mode to strict, schema-enforced json_schema mode.”
   • [probe] “PROBE llms.txt: HTTP 200 at https://docs.requesty.ai/llms.txt # Requesty > Requesty is a unified LLM gateway and OpenAI-compatible API for …”
   • [probe] “PROBE openapi: all candidate paths 404 (https://docs.requesty.ai/openapi.json, https://docs.requesty.ai/swagger.json, https://docs.requesty.…”

   proof ↗⚑ flag

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

   weight 2 · round to OpenRouter
   OpenRouter~partialcommunity7/10

   OpenRouter offers a documented Management API for creating/rotating API keys, workspace spend budgets, and per-key limits/expiry, which supports issuing distinct, capped credentials for agents (openrouter-docs-8, openrouter-docs-10, openrouter-comm-12, openrouter-comm-11). However, there's no explicit documentation of fine-grained scoping (e.g., restricting a key to specific models, tools, or actions) beyond spend caps, so 'least-privilege' is only partially realized. Missing for 10: explicit per-key model/tool/action scoping, granular permission controls beyond spend limits, and independent hands-on verification of the key-management API's robustness.

   • [claimed-docs] “OpenRouter provides endpoints to programmatically manage your API keys, enabling key creation and management for applications that need to d…”
   • [claimed-docs] “Workspace budgets let you cap how much a workspace can spend on OpenRouter inference. Set a dollar limit on any combination of intervals — d…”
   • [community] “They offer billing caps! Most model providers still don't do this, but if you're going to run anything in public it's very useful to have ha…”
   • [community] “One thing that OpenRouter makes easy is the ability to manage API keys (mint new ones, expiry/limits per key, etc.) that I wish other provid…”

   proof ↗⚑ flag

   Requesty—none0/10

   Requesty's docs mention BYOK (bringing your own provider keys), analytics, and 'centralized governance,' but there is no evidence of issuing scoped or least-privilege Requesty API keys/credentials specifically for individual agents. No mention of key scoping, permission levels, or per-agent credential issuance appears anywhere in the evidence pack.

   • [claimed-docs] “Bring Your Own Keys (BYOK) allows you to use your personal API keys from various providers with Requesty.”
   • [claimed-docs] “Access 600+ models through one API with intelligent routing, real-time analytics and centralized governance.”

   proof ↗⚑ flag

8. ai-native userBuild against official SDKs

   weight 2 · round drawn
   OpenRouter~partialprobed5/10

   OpenRouter documents an OpenAI-compatible API and explicitly recommends using the OpenAI SDK as a drop-in replacement, plus offers an OpenAPI spec and request builder for generating client code, which supports building against it programmatically. However, there is no evidence of dedicated first-party OpenRouter SDK packages (e.g., official Python/Node/Go libraries) beyond OpenAI SDK compatibility. Missing for 10: dedicated official multi-language SDKs, independent developer corroboration of SDK usage (only OpenAI-SDK compatibility and generic API docs are cited).

   • [claimed-docs] “You can also use the OpenAI SDK pointed at OpenRouter as a drop-in replacement.”
   • [claimed-docs] “You can also use the [OpenAI SDK](#using-the-openai-sdk) pointed at OpenRouter as a drop-in replacement.”
   • [probe] “PROBE openapi: HTTP 200 at https://openrouter.ai/openapi.json — contains "openapi" key”
   • [claimed-docs] “You can use the interactive Request Builder to generate OpenRouter API requests in the language of your choice.”

   proof ↗⚑ flag

   Requesty~partialprobed5/10

   Requesty documents OpenAI-SDK compatibility (point the OpenAI SDK's base_url at Requesty) so developers can build using the OpenAI SDK's standard interfaces, but there is no evidence of a dedicated first-party Requesty SDK package (e.g., a requesty-python or requesty-node client) or SDKs for other languages beyond OpenAI-compatible clients. missing for 10: dedicated official Requesty-branded SDKs, multi-language SDK coverage, and independent confirmation of SDK maintenance/versioning.

   • [claimed-docs] “If you're already using the OpenAI SDK, point it at Requesty and you're done. No SDK changes, no new client to learn.”
   • [claimed-docs] “base_url="https://router.requesty.ai/v1", # was: https://api.openai.com/v1”
   • [probe] “PROBE llms.txt: HTTP 200 at https://docs.requesty.ai/llms.txt # Requesty > Requesty is a unified LLM gateway and OpenAI-compatible API for …”

   proof ↗⚑ flag

9. ai-native userSubscribe to events via webhooks

   weight 2 · round drawn
   OpenRouter—none0/10

   No evidence in the pack mentions webhooks or event subscription mechanisms of any kind for OpenRouter; the documented features (routing, caching, key management, MCP server) do not include webhook support.

   ⚑ flag

   Requesty—none0/10

   No evidence anywhere in the pack of webhook subscription support for events (e.g., request completion, budget alerts, usage thresholds); the docs cover routing, fallback, caching, analytics, MCP gateway, etc., but no webhook/event-subscription feature is mentioned.

   ⚑ flag

Api quality

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

   weight 2 · round to OpenRouter
   OpenRouter✓fullprobed8/10

   OpenRouter's docs explicitly mention an interactive Request Builder for generating API requests in any language, plus a live OpenAPI spec is served and confirmed by probe, and the docs site is extensively organized with runnable-style examples across guides. Missing for 10: X, Y — no independent/hands-on account of actually running the interactive Request Builder or evidence of embedded runnable code sandboxes beyond the Request Builder claim.

   • [claimed-docs] “You can use the interactive Request Builder to generate OpenRouter API requests in the language of your choice.”
   • [probe] “PROBE openapi: HTTP 200 at https://openrouter.ai/openapi.json — contains "openapi" key”
   • [claimed-docs] “Browse the full catalog at openrouter.ai/models, or list every available slug programmatically via the GET /api/v1/models endpoint.”

   proof ↗⚑ flag

   Requesty—none0/10

   The evidence pack shows only markdown-based quickstart docs and code snippets; explicit probes for an OpenAPI/swagger spec all returned 404, and there is no mention of an interactive, runnable API reference or playground.

   • [probe] “PROBE openapi: all candidate paths 404 (https://docs.requesty.ai/openapi.json, https://docs.requesty.ai/swagger.json, https://docs.requesty.…”
   • [claimed-docs] “If you're already using the OpenAI SDK, point it at Requesty and you're done. No SDK changes, no new client to learn.”
   • [claimed-docs] “base_url="https://router.requesty.ai/v1", # was: https://api.openai.com/v1”

   proof ↗⚑ flag

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

   weight 2 · round to OpenRouter
   OpenRouter✓fullprobed9/10

   A probe confirms https://openrouter.ai/openapi.json returns HTTP 200 with an actual "openapi" key, giving a downloadable machine-readable OpenAPI spec, and docs also mention an interactive Request Builder and llms.txt for AI-native consumption. missing for 10: independent/community confirmation that the spec is actively used or kept in sync with the API by third-party developers.

   • [probe] “PROBE openapi: HTTP 200 at https://openrouter.ai/openapi.json — contains "openapi" key”
   • [probe] “PROBE llms.txt: HTTP 200 at https://openrouter.ai/llms.txt # OpenRouter > A unified API for every major LLM. One endpoint, hundreds of mode…”
   • [claimed-docs] “You can use the interactive Request Builder to generate OpenRouter API requests in the language of your choice.”

   proof ↗⚑ flag

   Requesty—none0/10

   Requesty is an API/gateway product where a downloadable OpenAPI spec would be a natural and expected artifact, so the axis applies, but a direct probe found all candidate OpenAPI/swagger paths returning 404 and no docs page references a spec file. No first-party mention of an OpenAPI spec exists anywhere in the docs pack.

   • [probe] “PROBE openapi: all candidate paths 404 (https://docs.requesty.ai/openapi.json, https://docs.requesty.ai/swagger.json, https://docs.requesty.…”

   proof ↗⚑ flag

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

   weight 2 · round drawn
   OpenRouter—none0/10

   The evidence pack covers routing, fallbacks, caching, BYOK, key management, and privacy settings, but nowhere documents API versioning (e.g., v1/v2 endpoints) or a formal deprecation policy/timeline for endpoints or models. The 'latest alias' for models is about model freshness, not API version stability guarantees.

