How Radeon RX 9070 XT’s scores are calculated
The full audit trail, recomputed from the verdict data at build time through the same code that produced the leaderboard: verdict × quality × story weight per cell, cells sum to dimension scores, dimensions blend into the PA Score. Every number on the product page is reproducible from this page alone; for why the formula looks like this, see the methodology.
verdict factors: full ×1.0 · partial ×0.6 · disputed ×0.3 · none ×0.0 · n/a excluded from both sides · cell points = weight × quality × factor · cell max = weight × 10
PA Score28/100
Agent-ready 38.2 × 0.30 = 11.46
API quality n/a — excluded, its ×0.20 weight renormalized away
Openness 54.0 × 0.20 = 10.80
Built-in AI 0.0 × 0.15 = 0.00
Automation 0.0 × 0.15 = 0.00
(11.46 + 10.80 + 0.00 + 0.00) ÷ (0.30 + 0.20 + 0.15 + 0.15) = 22.26 ÷ 0.80 = 27.8 — weights renormalized over the scored components
Scores are stored to 1 decimal; the product page’s pills round to whole numbers for display. Each dimension below shows the stories, verdicts, and cited evidence behind its number.
Agent-ready38.2/100×0.30 of the PA blend
Outside-in: can YOUR agent reach and drive this product — API, MCP, CLI, headless runs, agent docs.
Point an agent at llms.txt or agent-oriented docsweight 2
2 (weight) × 8 (quality) × 1.0 (full) = 16.0 of 20 max
- [probe] https://rocm.docs.amd.com/llms.txt“PROBE llms.txt: HTTP 200 at https://rocm.docs.amd.com/llms.txt # ROCm documentation > Note: ROCm documentation is split across multiple projects. In addition to this file, each proje”
- [probe] https://rocm.docs.amd.com/openapi.json“PROBE openapi: all candidate paths 404 (https://rocm.docs.amd.com/openapi.json, https://rocm.docs.amd.com/swagger.json, https://rocm.docs.amd.com/api/openapi.json, https://rocm.docs.amd.com/.well-known/openapi.json)”
- [claimed-docs] https://rocm.docs.amd.com/projects/radeon/en/latest/“PyTorch on Windows updated with ROCm 7.2.1 on AMD Radeon graphics products and AMD Ryzen AI processors.”
Run the product headlessly / in CI for automationweight 2
2 (weight) × 4 (quality) × 0.6 (partial) = 4.8 of 20 max
- [claimed-docs] https://rocm.docs.amd.com/projects/radeon/en/latest/“Radeon™ GPUs (9000 & select 7000 Series) Linux® PyTorch, TensorFlow, JAX, ONNX”
- [claimed-docs] https://rocm.docs.amd.com/projects/radeon/en/latest/“**vLLM**: Full support.”
- [claimed-docs] https://rocm.docs.amd.com/projects/radeon/en/latest/“**Llama.cpp**: Supported for efficient inference.”
- [claimed-docs] https://www.amd.com/en/products/graphics/desktops/radeon/9000-series/amd-radeon-rx-9070xt.html“OS Support Windows 10 - 64-Bit Edition , Windows 11 - 64-Bit Edition , Linux x86 64-Bit”
Plug MCP servers into this product so it can use their toolsweight 3
n/a — not applicable to this product: excluded from numerator and denominator
no evidence cited — the verdict rests on absence of evidence, re-checked on refresh
Connect an agent via an official MCP serverweight 3
n/a — not applicable to this product: excluded from numerator and denominator
no evidence cited — the verdict rests on absence of evidence, re-checked on refresh
Use an official CLIweight 2
2 (weight) × 0 (quality) × 0.0 (none) = 0.0 of 20 max
no evidence cited — the verdict rests on absence of evidence, re-checked on refresh
Drive the product through a documented public APIweight 3
3 (weight) × 4 (quality) × 0.6 (partial) = 7.2 of 30 max
- [claimed-docs] https://rocm.docs.amd.com/projects/radeon/en/latest/“PyTorch on Windows updated with ROCm 7.2.1 on AMD Radeon graphics products and AMD Ryzen AI processors.”
