magnus919_agent-skills/llama-cpp/references/source-index.md

Source index

Research checked 2026-07-25 against llama.cpp commit 555881ebc8b0fc0402b30e09258a32a7bfd13c52, immediately after release b10107. Links to master, generated command help, changelog issues, package repositories, and Hugging Face remain live sources and must be rechecked before relying on current flags, defaults, routes, or artifacts.

Coverage matrix

Requested dimension	Primary evidence	Skill reference	Status
Packages, releases, Docker, source builds	Install, build, Docker docs and releases	installation-and-backends.md	Covered with host-specific discovery
CPU, Metal, CUDA, HIP, Vulkan, SYCL	README backend table, build/backend guides, generated help	installation-and-backends.md	Covered; exact device support remains a task input
GGUF, provenance, conversion, quantization, imatrix	GGUF specification, quantize and imatrix docs, HF model cards	models-gguf-and-memory.md	Covered without a universal quant recommendation
Memory, context, cache, offload	Generated CLI/server help, model metadata, load logs, multi-GPU guide	models-gguf-and-memory.md, performance-and-benchmarking.md	Covered by measured procedure, not a fixed formula
CLI inference and chat templates	README quick start, generated CLI help, template and function docs	inference-and-serving.md	Covered with installed-help refresh gate
Server and OpenAI-compatible routes	Server README, tests, REST changelog	inference-and-serving.md	Covered; exact client contract must be tested
Structured output, embeddings, reranking, tools	Server README and function-calling docs	inference-and-serving.md	Covered with model/capability checks
Benchmarking and quality	llama-bench, server bench, perplexity docs	performance-and-benchmarking.md	Covered with matched-comparison contract
Multi-GPU	Current multi-GPU guide and generated help	performance-and-benchmarking.md, troubleshooting.md	Covered; experimental tensor support must be refreshed
Failure diagnosis	Build/server/multi-GPU docs, changelog, startup evidence	troubleshooting.md	Covered by symptom routing

Primary llama.cpp sources

Area	Source	Claims used
Project scope, quick start, backends, tools	README at reviewed commit	Supported operating surfaces, model acquisition, primary binaries
Pre-built installation	Install guide	Package-manager matrix and distributor boundaries
Source build and backends	Build guide	CMake paths, backend selection, multi-backend/device discovery
Containers	Docker guide	Image families, host driver and passthrough requirements
CLI interface	Generated CLI documentation	Current flags and defaults; generated and volatile
Server interface	Server documentation	Readiness, APIs, auth/TLS, capabilities, generated flags
REST changes	REST API changelog	Upgrade-sensitive route, response, default, and environment changes
Multi-GPU	Multi-GPU guide	Split-mode status, fit/cache constraints, troubleshooting
Quantization	Quantize guide	Conversion/quantization phases, requantization warning, example data
Importance matrices	Imatrix guide	Calibration inputs, outputs, statistics, quantization use
Model performance	llama-bench guide	pp/tg/pg methodology, repetitions, structured outputs, exclusions
Service performance	Server benchmark guide	Concurrent request benchmark and client/server metrics
Quant quality	Perplexity guide	Same-model comparison, uncertainty, KL, cross-model limits
Templates and tools	Function-calling guide	Template/handler coupling, props/log verification, cache-quality warning
Template provenance	Template maintenance	Model-source template acquisition

Format and model provenance sources

Area	Source	Claims used
GGUF format and metadata	GGUF specification	Extensibility, mmap, architecture, context, license/source/base-model and template metadata
Model cards	Hugging Face model cards	License, base-model lineage, intended use, limitations, datasets, evaluation
Reproducible downloads	Hugging Face download guide	Exact revisions, file filtering, caching, CLI dry runs

Source evaluation

The operational claims above are primarily Tier 1 official documentation, generated help, specifications, tests, and project changelogs. Upstream examples establish supported command shapes, not performance guarantees for other hardware or models. No local llama.cpp binary or model was available during skill authoring, so commands were source-verified but not represented as locally executed runtime evidence.

Refresh rules

Recheck the installed help and upstream sources when any of these change:

• llama.cpp build/release, binary name, package, or container image;
• backend SDK, driver, GPU architecture, build target, or device topology;
• model revision, GGUF metadata/version, quantization, sidecar, template, or license;
• REST route, stream/error schema, environment variable, authentication, CORS, or default bind behavior;
• context, cache, fit, batch, offload, split-mode, or speculative-decoding default;
• benchmark tool output/schema or measurement boundary.

Always recheck external-exposure and built-in-tool security options immediately before enabling them.