   ⚑ flag

   Requesty—none0/10

   No evidence of API versioning scheme or a documented deprecation policy; OpenAPI spec probes all returned 404, and none of the docs mention version numbers, changelogs, or deprecation timelines.

   • [probe] “PROBE openapi: all candidate paths 404 (https://docs.requesty.ai/openapi.json, https://docs.requesty.ai/swagger.json, https://docs.requesty.…”

   proof ↗⚑ flag

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

   weight 2 · round drawn
   OpenRouter—none0/10

   The evidence pack shows OpenRouter provides a single-request API, model routing/fallbacks, and programmatic key management, but there is no documentation of a batch/bulk inference endpoint or any mechanism to submit many items/prompts in one bulk operation. missing for 10: batch API or bulk job submission endpoint, evidence of processing many items in a single call, bulk data/export operations.

   ⚑ flag

   Requesty—none0/10

   Requesty's docs cover routing, fallback, load balancing, caching, and analytics for individual requests, but there is no evidence of a batch/bulk API or mechanism for processing many items in a single operation.

   ⚑ flag

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

   weight 3 · round to Requesty
   OpenRouter—none0/10

   OpenRouter is an LLM routing/API gateway; nothing in the evidence describes user-defined event-driven rules or triggers (e.g., webhooks, if-this-then-that automations) that fire actions automatically. Model fallback and provider routing are static request-time configs, not event-triggered automation rules.

   ⚑ flag

   Requesty~partialclaimed6/10

   Requesty provides several automatic policy mechanisms that act as event-triggered rules: Fallback Policies automatically retry with different models on failure events, Load Balancing Policies route by defined weights, and Guardrails automatically scan/act on content before reaching a provider. These are rule-based automations tied to conditions/events, but they are fixed policy types rather than a general-purpose custom event/action rule engine that an AI-native user could freely define. Missing for 10: a general rules/automation builder allowing arbitrary custom triggers and actions beyond the predefined fallback/load-balancing/guardrail policy types, and independent evidence of this automation working in production.

   • [claimed-docs] “Fallback Policies automatically retry your requests with different models if one fails, ensuring your application stays reliable even when i…”
   • [claimed-docs] “Your request goes to the primary model first. If it fails (timeout, rate limit, error, etc.), the router immediately tries the next model in…”
   • [claimed-docs] “Load Balancing Policies distribute your requests across multiple models based on weights you define. Perfect for A/B testing, gradual rollou…”
   • [claimed-docs] “Guardrails scan AI request content for sensitive information before it reaches a model provider.”

   proof ↗⚑ flag

Caching

1. developerCache responses at the gateway to cut cost and latency on repeated requests

   weight 2 · round to Requesty
   OpenRouter✓fullclaimed7/10

   OpenRouter's docs explicitly describe gateway-level response caching that returns cached results with zero billable usage (cutting cost) and near-instant latency, plus provider sticky routing specifically designed to maximize cache hit rates on subsequent requests. This directly matches the story's ask for gateway-side caching to reduce cost/latency on repeated calls. Missing for 10: independent or hands-on community confirmation that caching actually reduces cost/latency in practice, and more detail on cache TTL/configurability beyond the sticky-routing mechanism.

   • [claimed-docs] “When a cached response is available, OpenRouter returns it immediately from cache with no billing (all billable usage counters are reported …”
   • [claimed-docs] “When a cached response is available, OpenRouter returns it immediately from cache with no billing (all billable usage counters are reported …”
   • [claimed-docs] “OpenRouter uses provider sticky routing to route your subsequent requests to the same provider endpoint after a cached request.”
   • [claimed-docs] “OpenRouter uses **provider sticky routing** to route your subsequent requests to the same provider endpoint after a cached request.”
   • [claimed-docs] “To maximize cache hit rates, OpenRouter uses provider sticky routing to route your subsequent requests to the same provider endpoint after a…”

   proof ↗⚑ flag

   Requesty✓fullclaimed8/10

   Requesty documents automatic gateway-level caching of long system prompts and repeated content to reduce costs, with usage analytics tracking cache savings and latency in real-time, directly matching the story's intent. missing for 10: independent/hands-on benchmarks confirming actual latency/cost reduction, and detail on cache TTL/configurability.

   • [claimed-docs] “Requesty's auto caching automatically caches long system prompts and repeated content to reduce costs on any provider that supports prompt c…”
   • [claimed-docs] “Requesty's analytics dashboard gives you complete visibility into your AI usage across all models and providers. Track costs, requests, toke…”

   proof ↗⚑ flag

Latency

1. platform engineerRun traffic through gateway infrastructure that adds minimal latency overhead to provider calls

   weight 2 · round drawn
   OpenRouter~partialcommunity5/10

   OpenRouter's docs describe latency-reducing features (response caching bypasses billing and reduces latency, sticky routing to maximize cache hits, load-balanced provider selection, streaming support) that imply a gateway designed for low overhead, but there is no explicit benchmark or first-party claim quantifying the gateway's own latency overhead versus direct provider calls. Community feedback is mixed—some praise ease of switching models and reliability (comm-2), while others report unexplained inconsistency and debugging difficulty (comm-8)—but none of this directly measures gateway latency overhead. Missing for 10: quantified latency-overhead benchmarks (vendor or independent), explicit performance comparison vs. direct provider calls, and hands-on latency testing evidence.

   • [claimed-docs] “When a cached response is available, OpenRouter returns it immediately from cache with no billing (all billable usage counters are reported …”
   • [claimed-docs] “OpenRouter uses provider sticky routing to route your subsequent requests to the same provider endpoint after a cached request.”
   • [claimed-docs] “OpenRouter routes requests to the best available providers for your model. By default, requests are load balanced across the top providers t…”
   • [claimed-docs] “The OpenRouter API allows streaming responses from any model. This is useful for building chat interfaces or other applications where the UI…”
   • [community] “Happy for the OpenRouter team... the ability to run any AI model with the same api key and same request has been great to experiment with ne…”
   • [community] “I had consistent problems (5 months back) with OpenRouter and other providers. And very hard to debug. I used the provider directly (Google)…”

   proof ↗⚑ flag

   Requesty~partialclaimed5/10

   Requesty is a gateway/router with caching, fallback, and analytics features that imply performance-conscious design, and analytics dashboard tracks latency, but there is no explicit benchmark or claim quantifying gateway-added latency overhead. missing for 10: published latency benchmarks or overhead numbers, independent performance testing, and any explicit low-latency architecture documentation.

   • [claimed-docs] “Requesty's auto caching automatically caches long system prompts and repeated content to reduce costs on any provider that supports prompt c…”
   • [claimed-docs] “Requesty's analytics dashboard gives you complete visibility into your AI usage across all models and providers. Track costs, requests, toke…”
   • [claimed-docs] “Access 600+ models through one API with intelligent routing, real-time analytics and centralized governance.”

   proof ↗⚑ flag

Agent guardrails

1. ai-native userGive an autonomous agent its own key with budget and rate guardrails so it cannot run away on spend

   weight 2 · round to OpenRouter
   OpenRouter✓fullcommunity8/10

   OpenRouter supports programmatic API key management (creation, per-key limits/expiry) and workspace-level budget caps (daily/weekly/monthly/lifetime) that auto-block requests once reached, directly enabling an agent to be given its own scoped key with hard spend guardrails; community confirms billing caps and per-key limits are a valued differentiator. missing for 10: explicit per-key rate-limit (requests/sec) controls beyond spend caps, and independent hands-on verification that runaway agent spend is actually blocked in practice.

   • [claimed-docs] “OpenRouter provides endpoints to programmatically manage your API keys, enabling key creation and management for applications that need to d…”
   • [claimed-docs] “Workspace budgets let you cap how much a workspace can spend on OpenRouter inference. Set a dollar limit on any combination of intervals — d…”
   • [community] “They offer billing caps! Most model providers still don't do this, but if you're going to run anything in public it's very useful to have ha…”
   • [community] “One thing that OpenRouter makes easy is the ability to manage API keys (mint new ones, expiry/limits per key, etc.) that I wish other provid…”

   proof ↗⚑ flag

   Requesty—none0/10

   Requesty is an LLM gateway product where issuing scoped API keys with spend/rate limits would be a natural and expected capability, but the evidence pack only shows BYOK (using your own provider keys), content-safety 'guardrails' (sensitive-data scanning, not spend limits), and usage analytics dashboards for visibility — none of which describe issuing an agent its own key with a budget cap or rate limit to prevent runaway spend.

