llama-cpp SKILL.md skillA
llama-cpp from orchestra-research/ai-research-skills is an agent skill: a SKILL.md folder an AI agent loads when a task calls for it.
mdr add orchestra-research/ai-research-skills/llama-cpp@v1.0.0Pins v1.0.0 in mdr.lock. Pin the fingerprint instead.
- Audit grade
- A, 17 of 17 checks passed
- Kind
- SKILL.md skill
- Repository
- orchestra-research/ai-research-skills
- Path
12-inference-serving/llama-cpp/SKILL.md- Versions recorded
- 5
- Latest version
- v1.0.0, committed Nov 20, 2025
- First version recorded
- Nov 9, 2025
- Size
- 5,912 bytes
- Repository stars
- 13,718
- License
- MIT
Runs LLM inference on CPU, Apple Silicon, and consumer GPUs without NVIDIA hardware. Use for edge deployment, M1/M2/M3 Macs, AMD/Intel GPUs, or when CUDA is unavailable. Supports GGUF quantization (1.5-8 bit) for reduced memory and 4-10× speedup vs PyTorch on CPU.
Collected from public GitHub. Every version is saved exactly as it was and never changes. Install it at an exact version with the mdr tool, and every file is checked before it reaches your agent. The main file is checked against the SHA-256 fingerprint recorded here, and the others against the fingerprints GitHub keeps for its source commit. The automatic checks below grade the latest version, and the same checks always give the same file the same grade.
What the file says
# llama.cpp
Pure C/C++ LLM inference with minimal dependencies, optimized for CPUs and non-NVIDIA hardware.
## When to use llama.cpp
**Use llama.cpp when:**
- Running on CPU-only machines
- Deploying on Apple Silicon (M1/M2/M3/M4)
- Using AMD or Intel GPUs (no CUDA)
- Edge deployment (Raspberry Pi, embedded systems)
- Need simple deployment without Docker/Python
**Use TensorRT-LLM instead when:**
- Have NVIDIA GPUs (A100/H100)
- Need maximum throughput (100K+ tok/s)
- Running in datacenter with CUDA
**Use vLLM instead when:**
- Have NVIDIA GPUs
- Need Python-first API
- Want PagedAttention
## Quick start
### Installation
```bash
# macOS/Linux
brew install llama.cpp
# Or build from source
git clone https://github.com/ggerganov/llama.cpp
cd llama.cpp
make
# With Metal (Apple Silicon)
make LLAMA_METAL=1
# With CUDA (NVIDIA)
make LLAMA_CUDA=1
# With ROCm (AMD)
make LLAMA_HIP=1
```
### Download model
```bash
# Download from HuggingFace (GGUF format)
huggingface-cli download \
TheBloke/Llama-2-7B-Chat-GGUF \
llama-2-7b-chat.Q4_K_M.gguf \
--local-dir models/
# Or convert from HuggingFace
python convert_hf_to_gguf.py models/llama-2-7b-chat/
```
…Read the whole file at its exact version.
How to install
mdr add orchestra-research/ai-research-skills/llama-cpp@sha256:d74caa45483f5b3cThe line at the top of this page pins the label v1.0.0, which is what most people want. This one pins the sha256 fingerprint of the contents instead, so it survives a label being moved. Either way the exact version is written to mdr.lock, and mdr install downloads and checks those contents again, so it installs them exactly or stops with an error.
[](https://markdownregistry.com/a/art_eotp3md4shdp6q2r)
1 badge image fetches in 30 days. What the badge shows.
Versions
The registry has recorded 5 versions of this file, between Nov 9, 2025 and Nov 20, 2025, about one every 3 days.
| version | committed | commit | size | audit | |
|---|---|---|---|---|---|
| v1.0.0 latest | 2025-11-20 | 0a9ded4 | 5,912 B | A | view · diff |
| v1.0.0 | 2025-11-20 | 51fc3a3 | 5,893 B | A | view · diff |
| v1.0.0 | 2025-11-20 | 81c38fe | 5,892 B | A | view · diff |
| v1.0.0 | 2025-11-19 | bd4461f | 5,891 B | A | view · diff |
| git:20251109.096b8f0 | 2025-11-09 | 096b8f0 | 5,676 B | A | view |
Audit of the latest version
- pass: Frontmatter block present
- pass: Frontmatter declares a name
- pass: Frontmatter declares a description
- pass: Size between 200 bytes and 200 KB (5912 bytes)
- pass: No zero-width or bidi control characters
- pass: No instruction hidden inside an HTML comment
- pass: No link to an exfiltration or paste host
- pass: No credential-shaped string
- pass: No instruction to send local credentials anywhere
- pass: No text hidden with inline styles
- pass: No prompt-injection phrasing
- pass: No curl or wget piped into a shell
- pass: No recursive delete of root, home or parent
- pass: No instruction to read or print local credentials
- pass: No base64 blob over 200 characters
- pass: No link to a raw IP address
- pass: No script tag
Source
orchestra-research/ai-research-skills · 13,718 stars · license MIT · pushed 2026-10-11 · branch main
API
GET https://markdownregistry.com/api/v1/artifacts/art_eotp3md4shdp6q2r GET https://markdownregistry.com/api/v1/resolve?ref=orchestra-research/ai-research-skills/llama-cpp GET https://markdownregistry.com/api/v1/blob/d74caa45483f5b3c6bd6267e39b444627989ff90fdb84b6c2e7c3da4ddf143ef
Your AI assistant does the legwork. You hear about the deals worth your word. Hand yours the standing instructions at modelranch.com and it joins the network that reads files like this one.
Guides: the SKILL.md format and its required fields · what to check before you install a skill · how to pin a skill to an exact version · where to find agent skills · keeping a team on the same skills · which agent file does what.
More from orchestra-research/ai-research-skills
Every file in orchestra-research/ai-research-skills