- [claimed-docs] https://rocm.docs.amd.com/projects/radeon/en/latest/“Radeon™ GPUs (9000 & select 7000 Series) Linux® PyTorch, TensorFlow, JAX, ONNX”
- [claimed-docs] https://rocm.docs.amd.com/projects/radeon/en/latest/“**vLLM**: Full support.”
- [claimed-docs] https://rocm.docs.amd.com/projects/radeon/en/latest/“**Llama.cpp**: Supported for efficient inference.”
- [probe] https://rocm.docs.amd.com/llms.txt“PROBE llms.txt: HTTP 200 at https://rocm.docs.amd.com/llms.txt # ROCm documentation > Note: ROCm documentation is split across multiple projects. In addition to this file, each proje”
- [probe] https://rocm.docs.amd.com/openapi.json“PROBE openapi: all candidate paths 404 (https://rocm.docs.amd.com/openapi.json, https://rocm.docs.amd.com/swagger.json, https://rocm.docs.amd.com/api/openapi.json, https://rocm.docs.amd.com/.well-known/openapi.json)”
Issue scoped/least-privilege API credentials for an agentweight 2
n/a — not applicable to this product: excluded from numerator and denominator
no evidence cited — the verdict rests on absence of evidence, re-checked on refresh
Build against official SDKsweight 2
2 (weight) × 7 (quality) × 1.0 (full) = 14.0 of 20 max
- [claimed-docs] https://rocm.docs.amd.com/projects/radeon/en/latest/“PyTorch on Windows updated with ROCm 7.2.1 on AMD Radeon graphics products and AMD Ryzen AI processors.”
- [claimed-docs] https://rocm.docs.amd.com/projects/radeon/en/latest/“Radeon™ GPUs (9000 & select 7000 Series) Linux® PyTorch, TensorFlow, JAX, ONNX”
- [claimed-docs] https://rocm.docs.amd.com/projects/radeon/en/latest/“Radeon™ GPUs (9000 & select 7000 Series) Windows® PyTorch”
- [claimed-docs] https://rocm.docs.amd.com/projects/radeon/en/latest/“**vLLM**: Full support.”
- [claimed-docs] https://rocm.docs.amd.com/projects/radeon/en/latest/“**Llama.cpp**: Supported for efficient inference.”
- [claimed-docs] https://rocm.docs.amd.com/projects/radeon/en/latest/“The same ROCm™ stack that powers your desktop development on RDNA™ architecture GPUs also supports AMD Instinct™ accelerators on CDNA™ architecture in the datacenter. This unified platform creates a seamless migration path”
- [probe] https://rocm.docs.amd.com/llms.txt“PROBE llms.txt: HTTP 200 at https://rocm.docs.amd.com/llms.txt # ROCm documentation > Note: ROCm documentation is split across multiple projects. In addition to this file, each proje”
Subscribe to events via webhooksweight 2
n/a — not applicable to this product: excluded from numerator and denominator
no evidence cited — the verdict rests on absence of evidence, re-checked on refresh
Agent-ready = 42.0 ÷ 110 × 100 = 38.2
API qualityn/a×0.20 of the PA blend
The programmable surface once an agent is there — machine-readable spec, interactive docs, sandbox, versioning discipline.
Explore an interactive API reference with runnable examplesweight 2
n/a — not applicable to this product: excluded from numerator and denominator
no evidence cited — the verdict rests on absence of evidence, re-checked on refresh
Download a machine-readable API spec (OpenAPI or equivalent)weight 2
n/a — not applicable to this product: excluded from numerator and denominator
no evidence cited — the verdict rests on absence of evidence, re-checked on refresh
Test against a sandbox environment without touching production dataweight 1
n/a — not applicable to this product: excluded from numerator and denominator
no evidence cited — the verdict rests on absence of evidence, re-checked on refresh
Rely on versioned APIs with a documented deprecation policyweight 2
n/a — not applicable to this product: excluded from numerator and denominator
no evidence cited — the verdict rests on absence of evidence, re-checked on refresh
every cell n/a — unscored (not zero), excluded from the blend
Openness54.0/100×0.20 of the PA blend
Can you leave, inspect, or self-host — data export, open source, portability.