   • [claimed-docs] “Bring Your Own Keys (BYOK) allows you to use your personal API keys from various providers with Requesty.”
   • [claimed-docs] “Guardrails scan AI request content for sensitive information before it reaches a model provider.”
   • [claimed-docs] “Requesty's analytics dashboard gives you complete visibility into your AI usage across all models and providers. Track costs, requests, toke…”

   proof ↗⚑ flag

Budgets

1. platform engineerSet hard budgets and spend limits per key, team, or user

   weight 3 · round to OpenRouter
   OpenRouter~partialcommunity6/10

   OpenRouter's docs clearly show hard, auto-enforced 'workspace budgets' with configurable daily/weekly/monthly/lifetime dollar caps that block requests once reached (openrouter-docs-10), covering team-level budgets. Per-key limits are only supported by an informal community mention of 'expiry/limits per key' (openrouter-comm-12, openrouter-comm-11) rather than first-party documentation, and per-user budget controls are not evidenced at all. Missing for 10: official docs confirming per-key hard spend limits, explicit per-user budget/quota controls, and independent verification of enforcement.

   • [claimed-docs] “Workspace budgets let you cap how much a workspace can spend on OpenRouter inference. Set a dollar limit on any combination of intervals — d…”
   • [claimed-docs] “OpenRouter provides endpoints to programmatically manage your API keys, enabling key creation and management for applications that need to d…”
   • [community] “They offer billing caps! Most model providers still don't do this, but if you're going to run anything in public it's very useful to have ha…”
   • [community] “One thing that OpenRouter makes easy is the ability to manage API keys (mint new ones, expiry/limits per key, etc.) that I wish other provid…”

   proof ↗⚑ flag

   Requesty—none0/10

   The evidence pack shows analytics/usage tracking and BYOK/governance mentions, but no documentation of setting hard budgets or spend limits per API key, team, or user. This is a plausible and expected axis for an LLM gateway product like Requesty, so absence of evidence yields 'none'.

   • [claimed-docs] “Requesty's analytics dashboard gives you complete visibility into your AI usage across all models and providers. Track costs, requests, toke…”
   • [claimed-docs] “Access 600+ models through one API with intelligent routing, real-time analytics and centralized governance.”

   proof ↗⚑ flag

Spend tracking

1. platform engineerTrack spend per model, key, team, or user across all providers in one place

   weight 3 · round drawn
   OpenRouter~partialcommunity6/10

   OpenRouter provides key management (creation, limits per key), workspace budgets with dollar caps by interval, and BYOK cost control, plus community confirmation of billing caps and per-key limits — but the evidence pack lacks explicit documentation of a unified spend dashboard broken down by model, team, or user across providers in one place. missing for 10: consolidated analytics/dashboard showing spend segmented by model, by team, and by individual user; documentation of team-level spend attribution; independent confirmation of cross-provider spend reporting granularity.

   • [claimed-docs] “OpenRouter provides endpoints to programmatically manage your API keys, enabling key creation and management for applications that need to d…”
   • [claimed-docs] “Workspace budgets let you cap how much a workspace can spend on OpenRouter inference. Set a dollar limit on any combination of intervals — d…”
   • [claimed-docs] “OpenRouter supports both OpenRouter credits and the option to bring your own provider keys (BYOK)... Using provider keys enables direct cont…”
   • [community] “They offer billing caps! Most model providers still don't do this, but if you're going to run anything in public it's very useful to have ha…”
   • [community] “One thing that OpenRouter makes easy is the ability to manage API keys (mint new ones, expiry/limits per key, etc.) that I wish other provid…”

   proof ↗⚑ flag

   Requesty~partialclaimed6/10

   Requesty's analytics dashboard tracks costs, requests, tokens, cache savings, and latency across all models/providers in real-time, and trace_id/user_id tagging plus BYOK support per-key tracking, which covers most of the story. missing for 10: explicit documentation of per-team breakdowns/team-level grouping, per-user cost attribution dashboards, and independent/hands-on corroboration of the analytics dashboard's granularity beyond vendor docs.

   • [claimed-docs] “Requesty's analytics dashboard gives you complete visibility into your AI usage across all models and providers. Track costs, requests, toke…”
   • [claimed-docs] “Requests with the same trace_id or user_id always go to the same model.”
   • [claimed-docs] “Bring Your Own Keys (BYOK) allows you to use your personal API keys from various providers with Requesty.”
   • [claimed-docs] “Access 600+ models through one API with intelligent routing, real-time analytics and centralized governance.”

   proof ↗⚑ flag

Byok

1. developerBring my own provider API keys and have the gateway use them for my traffic

   weight 2 · round to OpenRouter
   OpenRouter✓fullcommunity9/10

   OpenRouter's docs explicitly describe BYOK (bring your own provider keys), letting developers use their own provider API keys for direct control over rate limits and costs, and this is corroborated by community testimony citing consolidated billing/key management as a core benefit. Missing for 10: independent hands-on verification specifically of BYOK traffic routing (most community evidence discusses OpenRouter credits/key management generally rather than BYOK specifically).

   • [claimed-docs] “OpenRouter supports both OpenRouter credits and the option to bring your own provider keys (BYOK)... Using provider keys enables direct cont…”
   • [claimed-docs] “OpenRouter supports both OpenRouter credits and the option to bring your own provider keys (BYOK). ... Using provider keys enables direct co…”
   • [claimed-docs] “OpenRouter supports both OpenRouter credits and the option to bring your own provider keys (BYOK).”
   • [community] “One thing that OpenRouter makes easy is the ability to manage API keys (mint new ones, expiry/limits per key, etc.) that I wish other provid…”

   proof ↗⚑ flag

   Requesty✓fullclaimed8/10

   Requesty explicitly documents a BYOK feature allowing developers to use personal API keys from various providers with the gateway, alongside the standard OpenAI-compatible routing setup. Missing for 10: independent/hands-on confirmation of BYOK working in practice and details on key storage/security guarantees.

   • [claimed-docs] “Bring Your Own Keys (BYOK) allows you to use your personal API keys from various providers with Requesty.”
   • [claimed-docs] “If you're already using the OpenAI SDK, point it at Requesty and you're done. No SDK changes, no new client to learn.”
   • [claimed-docs] “base_url="https://router.requesty.ai/v1", # was: https://api.openai.com/v1”

   proof ↗⚑ flag

Programmatic admin

1. ai-native userProvision gateways, keys, and budgets programmatically through an admin API

   weight 3 · round to OpenRouter
   OpenRouter~partialcommunity6/10

   OpenRouter documents a management API for provisioning and rotating API keys programmatically (openrouter-docs-8) and community users confirm the ability to mint/limit keys (openrouter-comm-12, openrouter-comm-11). Workspace budgets are documented as a feature to cap spend (openrouter-docs-10), but the evidence doesn't explicitly confirm budgets are settable via the same admin API, and there's no mention of provisioning 'gateways' as a distinct programmable resource. Missing for 10: explicit API endpoint documentation for setting/adjusting workspace budgets programmatically, and any concept of provisioning separate 'gateways' via API.

   • [claimed-docs] “OpenRouter provides endpoints to programmatically manage your API keys, enabling key creation and management for applications that need to d…”
   • [claimed-docs] “Workspace budgets let you cap how much a workspace can spend on OpenRouter inference. Set a dollar limit on any combination of intervals — d…”
   • [community] “They offer billing caps! Most model providers still don't do this, but if you're going to run anything in public it's very useful to have ha…”
   • [community] “One thing that OpenRouter makes easy is the ability to manage API keys (mint new ones, expiry/limits per key, etc.) that I wish other provid…”

   proof ↗⚑ flag

   Requesty—none0/10

   No evidence of an admin API for programmatically provisioning gateways, keys, or budgets; docs cover BYOK (manual key entry), analytics dashboard, and routing policies, but nothing about API-driven account/key/budget provisioning. The OpenAPI/swagger probe returned 404 for all candidate paths, further indicating no discoverable admin API surface.

