--- title: "chatllm.cpp vs llm" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/foldl-chatllm-cpp-vs-simonw-llm" tools: ["foldl-chatllm-cpp", "simonw-llm"] --- # chatllm.cpp vs llm *GraphCanon updated Aug 25, 2026* ## Verdict Pick chatllm.cpp if this C++ library aims to deploy language models for real-time chatting on local systems with support for CPU and GPU; pick llm if decision-critical facts for 'llm'. [chatllm.cpp](https://github.com/foldl/chatllm.cpp) reports 917 GitHub stars, 72 forks, and 11 open issues, last pushed Aug 22, 2026. [llm](https://llm.datasette.io) has 12k stars, 939 forks, and 664 open issues, last pushed Aug 5, 2026. Figures are from public GitHub metadata via [chatllm.cpp's repository](https://github.com/foldl/chatllm.cpp) and [llm's repository](https://github.com/simonw/llm). | | [chatllm.cpp](/tools/foldl-chatllm-cpp.md) | [llm](/tools/simonw-llm.md) | | --- | --- | --- | | Tagline | C++ real-time chat models for CPU and GPU | Access large language models from the command-line | | Stars | 917 | 12,324 | | Forks | 72 | 939 | | Open issues | 11 | 664 | | Language | C++ | Python | | Adopt for | This C++ library aims to deploy language models for real-time chatting on local systems with support for CPU and GPU. | Decision-critical facts for 'llm' | | Persona | - | - | | Runtime | - | - | | License | MIT | Apache-2.0 | | Categories | Inference & Serving, LLM Frameworks | Inference & Serving, LLM Frameworks | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [chatllm.cpp](/tools/foldl-chatllm-cpp.md) | [llm](/tools/simonw-llm.md) | | --- | --- | --- | | Open issues (now) | 11 | 664 | | Stars delta | +5 (30d) | Unknown | | Open issues delta | 0 (30d) | Unknown | | Full report | [trust report](/tools/foldl-chatllm-cpp/trust.md) | [trust report](/tools/simonw-llm/trust.md) | ## Shared compatibility - **Python**: [chatllm.cpp](/tools/foldl-chatllm-cpp.md) - Python runtime; [llm](/tools/simonw-llm.md) - Python runtime ## Decision facts: chatllm.cpp - **Adopt for:** This C++ library aims to deploy language models for real-time chatting on local systems with support for CPU and GPU. ## Decision facts: llm - **Requirements:** - Installation supports multiple methods including `pip`, Homebrew (with caveats noted), `pipx`, and `uv`.; - Requires an OpenAI API key for certain functionalities. - **Adopt for:** Decision-critical facts for 'llm' - **License detail:** Apache-2.0 ## Choose when ### Choose chatllm.cpp if… - chatllm.cpp is primarily C++; llm is Python. - License: chatllm.cpp is MIT, llm is Apache-2.0. - Tags unique to chatllm.cpp: cpu-support, gpu-support, llm, llm-inference. - When you need a C++ framework that can integrate tightly into existing C++ applications requiring fast chat responses. ### Choose llm if… - llm is primarily Python; chatllm.cpp is C++. - License: llm is Apache-2.0, chatllm.cpp is MIT. - Requirements: - Installation supports multiple methods including `pip`, Homebrew (with caveats noted), `pipx`, and `uv`.; - Requires an OpenAI API key for certain functionalities.. - Tags unique to llm: ai, llms, openai. - - You prioritize command-line interaction over graphical interfaces, as llm is designed to provide a seamless CLI experience with multiple installation methods. ## When NOT to use chatllm.cpp - Avoid if your preferred development environment is centered around high-level languages such as Python, where alternatives like Transformers are robust and well-supported. - Not suitable for projects that require a wide array of pre-trained models not provided by chatllm.cpp itself, since it does not include model training functionalities. ## When NOT to use llm - - If you require real-time visual feedback or a graphical interface for interacting with language models, as llm is strictly command-line-based. - - If your primary focus is on model training rather than inference or serving, since llm is aimed at accessing and using pre-trained models. ## Common questions ### What is the difference between chatllm.cpp and llm? chatllm.cpp: C++ real-time chat models for CPU and GPU. llm: Access large language models from the command-line. See the comparison table for live GitHub stats and shared categories. ### When should I choose chatllm.cpp over llm? Choose chatllm.cpp over llm when chatllm.cpp is primarily C++; llm is Python; License: chatllm.cpp is MIT, llm is Apache-2.0; Tags unique to chatllm.cpp: cpu-support, gpu-support, llm, llm-inference; When you need a C++ framework that can integrate tightly into existing C++ applications requiring fast chat responses. ### When should I choose llm over chatllm.cpp? Choose llm over chatllm.cpp when llm is primarily Python; chatllm.cpp is C++; License: llm is Apache-2.0, chatllm.cpp is MIT; Requirements: - Installation supports multiple methods including `pip`, Homebrew (with caveats noted), `pipx`, and `uv`.; - Requires an OpenAI API key for certain functionalities.; Tags unique to llm: ai, llms, openai; - You prioritize command-line interaction over graphical interfaces, as llm is designed to provide a seamless CLI experience with multiple installation methods. ### When should I avoid chatllm.cpp? Avoid if your preferred development environment is centered around high-level languages such as Python, where alternatives like Transformers are robust and well-supported. Not suitable for projects that require a wide array of pre-trained models not provided by chatllm.cpp itself, since it does not include model training functionalities. ### When should I avoid llm? - If you require real-time visual feedback or a graphical interface for interacting with language models, as llm is strictly command-line-based. - If your primary focus is on model training rather than inference or serving, since llm is aimed at accessing and using pre-trained models. ### Is chatllm.cpp or llm more popular on GitHub? llm has more GitHub stars (12,324 vs 917). Stars measure visibility, not whether either tool fits your constraints. ### Are chatllm.cpp and llm open source? Yes - both are open-source projects on GitHub (chatllm.cpp: MIT, llm: Apache-2.0). ### Where can I find alternatives to chatllm.cpp or llm? GraphCanon lists graph-backed alternatives at [chatllm.cpp alternatives](/tools/foldl-chatllm-cpp/alternatives) and [llm alternatives](/tools/simonw-llm/alternatives) ([chatllm.cpp markdown twin](/tools/foldl-chatllm-cpp/alternatives.md), [llm markdown twin](/tools/simonw-llm/alternatives.md)), ranked by typed relationship edges rather than popularity votes. ### Is there a machine-readable version of this comparison? Yes. The markdown twin at [this comparison](/compare/foldl-chatllm-cpp-vs-simonw-llm.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, chatllm.cpp or llm? chatllm.cpp: Very active. llm: Very active. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance. ### Where are the full trust reports for chatllm.cpp and llm? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [chatllm.cpp trust report](/tools/foldl-chatllm-cpp/trust); [llm trust report](/tools/simonw-llm/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=foldl-chatllm-cpp`](/api/graphcanon/graph?tool=foldl-chatllm-cpp) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_