--- title: "ChatMock vs llm" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/raybytes-chatmock-vs-simonw-llm" tools: ["raybytes-chatmock", "simonw-llm"] --- # ChatMock vs llm *GraphCanon updated Sep 20, 2026* ## Verdict Pick ChatMock if chatMock offers an AI-based chat service compatible with OpenAI and Ollama APIs using Codex for response processing; pick llm if decision-critical facts for 'llm'. [ChatMock](https://github.com/RayBytes/ChatMock) reports 1.5k GitHub stars, 212 forks, and 14 open issues, last pushed Sep 1, 2026. [llm](https://llm.datasette.io) has 12k stars, 978 forks, and 689 open issues, last pushed Sep 2, 2026. Figures are from public GitHub metadata via [ChatMock's repository](https://github.com/RayBytes/ChatMock) and [llm's repository](https://github.com/simonw/llm). | | [ChatMock](/tools/raybytes-chatmock.md) | [llm](/tools/simonw-llm.md) | | --- | --- | --- | | Tagline | OpenAI & Ollama compatible API powered by Codex | Access large language models from the command-line | | Stars | 1,545 | 12,473 | | Forks | 212 | 978 | | Open issues | 14 | 689 | | Language | Python | Python | | Adopt for | ChatMock offers an AI-based chat service compatible with OpenAI and Ollama APIs using Codex for response processing. | 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._ | | [ChatMock](/tools/raybytes-chatmock.md) | [llm](/tools/simonw-llm.md) | | --- | --- | --- | | Maintenance | Active (82%) | Very active (96%) | | Days since push | 19d | 4d | | Open issues (now) | 14 | 689 | | Stars delta | +17 (30d) | +149 (30d) | | Open issues delta | +7 (30d) | +25 (30d) | | Full report | [trust report](/tools/raybytes-chatmock/trust.md) | [trust report](/tools/simonw-llm/trust.md) | ## Decision facts: ChatMock - **Pricing:** freemium - Open-source under MIT license, meaning free to use for all development phases; premium features or commercial support may apply at a later stage if introduced by the maintainers. - **Requirements:** Min 4 GB RAM; Requires Docker - **Adopt for:** ChatMock offers an AI-based chat service compatible with OpenAI and Ollama APIs using Codex for response processing. ## 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 ChatMock if… - License: ChatMock is MIT, llm is Apache-2.0. - Pricing: Open-source under MIT license, meaning free to use for all development phases; premium features or commercial support may apply at a later stage if introduced by the maintainers.. - Requirements: Min 4 GB RAM; Requires Docker. - Tags unique to ChatMock: chatgpt, codex, gpt-5, ollama. - ChatMock ships Docker support for self-hosted deployment. - Developers leveraging OpenAI or Ollama APIs looking to integrate a chat component that is powered by Codex can opt for ChatMock. ### Choose llm if… - License: llm is Apache-2.0, ChatMock 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: llms. - - 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 ChatMock - If your project specifically requires an alternative chat framework not compatible with or leveraging Codex or OpenAI/Ollama APIs, avoid using ChatMock. - Avoid this tool if you require a more diversified set of AI models not integrated within OpenAI or Ollama ecosystems, as this could limit flexibility over other tools. ## 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 ChatMock and llm? ChatMock: OpenAI & Ollama compatible API powered by Codex. llm: Access large language models from the command-line. See the comparison table for live GitHub stats and shared categories. ### When should I choose ChatMock over llm? Choose ChatMock over llm when License: ChatMock is MIT, llm is Apache-2.0; Pricing: Open-source under MIT license, meaning free to use for all development phases; premium features or commercial support may apply at a later stage if introduced by the maintainers.; Requirements: Min 4 GB RAM; Requires Docker; Tags unique to ChatMock: chatgpt, codex, gpt-5, ollama; ChatMock ships Docker support for self-hosted deployment; Developers leveraging OpenAI or Ollama APIs looking to integrate a chat component that is powered by Codex can opt for ChatMock. ### When should I choose llm over ChatMock? Choose llm over ChatMock when License: llm is Apache-2.0, ChatMock 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: llms; - 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 ChatMock? If your project specifically requires an alternative chat framework not compatible with or leveraging Codex or OpenAI/Ollama APIs, avoid using ChatMock. Avoid this tool if you require a more diversified set of AI models not integrated within OpenAI or Ollama ecosystems, as this could limit flexibility over other tools. ### 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 ChatMock or llm more popular on GitHub? llm has more GitHub stars (12,473 vs 1,545). Stars measure visibility, not whether either tool fits your constraints. ### Are ChatMock and llm open source? Yes - both are open-source projects on GitHub (ChatMock: MIT, llm: Apache-2.0). ### Where can I find alternatives to ChatMock or llm? GraphCanon lists graph-backed alternatives at [ChatMock alternatives](/tools/raybytes-chatmock/alternatives) and [llm alternatives](/tools/simonw-llm/alternatives) ([ChatMock markdown twin](/tools/raybytes-chatmock/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/raybytes-chatmock-vs-simonw-llm.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, ChatMock or llm? ChatMock: 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 ChatMock and llm? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [ChatMock trust report](/tools/raybytes-chatmock/trust); [llm trust report](/tools/simonw-llm/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=raybytes-chatmock`](/api/graphcanon/graph?tool=raybytes-chatmock) - 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/_