   • [claimed-docs] “Bring Your Own Keys (BYOK) allows you to use your personal API keys from various providers with Requesty.”
   • [claimed-docs] “Requesty's analytics dashboard gives you complete visibility into your AI usage across all models and providers. Track costs, requests, toke…”
   • [probe] “PROBE openapi: all candidate paths 404 (https://docs.requesty.ai/openapi.json, https://docs.requesty.ai/swagger.json, https://docs.requesty.…”

   proof ↗⚑ flag

Virtual keys

1. platform engineerMint gateway-managed keys for teams and apps without exposing raw provider keys

   weight 3 · round to OpenRouter
   OpenRouter✓fullcommunity8/10

   OpenRouter's docs explicitly describe programmatic key management endpoints for creating/managing/rotating API keys for apps without exposing provider keys (docs-8), backed by BYOK for provider key control (docs-9/24/32) and workspace budgets to cap spend per workspace/team (docs-10). Community corroborates ease of minting and limiting keys (comm-12, comm-11). Missing for 10: independent verification of team/app-scoped key isolation guarantees and no first-hand platform-engineer account of using the management API at scale.

   • [claimed-docs] “OpenRouter provides endpoints to programmatically manage your API keys, enabling key creation and management for applications that need to d…”
   • [claimed-docs] “OpenRouter supports both OpenRouter credits and the option to bring your own provider keys (BYOK)... Using provider keys enables direct cont…”
   • [claimed-docs] “Workspace budgets let you cap how much a workspace can spend on OpenRouter inference. Set a dollar limit on any combination of intervals — d…”
   • [community] “One thing that OpenRouter makes easy is the ability to manage API keys (mint new ones, expiry/limits per key, etc.) that I wish other provid…”
   • [community] “They offer billing caps! Most model providers still don't do this, but if you're going to run anything in public it's very useful to have ha…”

   proof ↗⚑ flag

   Requesty—none0/10

   Evidence covers BYOK (users supplying their own provider keys into Requesty) and general governance/analytics claims, but nothing describes an admin/platform-engineer flow for minting distinct gateway-managed keys per team or app that shield the underlying provider keys. Missing for 10: documentation of virtual/scoped key issuance, team/app-level key scoping, or key rotation/management APIs.

   • [claimed-docs] “Bring Your Own Keys (BYOK) allows you to use your personal API keys from various providers with Requesty.”
   • [claimed-docs] “Access 600+ models through one API with intelligent routing, real-time analytics and centralized governance.”

   proof ↗⚑ flag

Integrations

1. developerExport gateway logs and traces to my own observability stack

   weight 1 · round drawn
   OpenRouter—none0/10

   Evidence pack shows OpenRouter's API gateway features (routing, fallbacks, caching, key management, privacy settings) but contains no mention of exporting logs/traces, webhooks, log streaming, or integration with observability stacks like Datadog, OpenTelemetry, or similar. missing for 10: log/trace export mechanism, OpenTelemetry or webhook integration, documentation of any observability-stack connector.

   ⚑ flag

   Requesty—none0/10

   Requesty documents an internal analytics dashboard for usage visibility, but there is no evidence of any export mechanism (webhooks, OpenTelemetry, log/trace export API, or third-party observability integrations like Datadog/Grafana) that would let a developer send gateway logs/traces to their own observability stack.

   • [claimed-docs] “Requesty's analytics dashboard gives you complete visibility into your AI usage across all models and providers. Track costs, requests, toke…”

   proof ↗⚑ flag

Logs

1. platform engineerInspect logged requests and responses with latency, token counts, and cost attached

   weight 3 · round to Requesty
   OpenRouter—none0/10

   The evidence pack covers routing, caching, BYOK, budgets, and key management, but contains no mention of a request/response log viewer, latency dashboards, or per-request token/cost breakdowns that a platform engineer could inspect. missing for 10: activity/logs dashboard documentation, per-request latency metrics, per-request token count and cost attribution evidence.

   ⚑ flag

   Requesty~partialclaimed6/10

   Requesty's analytics dashboard docs confirm tracking of costs, requests, tokens, cache savings, and latency in real-time, which covers most of the story, but there is no evidence of inspecting individual logged request/response payload content (bodies) rather than aggregate metrics. missing for 10: evidence of per-request log inspection with full request/response bodies, screenshots or independent corroboration of the dashboard UI, and confirmation of per-call cost/latency drill-down rather than aggregate analytics.

   • [claimed-docs] “Requesty's analytics dashboard gives you complete visibility into your AI usage across all models and providers. Track costs, requests, toke…”

   proof ↗⚑ flag

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

   weight 2 · round to OpenRouter
   OpenRouter~partialprobed6/10

   OpenRouter's core capabilities—model routing, fallbacks, provider selection, key management, workspace budgets, privacy settings, and even the model catalog—are all documented as programmatically accessible via the API (openrouter-docs-8, 10, 12, 21, 35, openapi.json probe), suggesting strong API/UI parity for a product that is API-first. However, there's no explicit vendor claim of full UI-API parity, and dashboard-only features like rankings/analytics visualizations aren't confirmed as API-exposed. Missing for 10: explicit parity statement, evidence that UI-exclusive features (e.g., rankings, usage analytics dashboards) are also fully API-accessible, and independent confirmation from hands-on API users of complete feature parity.

   • [claimed-docs] “OpenRouter provides endpoints to programmatically manage your API keys, enabling key creation and management for applications that need to d…”
   • [claimed-docs] “Workspace budgets let you cap how much a workspace can spend on OpenRouter inference. Set a dollar limit on any combination of intervals — d…”
   • [claimed-docs] “You can restrict individual requests to only use providers with a certain data policy. This is also available as an account-wide setting in …”
   • [claimed-docs] “You can customize how your requests are routed using the `provider` object in the request body for [Chat Completions]”
   • [claimed-docs] “Browse the full catalog at openrouter.ai/models, or list every available slug programmatically via the GET /api/v1/models endpoint.”
   • [probe] “PROBE openapi: HTTP 200 at https://openrouter.ai/openapi.json — contains "openapi" key”
   • [probe] “PROBE keyless-endpoint: GET https://openrouter.ai/api/v1/models returned HTTP 200 application/json with 426 models (unauthenticated) - live …”
   • [community] “One thing that OpenRouter makes easy is the ability to manage API keys (mint new ones, expiry/limits per key, etc.) that I wish other provid…”

   proof ↗⚑ flag

   Requesty~partialprobed4/10

   Requesty's core inference path (chat completions, model routing) is fully API-driven via an OpenAI-compatible endpoint, and features like fallback/load-balancing policies, BYOK, and guardrails are described as usable at request time. However, there's no evidence of a management/admin API for configuring these policies, keys, or viewing analytics programmatically, and the OpenAPI spec probe returned 404s across all candidate paths, suggesting dashboard-only configuration for policy setup and analytics viewing. missing for 10: a documented admin/management API for configuring fallback policies, load balancing, guardrails, BYOK keys, and pulling analytics data programmatically; a published OpenAPI spec confirming full API parity with the dashboard.

   • [claimed-docs] “Fallback Policies automatically retry your requests with different models if one fails, ensuring your application stays reliable even when i…”
   • [claimed-docs] “Load Balancing Policies distribute your requests across multiple models based on weights you define. Perfect for A/B testing, gradual rollou…”
   • [claimed-docs] “Bring Your Own Keys (BYOK) allows you to use your personal API keys from various providers with Requesty.”
   • [claimed-docs] “Guardrails scan AI request content for sensitive information before it reaches a model provider.”
   • [claimed-docs] “Requesty's analytics dashboard gives you complete visibility into your AI usage across all models and providers. Track costs, requests, toke…”
   • [probe] “PROBE openapi: all candidate paths 404 (https://docs.requesty.ai/openapi.json, https://docs.requesty.ai/swagger.json, https://docs.requesty.…”

   proof ↗⚑ flag

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

   weight 3 · round drawn
   OpenRouter—none0/10

   The evidence pack covers API routing, model access, MCP server, and billing features, but contains no mention of any user data export capability (usage logs, account data, chat history) in open formats or account portability/closure process — the axis is applicable to a SaaS platform storing usage/billing data, but no supporting evidence exists.

