How llama.cpp’s scores are calculated

Point an agent at llms.txt or agent-oriented docsweight 2

2 (weight) × 0 (quality) × 0.0 (none) = 0.0 of 20 max

• [probe] https://github.com/llms.txt“PROBE llms.txt: HTTP 200 at https://github.com/llms.txt # GitHub > GitHub is a developer platform for building, shipping, and maintaining software. It provides cloud-based Git”

Run the product headlessly / in CI for automationweight 2

2 (weight) × 6 (quality) × 0.6 (partial) = 7.2 of 20 max

• [github] https://github.com/ggml-org/llama.cpp“llama cli -hf ggml-org/Qwen3.5-0.8B-GGUF”
• [github] https://github.com/ggml-org/llama.cpp“llama serve -hf ggml-org/Qwen3.5-0.8B-GGUF”
• [github] https://github.com/ggml-org/llama.cpp“Run with Docker - see our [Docker documentation](docs/docker.md)”
• [github] https://github.com/ggml-org/llama.cpp“Download pre-built binaries from the [releases page](https://github.com/ggml-org/llama.cpp/releases)”
• [github] https://github.com/ggml-org/llama.cpp“Plain C/C++ implementation without any dependencies”

Plug MCP servers into this product so it can use their toolsweight 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

Connect an agent via an official MCP serverweight 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

Use an official CLIweight 2

2 (weight) × 8 (quality) × 1.0 (full) = 16.0 of 20 max

• [github] https://github.com/ggml-org/llama.cpp“llama cli -hf ggml-org/Qwen3.5-0.8B-GGUF”
• [github] https://github.com/ggml-org/llama.cpp“VLM session with `llama cli`”
• [github] https://github.com/ggml-org/llama.cpp“Download pre-built binaries from the [releases page](https://github.com/ggml-org/llama.cpp/releases)”
• [community] https://news.ycombinator.com/item?id=43943047“User found the vision feature 'works super well' after compiling from source, using llama-mtmd-cli with quantized multimodal models like Gemma-3, loading images via '/image image.png' in chat.”

Drive the product through a documented public APIweight 3

3 (weight) × 4 (quality) × 0.6 (partial) = 7.2 of 30 max

• [github] https://github.com/ggml-org/llama.cpp“llama serve -hf ggml-org/Qwen3.5-0.8B-GGUF”
• [github] https://github.com/ggml-org/llama.cpp“Built-in web UI against `llama serve` running Qwen 3.6”

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) × 0 (quality) × 0.0 (none) = 0.0 of 20 max

• [github] https://github.com/ggml-org/llama.cpp“llama cli -hf ggml-org/Qwen3.5-0.8B-GGUF”
• [github] https://github.com/ggml-org/llama.cpp“llama serve -hf ggml-org/Qwen3.5-0.8B-GGUF”
• [github] https://github.com/ggml-org/llama.cpp“Plain C/C++ implementation without any dependencies”

Subscribe to events via webhooksweight 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

Connect a coding agent to this product as a working backendweight 3

3 (weight) × 4 (quality) × 0.6 (partial) = 7.2 of 30 max

• [github] https://github.com/ggml-org/llama.cpp“llama serve -hf ggml-org/Qwen3.5-0.8B-GGUF”
• [github] https://github.com/ggml-org/llama.cpp“Built-in web UI against `llama serve` running Qwen 3.6”

Explore an interactive API reference with runnable examplesweight 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

Download a machine-readable API spec (OpenAPI or equivalent)weight 2

2 (weight) × 0 (quality) × 0.0 (none) = 0.0 of 20 max

• [github] https://github.com/ggml-org/llama.cpp“llama serve -hf ggml-org/Qwen3.5-0.8B-GGUF”
• [github] https://github.com/ggml-org/llama.cpp“Built-in web UI against `llama serve` running Qwen 3.6”

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

2 (weight) × 0 (quality) × 0.0 (none) = 0.0 of 20 max

• [community] https://news.ycombinator.com/item?id=43943047“User noted it was 'really sad' when vision support was removed from llama.cpp previously, and expressed thanks that it's been restored.”