Do everything through the API that I can do in the UIweight 2
n/a — not applicable to this product: excluded from numerator and denominator
no evidence cited — the verdict rests on absence of evidence, re-checked on refresh
Export all of my data in open formats and leaveweight 3
n/a — not applicable to this product: excluded from numerator and denominator
no evidence cited — the verdict rests on absence of evidence, re-checked on refresh
Read the product's source under an open licenseweight 2
2 (weight) × 5 (quality) × 0.6 (partial) = 6.0 of 20 max
- [claimed-docs] https://rocm.docs.amd.com/projects/radeon/en/latest/“As a primarily open-source ecosystem, ROCm™ gives you the freedom to inspect, customize, and tailor the software stack to your specific needs”
- [probe] https://rocm.docs.amd.com/llms.txt“PROBE llms.txt: HTTP 200 at https://rocm.docs.amd.com/llms.txt # ROCm documentation > Note: ROCm documentation is split across multiple projects. In addition to this file, each proje”
Self-host the core productweight 3
3 (weight) × 7 (quality) × 1.0 (full) = 21.0 of 30 max
- [claimed-docs] https://rocm.docs.amd.com/projects/radeon/en/latest/“A local workstation equipped with a Radeon™ GPU, featuring up to 48GB of VRAM, offers a secure and economical alternative to relying solely on cloud-based solutions.”
- [claimed-docs] https://rocm.docs.amd.com/projects/radeon/en/latest/“This unified platform creates a seamless migration path, allowing you to develop applications locally and deploy them at scale with confidence.”
- [claimed-docs] https://rocm.docs.amd.com/projects/radeon/en/latest/“The same ROCm™ stack that powers your desktop development on RDNA™ architecture GPUs also supports AMD Instinct™ accelerators on CDNA™ architecture in the datacenter. This unified platform creates a seamless migration path”
- [claimed-docs] https://rocm.docs.amd.com/projects/radeon/en/latest/“Radeon™ GPUs (9000 & select 7000 Series) Linux® PyTorch, TensorFlow, JAX, ONNX”
- [claimed-docs] https://rocm.docs.amd.com/projects/radeon/en/latest/“**vLLM**: Full support.”
- [claimed-docs] https://rocm.docs.amd.com/projects/radeon/en/latest/“**Llama.cpp**: Supported for efficient inference.”
Openness = 27.0 ÷ 50 × 100 = 54.0
Built-in AI0.0/100×0.15 of the PA blend
Inside-out: how agentic the product itself is for its users — built-in assistants, autonomous features.
Get AI-generated insights and suggestions from my data inside the productweight 2
2 (weight) × 0 (quality) × 0.0 (none) = 0.0 of 20 max
no evidence cited — the verdict rests on absence of evidence, re-checked on refresh
Set up automations that run autonomously in the backgroundweight 2
n/a — not applicable to this product: excluded from numerator and denominator
no evidence cited — the verdict rests on absence of evidence, re-checked on refresh
Delegate tasks to a built-in AI assistant inside the productweight 3
3 (weight) × 0 (quality) × 0.0 (none) = 0.0 of 30 max
no evidence cited — the verdict rests on absence of evidence, re-checked on refresh
Operate the product with natural-language commandsweight 2
2 (weight) × 0 (quality) × 0.0 (none) = 0.0 of 20 max
no evidence cited — the verdict rests on absence of evidence, re-checked on refresh
Built-in AI = 0.0 ÷ 70 × 100 = 0.0
Automation0.0/100×0.15 of the PA blend
Depth of automation primitives — rules, scheduling, bulk operations, webhooks.
Perform bulk operations across many items at onceweight 2
2 (weight) × 0 (quality) × 0.0 (none) = 0.0 of 20 max
no evidence cited — the verdict rests on absence of evidence, re-checked on refresh
Define rules that trigger actions automatically on eventsweight 3
n/a — not applicable to this product: excluded from numerator and denominator
no evidence cited — the verdict rests on absence of evidence, re-checked on refresh
Schedule recurring jobs or workflowsweight 2
2 (weight) × 0 (quality) × 0.0 (none) = 0.0 of 20 max
no evidence cited — the verdict rests on absence of evidence, re-checked on refresh
Version, review, and roll back my automationsweight 1
n/a — not applicable to this product: excluded from numerator and denominator
no evidence cited — the verdict rests on absence of evidence, re-checked on refresh
Automation = 0.0 ÷ 40 × 100 = 0.0