   ⚑ flag

   Requesty—none0/10

   The evidence pack covers routing, caching, guardrails, analytics dashboard, and pricing, but nothing describes exporting usage data, logs, or configuration in open formats or a data-portability/account-deletion path. This is a fair question for a gateway that stores analytics/usage data, so absence of evidence yields 'none' rather than 'na'.

   • [claimed-docs] “Requesty's analytics dashboard gives you complete visibility into your AI usage across all models and providers. Track costs, requests, toke…”

   proof ↗⚑ flag

3. ai-native userRead the product's source under an open license

   weight 2 · round drawn
   OpenRouter—none0/10

   No evidence that OpenRouter's own source code (the API service, routing platform, or website) is published under an open license; evidence pack only covers API docs, features, and OpenAPI spec, not source availability. missing for 10: any repository link, open-source license file, or statement that OpenRouter's codebase is publicly available.

   ⚑ flag

   Requesty—none0/10

   No evidence of an open-source license or public source repository for Requesty; it appears to be a closed commercial SaaS gateway with only documentation and API access exposed. Missing for 10: any mention of open-source licensing, public code repository, or license file.

   ⚑ flag

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

   weight 2 · round drawn
   OpenRouter~partialcommunity6/10

   OpenRouter documents EU/US in-region routing for enterprise customers and per-request/account-wide data-policy restrictions, giving users some control over where data is processed, but this is gated to enterprise accounts rather than available to all AI-native users, and community comments note there's no true ZDR/data-sovereignty guarantee in practice. missing for 10: general-tier (non-enterprise) region selection, independent verification that in-region routing works as claimed, and clarity on residency guarantees beyond enterprise contracts.

   • [claimed-docs] “For enterprise customers, OpenRouter supports in-region routing in the EU and US. When enabled for your account, your prompts and completion…”
   • [claimed-docs] “You can restrict individual requests to only use providers with a certain data policy. This is also available as an account-wide setting in …”
   • [claimed-docs] “On your account settings page, you can set whether you would like to allow routing to providers that may train on your data (according to th…”
   • [community] “OpenRouter doesn't expose all the LLM sampling parameters/research that llamacpp, vllm, sglang expose (so no high temperature/highly diverse…”

   proof ↗⚑ flag

   Requesty~partialclaimed6/10

   Requesty offers an explicit EU-routing option (Frankfurt, AWS eu-central-1) keeping processing and storage within the EU, giving users some data-residency choice. However, evidence only shows one alternative region (EU vs default), not a broader set of selectable regions/residency options. Missing for 10: documentation of additional region choices (e.g., US-only, APAC), enterprise data-residency controls, and independent verification of enforcement.

   • [claimed-docs] “Route your AI traffic through Requesty's EU infrastructure in Frankfurt, Germany (AWS eu-central-1). All processing and storage by Requesty …”

   proof ↗⚑ flag

2. ai-native userPrevent my data from being used to train AI models

   weight 3 · round to OpenRouter
   OpenRouter~partialcommunity6/10

   OpenRouter lets users restrict requests/account-wide to providers with certain data policies and opt out of routing to providers that may train on data, plus EU/US in-region processing for enterprise, which directly supports preventing training-data use; however community evidence notes there is 'no ZDR' (zero data retention) and 'no true guarantees of ZDR/privacy/data sovereignty,' indicating limits to how absolute this protection is. missing for 10: independent verification that opt-out settings are consistently honored by all providers, clarity on default behavior, and resolution of the ZDR gap raised by users.

   • [claimed-docs] “You can restrict individual requests to only use providers with a certain data policy. This is also available as an account-wide setting in …”
   • [claimed-docs] “On your account settings page, you can set whether you would like to allow routing to providers that may train on your data (according to th…”
   • [claimed-docs] “You can restrict individual requests to only use providers with a certain data policy.”
   • [claimed-docs] “For enterprise customers, OpenRouter supports in-region routing in the EU and US. When enabled for your account, your prompts and completion…”
   • [community] “No ZDR. No dice.”
   • [community] “OpenRouter doesn't expose all the LLM sampling parameters/research that llamacpp, vllm, sglang expose (so no high temperature/highly diverse…”

   proof ↗⚑ flag

   Requesty—none0/10

   The evidence pack covers routing, caching, guardrails, EU data residency, and BYOK, but contains no statement about a no-training policy or data opt-out for model training, so this claim is unevidenced.

   ⚑ flag

3. ai-native userControl data retention and deletion

   weight 2 · round to OpenRouter
   OpenRouter~partialcommunity5/10

   OpenRouter lets users restrict routing to providers with certain data policies (e.g. no-training, zero-retention) both per-request and account-wide, and offers EU/US in-region processing for enterprise, which are real retention/data-policy controls. However there is no documented mechanism for deleting already-retained data or setting explicit retention periods, and community comments (e.g. 'No ZDR. No dice') indicate the zero-data-retention toggle has real-world limitations/gaps rather than full guaranteed retention control. Missing for 10: explicit data deletion/erasure endpoint, documented retention-period settings, and independent confirmation that ZDR/data-policy filters reliably cover all providers.

   • [claimed-docs] “You can restrict individual requests to only use providers with a certain data policy. This is also available as an account-wide setting in …”
   • [claimed-docs] “For enterprise customers, OpenRouter supports in-region routing in the EU and US. When enabled for your account, your prompts and completion…”
   • [claimed-docs] “On your account settings page, you can set whether you would like to allow routing to providers that may train on your data (according to th…”
   • [claimed-docs] “You can restrict individual requests to only use providers with a certain data policy.”
   • [community] “No ZDR. No dice.”
   • [community] “Since it's only discounted on the standard 'OpenAI,' non-ZDR route (old pricing on Azure), a lot of users won't see this benefit since many …”
   • [community] “OpenRouter doesn't expose all the LLM sampling parameters/research that llamacpp, vllm, sglang expose (so no high temperature/highly diverse…”

   proof ↗⚑ flag

   Requesty—none0/10

   The evidence pack shows EU data-residency routing and guardrails for sensitive content scanning, but nothing about data retention periods, deletion controls, or user-initiated data purge/export mechanisms. Missing for 10: documented retention policy, deletion/erasure API or dashboard control, retention configuration options.

   • [claimed-docs] “Route your AI traffic through Requesty's EU infrastructure in Frankfurt, Germany (AWS eu-central-1). All processing and storage by Requesty …”
   • [claimed-docs] “Guardrails scan AI request content for sensitive information before it reaches a model provider.”

   proof ↗⚑ flag

4. ai-native userOpt out of telemetry and usage tracking

   weight 2 · round to OpenRouter
   OpenRouter~partialcommunity4/10

   OpenRouter documents privacy controls—restricting requests to providers with certain data policies, disallowing providers that may train on your data, and EU/US in-region routing for enterprise—which give users some control over how their prompt data is handled downstream, but this is about provider-side data handling, not an explicit opt-out of OpenRouter's own telemetry/usage tracking. Community evidence directly notes 'No ZDR. No dice' and 'no true guarantees of ZDR/privacy/data sovereignty,' indicating real limits on data-handling assurances. Missing for 10: an explicit telemetry/usage-tracking opt-out toggle for OpenRouter's own platform analytics, and independent confirmation that opting out actually stops tracking.

   • [claimed-docs] “You can restrict individual requests to only use providers with a certain data policy. This is also available as an account-wide setting in …”
   • [claimed-docs] “On your account settings page, you can set whether you would like to allow routing to providers that may train on your data (according to th…”
   • [claimed-docs] “For enterprise customers, OpenRouter supports in-region routing in the EU and US. When enabled for your account, your prompts and completion…”
   • [community] “No ZDR. No dice.”
   • [community] “OpenRouter doesn't expose all the LLM sampling parameters/research that llamacpp, vllm, sglang expose (so no high temperature/highly diverse…”

   proof ↗⚑ flag

   Requesty—none0/10

   The evidence pack shows analytics/usage dashboards and EU data routing but contains no mention of a telemetry/usage-tracking opt-out setting or privacy control for disabling data collection. As a hosted API gateway that logs requests, this is a fair axis to expect documentation on, but none is present.