Do everything through the API that I can do in the UIweight 2

2 (weight) × 6 (quality) × 0.6 (partial) = 7.2 of 20 max

• [github] https://github.com/ggml-org/llama.cpp“llama serve -hf ggml-org/Qwen3.5-0.8B-GGUF”
• [github] https://github.com/ggml-org/llama.cpp“Built-in web UI against `llama serve` running Qwen 3.6”
• [github] https://github.com/ggml-org/llama.cpp“VLM session with `llama cli`”

Export all of my data in open formats and leaveweight 3

3 (weight) × 5 (quality) × 0.6 (partial) = 9.0 of 30 max

• [github] https://github.com/ggml-org/llama.cpp“Plain C/C++ implementation without any dependencies”
• [github] https://github.com/ggml-org/llama.cpp“1.5-bit, 2-bit, 3-bit, 4-bit, 5-bit, 6-bit, and 8-bit integer quantization for faster inference and reduced memory use”
• [github] https://github.com/ggml-org/llama.cpp“Run with Docker - see our [Docker documentation](docs/docker.md)”
• [github] https://github.com/ggml-org/llama.cpp“Download pre-built binaries from the [releases page](https://github.com/ggml-org/llama.cpp/releases)”
• [community] https://news.ycombinator.com/item?id=35100086“Praise for the minimal, dependency-free implementation: 'awesome being able to experiment with complex models without needing a billion python/c/cpp dependencies.'”
• [community] https://news.ycombinator.com/item?id=36304143“"llama.cpp is great. It started off as CPU-only solution and now looks like it wants to support any computation device it can... totally detached from Python ML ecosystem and also popular."”

Read the product's source under an open licenseweight 2

2 (weight) × 7 (quality) × 1.0 (full) = 14.0 of 20 max

• [github] https://github.com/ggml-org/llama.cpp“Contributors can open PRs - Collaborators will be invited based on contributions”
• [github] https://github.com/ggml-org/llama.cpp“Plain C/C++ implementation without any dependencies”

Self-host the core productweight 3

3 (weight) × 9 (quality) × 1.0 (full) = 27.0 of 30 max

• [github] https://github.com/ggml-org/llama.cpp“llama serve -hf ggml-org/Qwen3.5-0.8B-GGUF”
• [github] https://github.com/ggml-org/llama.cpp“Plain C/C++ implementation without any dependencies”
• [github] https://github.com/ggml-org/llama.cpp“Run with Docker - see our [Docker documentation](docs/docker.md)”
• [github] https://github.com/ggml-org/llama.cpp“Download pre-built binaries from the [releases page](https://github.com/ggml-org/llama.cpp/releases)”
• [community] https://news.ycombinator.com/item?id=35100086“User got llama.cpp working on M1 iMac trivially easily; performance was very impressive even without using Apple's neural compute hardware, and output lacked political correctness conditioning.”
• [community] https://news.ycombinator.com/item?id=35100086“Praise for the minimal, dependency-free implementation: 'awesome being able to experiment with complex models without needing a billion python/c/cpp dependencies.'”
• [community] https://news.ycombinator.com/item?id=43943047“User used llama.cpp's vision support with Gemma3 4b to generate keywords/descriptions for trip photos, including basic OCR and context clues to identify photo locations, calling it 'very nice for something self-hosted.'”

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

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

Delegate tasks to a built-in AI assistant inside the productweight 3

3 (weight) × 0 (quality) × 0.0 (none) = 0.0 of 30 max

• [github] https://github.com/ggml-org/llama.cpp“llama cli -hf ggml-org/Qwen3.5-0.8B-GGUF”
• [github] https://github.com/ggml-org/llama.cpp“llama serve -hf ggml-org/Qwen3.5-0.8B-GGUF”
• [github] https://github.com/ggml-org/llama.cpp“Built-in web UI against `llama serve` running Qwen 3.6”
• [community] https://news.ycombinator.com/item?id=43943047“User found the vision feature 'works super well' after compiling from source, using llama-mtmd-cli with quantized multimodal models like Gemma-3, loading images via '/image image.png' in chat.”
• [community] https://news.ycombinator.com/item?id=43943047“User used llama.cpp's vision support with Gemma3 4b to generate keywords/descriptions for trip photos, including basic OCR and context clues to identify photo locations, calling it 'very nice for something self-hosted.'”

Operate the product with natural-language commandsweight 2

2 (weight) × 0 (quality) × 0.0 (none) = 0.0 of 20 max

• [github] https://github.com/ggml-org/llama.cpp“llama cli -hf ggml-org/Qwen3.5-0.8B-GGUF”
• [github] https://github.com/ggml-org/llama.cpp“llama serve -hf ggml-org/Qwen3.5-0.8B-GGUF”
• [github] https://github.com/ggml-org/llama.cpp“Built-in web UI against `llama serve` running Qwen 3.6”

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

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

Schedule recurring jobs or workflowsweight 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

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