   • [claimed-docs] “Requesty's analytics dashboard gives you complete visibility into your AI usage across all models and providers. Track costs, requests, toke…”
   • [claimed-docs] “Route your AI traffic through Requesty's EU infrastructure in Frankfurt, Germany (AWS eu-central-1). All processing and storage by Requesty …”

   proof ↗⚑ flag

Fallbacks

1. platform engineerConfigure automatic fallback to another model or provider when one fails

   weight 3 · round to OpenRouter
   OpenRouter✓fullcommunity9/10

   OpenRouter documents explicit model fallback via a priority-ordered `models` array that auto-retries the next model on error, plus provider-level fallback/load balancing across top providers, and community confirms this works ('They also support fallback by default so you don't have to write wrappers'). This directly matches the platform engineer's story of configuring automatic fallback across models/providers on failure. Missing for 10: independent quantitative reliability data or a documented edge-case failure of the fallback mechanism itself.

   • [claimed-docs] “Provide an array of model IDs in priority order. If the first model returns an error, OpenRouter will automatically try the next model in th…”
   • [claimed-docs] “The models parameter lets you automatically try other models if the primary model's providers are down, rate-limited, or refuse to reply due…”
   • [claimed-docs] “OpenRouter routes requests to the best available providers for your model. By default, requests are load balanced across the top providers t…”
   • [claimed-docs] “Reliable AI models via our distributed infrastructure. Fall back to other providers when one goes down.”
   • [community] “Happy for the OpenRouter team... the ability to run any AI model with the same api key and same request has been great to experiment with ne…”

   proof ↗⚑ flag

   Requesty✓fullclaimed8/10

   Requesty's Fallback Policies feature explicitly documents automatic retry to a different model/provider when the primary fails (timeout, rate limit, error), directly matching the story. Missing for 10: independent/hands-on corroboration beyond vendor docs and detail on configuration granularity (e.g., how fallback chains are set up in the dashboard/API).

   • [claimed-docs] “Fallback Policies automatically retry your requests with different models if one fails, ensuring your application stays reliable even when i…”
   • [claimed-docs] “Your request goes to the primary model first. If it fails (timeout, rate limit, error, etc.), the router immediately tries the next model in…”

   proof ↗⚑ flag

Load balancing

1. platform engineerLoad-balance traffic across providers, deployments, or keys by weight, latency, or cost

   weight 2 · round to OpenRouter
   OpenRouter✓fullcommunity7/10

   Docs show default load balancing across top providers, customizable provider routing (sort by price/throughput), and ordered model fallbacks, plus BYOK for provider-key control, corroborated by community mentions of built-in fallback behavior. Missing for 10: explicit documentation of weighted routing across specific API keys and independent benchmarks validating latency/cost-based routing performance in practice.

   • [claimed-docs] “OpenRouter routes requests to the best available providers for your model. By default, requests are load balanced across the top providers t…”
   • [claimed-docs] “Provide an array of model IDs in priority order. If the first model returns an error, OpenRouter will automatically try the next model in th…”
   • [claimed-docs] “You can customize how your requests are routed using the `provider` object in the request body for [Chat Completions]”
   • [claimed-docs] “You can customize how your requests are routed using the provider object in the request body for Chat Completions.”
   • [claimed-docs] “OpenRouter supports both OpenRouter credits and the option to bring your own provider keys (BYOK)... Using provider keys enables direct cont…”
   • [community] “Happy for the OpenRouter team... the ability to run any AI model with the same api key and same request has been great to experiment with ne…”

   proof ↗⚑ flag

   Requesty~partialclaimed6/10

   Requesty documents weight-based Load Balancing Policies that distribute requests across multiple models/providers, plus session affinity via trace_id/user_id, and separate Fallback Policies for failure-driven rerouting. However, there is no evidence of latency-based or cost-based load balancing—only weight is explicitly supported. missing for 10: latency-based routing/balancing, cost-based routing/balancing, explicit per-key (not just per-model/provider) balancing.

   • [claimed-docs] “Load Balancing Policies distribute your requests across multiple models based on weights you define. Perfect for A/B testing, gradual rollou…”
   • [claimed-docs] “Requests with the same trace_id or user_id always go to the same model.”
   • [claimed-docs] “Fallback Policies automatically retry your requests with different models if one fails, ensuring your application stays reliable even when i…”
   • [claimed-docs] “Your request goes to the primary model first. If it fails (timeout, rate limit, error, etc.), the router immediately tries the next model in…”

   proof ↗⚑ flag

Policy routing

1. ai-native userMy agent can switch models mid-task by policy — cost, capability, or availability — through gateway routing rules

   weight 3 · round drawn
   OpenRouter✓fullcommunity8/10

   OpenRouter's docs and community evidence confirm model fallback lists (priority order, automatic retry on error/rate-limit/down), provider-selection routing rules, load balancing across providers, a 'latest' alias for staying current, and an auto-routing 'meta' model that picks capability-appropriate models to control cost — directly matching policy-based mid-task model switching by cost/capability/availability. missing for 10: no first-party documentation or hands-on evidence of dynamically switching models *within* a single in-flight task/conversation (vs. per-request fallback/config), and no independent benchmark validating routing-rule reliability in production.

   • [claimed-docs] “The models parameter lets you automatically try other models if the primary model's providers are down, rate-limited, or refuse to reply due…”
   • [claimed-docs] “Provide an array of model IDs in priority order. If the first model returns an error, OpenRouter will automatically try the next model in th…”
   • [claimed-docs] “OpenRouter routes requests to the best available providers for your model. By default, requests are load balanced across the top providers t…”
   • [claimed-docs] “You can customize how your requests are routed using the `provider` object in the request body for [Chat Completions]”
   • [claimed-docs] “a latest alias that always resolves to the newest OpenAI flagship model, so your code keeps using the freshest version without redeploying”
   • [community] “Happy for the OpenRouter team... the ability to run any AI model with the same api key and same request has been great to experiment with ne…”
   • [community] “One thing I really like about OpenRouter is their 'meta' model that automatically routes the prompt to an appropriately capable model. Saves…”
   • [claimed-docs] “Reliable AI models via our distributed infrastructure. Fall back to other providers when one goes down.”

   proof ↗⚑ flag

   Requesty✓fullclaimed8/10

   Requesty's gateway supports fallback policies (retry with different models on failure/rate limit/error), load-balancing policies (distribute across models by weight, sticky routing by trace/user), and access to 300+/600+ models via a single API, directly enabling policy-based mid-task model switching for cost, capability, or availability reasons. missing for 10: no independent/hands-on corroboration of dynamic policy switching in a live agent task, and no explicit example combining cost+capability+availability rules in one policy config.

   • [claimed-docs] “Fallback Policies automatically retry your requests with different models if one fails, ensuring your application stays reliable even when i…”
   • [claimed-docs] “Your request goes to the primary model first. If it fails (timeout, rate limit, error, etc.), the router immediately tries the next model in…”
   • [claimed-docs] “Load Balancing Policies distribute your requests across multiple models based on weights you define. Perfect for A/B testing, gradual rollou…”
   • [claimed-docs] “Requests with the same trace_id or user_id always go to the same model.”
   • [claimed-docs] “Using the Requesty integration, you can: Use 300+ models while coding, giving you flexibility to choose the best model for each task.”
   • [claimed-docs] “Access 600+ models through one API with intelligent routing, real-time analytics and centralized governance.”

   proof ↗⚑ flag

Rate limits

1. platform engineerSmooth provider rate limits by spreading traffic across keys and queuing or throttling requests

   weight 2 · round drawn
   OpenRouter~partialcommunity5/10

   OpenRouter's default load balancing across providers and automatic model/provider fallbacks (docs-3,4,19) inherently smooths provider-side rate limits, and its key-management API (docs-8) plus BYOK (docs-9,24,32) let engineers create/distribute multiple keys with per-key limits (echoed by comm-12). But there is no explicit documentation of client-side request queuing or throttling, or of deliberately spreading traffic across multiple OpenRouter keys for load smoothing — the evidence covers provider-side resilience, not key-pool traffic shaping. Missing for 10: explicit queuing/throttling mechanism, documented multi-key load-balancing pattern, independent confirmation of rate-limit smoothing at scale.

   • [claimed-docs] “The models parameter lets you automatically try other models if the primary model's providers are down, rate-limited, or refuse to reply due…”
   • [claimed-docs] “OpenRouter routes requests to the best available providers for your model. By default, requests are load balanced across the top providers t…”
   • [claimed-docs] “OpenRouter provides endpoints to programmatically manage your API keys, enabling key creation and management for applications that need to d…”
   • [claimed-docs] “OpenRouter supports both OpenRouter credits and the option to bring your own provider keys (BYOK)... Using provider keys enables direct cont…”
   • [claimed-docs] “Provide an array of model IDs in priority order. If the first model returns an error, OpenRouter will automatically try the next model in th…”
   • [community] “One thing that OpenRouter makes easy is the ability to manage API keys (mint new ones, expiry/limits per key, etc.) that I wish other provid…”

   proof ↗⚑ flag

   Requesty~partialclaimed5/10

   Requesty's Fallback Policies explicitly retry on rate-limit errors by switching models, and Load Balancing Policies distribute requests across multiple models/providers by weight, which can smooth rate-limit pressure; BYOK lets users supply multiple provider keys. However, there is no documented queuing/throttling mechanism or explicit per-key round-robin/rate-limit-aware routing across multiple keys for the same provider. Missing for 10: explicit request queuing/throttling controls, documented multi-key rotation within a single provider, and rate-limit-specific load-balancing logic (vs. general failure retries).

   • [claimed-docs] “Fallback Policies automatically retry your requests with different models if one fails, ensuring your application stays reliable even when i…”
   • [claimed-docs] “Your request goes to the primary model first. If it fails (timeout, rate limit, error, etc.), the router immediately tries the next model in…”
   • [claimed-docs] “Load Balancing Policies distribute your requests across multiple models based on weights you define. Perfect for A/B testing, gradual rollou…”
   • [claimed-docs] “Bring Your Own Keys (BYOK) allows you to use your personal API keys from various providers with Requesty.”

   proof ↗⚑ flag

Retries

1. platform engineerSet automatic retry policies for transient provider errors

   weight 2 · round to OpenRouter
   OpenRouter~partialcommunity7/10

   OpenRouter's model-fallbacks and provider load-balancing features automatically retry a request against alternate providers/models when the primary is down, rate-limited, or errors out, and this is corroborated by community reports of built-in fallback behavior (openrouter-docs-3, openrouter-docs-4, openrouter-docs-17, openrouter-docs-19, openrouter-comm-2). However, this is provider/model-level fallback rather than a granular, configurable retry policy (e.g., retry count, backoff intervals, specific transient-error codes) that a platform engineer might expect. Missing for 10: explicit retry-count/backoff configuration options, granular control over which transient error codes trigger retries, and independent verification of retry behavior under real outages.

   • [claimed-docs] “The models parameter lets you automatically try other models if the primary model's providers are down, rate-limited, or refuse to reply due…”
   • [claimed-docs] “OpenRouter routes requests to the best available providers for your model. By default, requests are load balanced across the top providers t…”
   • [claimed-docs] “Reliable AI models via our distributed infrastructure. Fall back to other providers when one goes down.”
   • [claimed-docs] “Provide an array of model IDs in priority order. If the first model returns an error, OpenRouter will automatically try the next model in th…”
   • [community] “Happy for the OpenRouter team... the ability to run any AI model with the same api key and same request has been great to experiment with ne…”

   proof ↗⚑ flag

   Requesty~partialclaimed6/10

   Requesty's Fallback Policies explicitly retry requests on a different model when the primary fails due to timeout, rate limit, or error, which directly addresses transient provider errors. However, this is model-fallback rather than a configurable retry policy (e.g., retry counts, backoff intervals, retry-same-provider-first) explicitly for transient errors. missing for 10: documentation of configurable retry counts/backoff on the same provider before failover, independent/hands-on confirmation of retry behavior, and explicit mention of 'transient error' handling distinct from full model fallback.

   • [claimed-docs] “Fallback Policies automatically retry your requests with different models if one fails, ensuring your application stays reliable even when i…”
   • [claimed-docs] “Your request goes to the primary model first. If it fails (timeout, rate limit, error, etc.), the router immediately tries the next model in…”

   proof ↗⚑ flag

Streaming

1. developerStream token-by-token responses through the gateway from any provider

   weight 3 · round to OpenRouter
   OpenRouter✓fullcommunity8/10

   OpenRouter's docs explicitly state streaming is supported for any model through the gateway API, and community feedback corroborates using a single API/key across many providers with model switching in production. missing for 10: independent hands-on confirmation specifically of token-by-token streaming behavior (e.g., latency/chunking quality) and any provider-specific streaming caveats or limitations.

   • [claimed-docs] “The OpenRouter API allows streaming responses from any model. This is useful for building chat interfaces or other applications where the UI…”
   • [claimed-docs] “The OpenRouter API allows streaming responses from *any model*. This is useful for building chat interfaces or other applications where the …”
   • [claimed-docs] “OpenRouter gives you access to hundreds of AI models through a single API endpoint.”
   • [community] “Happy for the OpenRouter team... the ability to run any AI model with the same api key and same request has been great to experiment with ne…”

   proof ↗⚑ flag

   Requesty~partialclaimed4/10

   Requesty claims full OpenAI-SDK compatibility with no code changes (drop-in base_url swap), which implies standard SDK streaming (stream=True) would work across any of its 300+ models, but no evidence pack item explicitly confirms streaming/token-by-token behavior or documents a streaming example. missing for 10: explicit streaming documentation/example, confirmation across multiple providers, and any independent/hands-on verification of streaming behavior.

   • [claimed-docs] “If you're already using the OpenAI SDK, point it at Requesty and you're done. No SDK changes, no new client to learn.”
   • [claimed-docs] “base_url="https://router.requesty.ai/v1", # was: https://api.openai.com/v1”
   • [claimed-docs] “Access 600+ models through one API with intelligent routing, real-time analytics and centralized governance.”

   proof ↗⚑ flag

Tool calling

1. developerRequest structured JSON-schema outputs across providers

   weight 1 · round to Requesty
   OpenRouter—none0/10

   The evidence pack covers tool-calling standardization, streaming, routing, fallbacks, and key management, but contains no mention of structured JSON-schema/response_format output support across providers. missing for 10: any documentation or example of JSON-schema response_format, schema validation, or structured output enforcement across providers.

   ⚑ flag

   Requesty✓fullclaimed8/10

   Requesty explicitly documents structured outputs, stating it makes 'every supported model speak structured JSON — from simple json_object mode to strict, schema-enforced json_schema mode,' directly addressing cross-provider JSON-schema support via its unified OpenAI-compatible API. Missing for 10: independent/hands-on verification across multiple providers and no explicit list of which of the 300+ models fully honor strict schema enforcement.

   • [claimed-docs] “Requesty makes every supported model speak structured JSON — from simple json_object mode to strict, schema-enforced json_schema mode.”
   • [claimed-docs] “Access 600+ models through one API with intelligent routing, real-time analytics and centralized governance.”
   • [claimed-docs] “If you're already using the OpenAI SDK, point it at Requesty and you're done. No SDK changes, no new client to learn.”

   proof ↗⚑ flag

2. developerMake tool and function calls across different providers with a consistent schema

   weight 3 · round to OpenRouter
   OpenRouter✓fullcommunity8/10

   OpenRouter explicitly documents a standardized tool-calling interface across models/providers (docs-5), consistent with its single-API model access across 500+ models and providers (docs-1, docs-16), and community confirms using the same API key/request format to switch models seamlessly (openrouter-comm-2). Streaming is also documented as working across any model (docs-11/20), supporting the streaming-tools theme. Missing for 10: no independent hands-on verification specifically of function/tool-call schema consistency across multiple providers, and no detailed example showing identical tool-call JSON working unchanged across e.g. OpenAI vs Anthropic vs Google models.

   • [claimed-docs] “OpenRouter standardizes the tool calling interface across models and providers, making it easy to integrate external tools with any supporte…”
   • [claimed-docs] “OpenRouter gives you access to hundreds of AI models through a single API endpoint.”
   • [claimed-docs] “The OpenRouter API allows streaming responses from any model. This is useful for building chat interfaces or other applications where the UI…”
   • [claimed-docs] “The OpenRouter API allows streaming responses from *any model*. This is useful for building chat interfaces or other applications where the …”
   • [community] “Happy for the OpenRouter team... the ability to run any AI model with the same api key and same request has been great to experiment with ne…”

   proof ↗⚑ flag

   Requesty~partialclaimed6/10

   Requesty's OpenAI-compatible unified API (docs-1, docs-2, docs-16) implies that developers can use the same OpenAI SDK request format—including tool/function-call schema—across 300+/600+ models, and structured-outputs docs (docs-14) show JSON/schema-enforced output support across providers. However, there is no explicit documentation or example showing tool/function-call payloads being translated or normalized for non-OpenAI-native providers, nor any hands-on confirmation that function calling works uniformly across all providers. Missing for 10: explicit function/tool-calling schema documentation, cross-provider tool-call examples, and independent verification of consistent behavior across providers.

   • [claimed-docs] “If you're already using the OpenAI SDK, point it at Requesty and you're done. No SDK changes, no new client to learn.”
   • [claimed-docs] “base_url="https://router.requesty.ai/v1", # was: https://api.openai.com/v1”
   • [claimed-docs] “Requesty makes every supported model speak structured JSON — from simple json_object mode to strict, schema-enforced json_schema mode.”
   • [claimed-docs] “Access 600+ models through one API with intelligent routing, real-time analytics and centralized governance.”

   proof ↗⚑ flag

Catalog

1. developerBrowse or query a catalog of available models with pricing and context-window metadata

   weight 2 · round to OpenRouter
   OpenRouter✓fullprobed9/10

   OpenRouter documents a browsable model catalog at openrouter.ai/models and a programmatic GET /api/v1/models endpoint listing model slugs, and a live probe confirms this endpoint returns 426 models with pricing/context-window metadata unauthenticated. Community feedback corroborates ease of comparing/switching models via the unified catalog. Missing for 10: no independent third-party review specifically validating completeness/accuracy of pricing or context-window fields beyond the probe.

   • [claimed-docs] “Browse the full catalog at openrouter.ai/models, or list every available slug programmatically via the GET /api/v1/models endpoint.”
   • [probe] “PROBE keyless-endpoint: GET https://openrouter.ai/api/v1/models returned HTTP 200 application/json with 426 models (unauthenticated) - live …”
   • [claimed-docs] “300T+ Monthly Tokens 10M+ Global Users 80+ Providers 500+ Models”
   • [community] “Happy for the OpenRouter team... the ability to run any AI model with the same api key and same request has been great to experiment with ne…”

   proof ↗⚑ flag

   Requesty—none0/10

   Evidence confirms Requesty routes across 300–600+ models via a unified API, but nothing in the pack documents a browsable/queryable model catalog exposing pricing or context-window metadata (no /models endpoint, no models page, and the OpenAPI probe returned 404s). missing for 10: a models catalog page or API endpoint, per-model pricing data, per-model context-window metadata.

   • [claimed-docs] “Access 600+ models through one API with intelligent routing, real-time analytics and centralized governance.”
   • [claimed-docs] “Using the Requesty integration, you can: Use 300+ models while coding, giving you flexibility to choose the best model for each task.”
   • [probe] “PROBE openapi: all candidate paths 404 (https://docs.requesty.ai/openapi.json, https://docs.requesty.ai/swagger.json, https://docs.requesty.…”

   proof ↗⚑ flag

Compatibility

1. developerPoint existing OpenAI-compatible code at the gateway by changing only the base URL and key

   weight 3 · round to OpenRouter
   OpenRouter✓fullprobed9/10

   Docs explicitly state the OpenAI SDK can be pointed at OpenRouter as a drop-in replacement, and community users corroborate using 'the same api key and same request' across models, confirming base-URL/key swap works in practice. Missing for 10: no explicit first-party code snippet showing the exact base_url/api_key change in the evidence pack, only the general drop-in claim.

   • [claimed-docs] “You can also use the OpenAI SDK pointed at OpenRouter as a drop-in replacement.”
   • [claimed-docs] “You can also use the [OpenAI SDK](#using-the-openai-sdk) pointed at OpenRouter as a drop-in replacement.”
   • [community] “Happy for the OpenRouter team... the ability to run any AI model with the same api key and same request has been great to experiment with ne…”
   • [probe] “PROBE llms.txt: HTTP 200 at https://openrouter.ai/llms.txt # OpenRouter > A unified API for every major LLM. One endpoint, hundreds of mode…”

   proof ↗⚑ flag

   Requesty✓fullprobed8/10

   Docs explicitly show swapping only base_url (to router.requesty.ai/v1) and API key while keeping OpenAI SDK unchanged, directly matching the story. Missing for 10: independent/hands-on third-party confirmation beyond vendor docs and a formal OpenAPI spec (probe found 404s).

   • [claimed-docs] “If you're already using the OpenAI SDK, point it at Requesty and you're done. No SDK changes, no new client to learn.”
   • [claimed-docs] “base_url="https://router.requesty.ai/v1", # was: https://api.openai.com/v1”
   • [probe] “PROBE llms.txt: HTTP 200 at https://docs.requesty.ai/llms.txt # Requesty > Requesty is a unified LLM gateway and OpenAI-compatible API for …”

   proof ↗⚑ flag

One endpoint

1. developerCall many model providers through one consistent API

   weight 3 · round to OpenRouter
   OpenRouter✓fullprobed9/10

   OpenRouter's core value proposition is a single API endpoint (OpenAI-SDK compatible) that routes to hundreds of models across 80+ providers, with fallback, load-balancing, standardized tool calling, and streaming for any model — corroborated by live probes (426-model catalog, openapi.json) and community testimonials confirming 'same API key and same request' across providers with automatic fallback. Minor gaps: community notes some inconsistencies (missing sampling params, occasional reliability complaints), missing for 10: fully independent benchmark of API consistency across all providers and resolution of reported debugging/latency complaints.

   • [claimed-docs] “OpenRouter gives you access to hundreds of AI models through a single API endpoint.”
   • [claimed-docs] “You can also use the OpenAI SDK pointed at OpenRouter as a drop-in replacement.”
   • [claimed-docs] “Provide an array of model IDs in priority order. If the first model returns an error, OpenRouter will automatically try the next model in th…”
   • [claimed-docs] “OpenRouter standardizes the tool calling interface across models and providers, making it easy to integrate external tools with any supporte…”
   • [claimed-docs] “The OpenRouter API allows streaming responses from *any model*. This is useful for building chat interfaces or other applications where the …”
   • [probe] “PROBE llms.txt: HTTP 200 at https://openrouter.ai/llms.txt # OpenRouter > A unified API for every major LLM. One endpoint, hundreds of mode…”
   • [probe] “PROBE keyless-endpoint: GET https://openrouter.ai/api/v1/models returned HTTP 200 application/json with 426 models (unauthenticated) - live …”
   • [community] “Happy for the OpenRouter team... the ability to run any AI model with the same api key and same request has been great to experiment with ne…”
   • [community] “It's definitely the best way to try out new models without fiddling with each providers distinct APIs. That said, I don't understand people …”

   proof ↗⚑ flag

   Requesty✓fullprobed8/10

   Requesty is explicitly documented as an OpenAI-compatible unified API/gateway supporting 300+ (or 600+) models via a single base_url swap, with routing, fallback, load balancing, and BYOK across providers, all first-party documented and corroborated by an llms.txt probe describing it as a unified LLM gateway. Missing for 10: independent/hands-on third-party verification beyond docs, and no public OpenAPI spec found (404s on probe).

   • [claimed-docs] “If you're already using the OpenAI SDK, point it at Requesty and you're done. No SDK changes, no new client to learn.”
   • [claimed-docs] “base_url="https://router.requesty.ai/v1", # was: https://api.openai.com/v1”
   • [claimed-docs] “Bring Your Own Keys (BYOK) allows you to use your personal API keys from various providers with Requesty.”
   • [claimed-docs] “Access 600+ models through one API with intelligent routing, real-time analytics and centralized governance.”
   • [probe] “PROBE llms.txt: HTTP 200 at https://docs.requesty.ai/llms.txt # Requesty > Requesty is a unified LLM gateway and OpenAI-compatible API for …”

   proof ↗⚑ flag