--- title: "OfflineLLM vs ChatMock" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/jegly-offlinellm-vs-raybytes-chatmock" tools: ["jegly-offlinellm", "raybytes-chatmock"] --- # OfflineLLM vs ChatMock *GraphCanon updated Sep 20, 2026* ## Verdict Pick OfflineLLM if offlineLLM provides private on-device AI chat for Android with ARM-optimised llama.cpp support, ideal for scenarios requiring privacy and offline capabilities; pick ChatMock if chatMock offers an AI-based chat service compatible with OpenAI and Ollama APIs using Codex for response processing. [OfflineLLM](https://jegly.xyz) reports 240 GitHub stars, 23 forks, and 7 open issues, last pushed Aug 18, 2026. [ChatMock](https://github.com/RayBytes/ChatMock) has 1.5k stars, 212 forks, and 14 open issues, last pushed Sep 1, 2026. Figures are from public GitHub metadata via [OfflineLLM's repository](https://github.com/jegly/OfflineLLM) and [ChatMock's repository](https://github.com/RayBytes/ChatMock). | | [OfflineLLM](/tools/jegly-offlinellm.md) | [ChatMock](/tools/raybytes-chatmock.md) | | --- | --- | --- | | Tagline | Private on-device AI chat for Android with local LLM support via ARM-optimised llama.cpp | OpenAI & Ollama compatible API powered by Codex | | Stars | 240 | 1,545 | | Forks | 23 | 212 | | Open issues | 7 | 14 | | Language | Kotlin | Python | | Adopt for | OfflineLLM provides private on-device AI chat for Android with ARM-optimised llama.cpp support, ideal for scenarios requiring privacy and offline capabilities. | ChatMock offers an AI-based chat service compatible with OpenAI and Ollama APIs using Codex for response processing. | | Persona | - | - | | Runtime | - | - | | License | Other | MIT | | Categories | Inference & Serving, LLM Frameworks | Inference & Serving, LLM Frameworks | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [OfflineLLM](/tools/jegly-offlinellm.md) | [ChatMock](/tools/raybytes-chatmock.md) | | --- | --- | --- | | Maintenance | Steady (60%) | Active (82%) | | Days since push | 32d | 19d | | Open issues (now) | 7 | 14 | | Stars delta | +36 (30d) | +17 (30d) | | Full report | [trust report](/tools/jegly-offlinellm/trust.md) | [trust report](/tools/raybytes-chatmock/trust.md) | ## Decision facts: OfflineLLM - **Adopt for:** OfflineLLM provides private on-device AI chat for Android with ARM-optimised llama.cpp support, ideal for scenarios requiring privacy and offline capabilities. ## 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. ## Choose when ### Choose OfflineLLM if… - OfflineLLM is primarily Kotlin; ChatMock is Python. - License: OfflineLLM is Other, ChatMock is MIT. - Tags unique to OfflineLLM: android, local-llm, on-device-ai, privacy-first-ai. - Need a privacy-first solution that operates fully offline ### Choose ChatMock if… - ChatMock is primarily Python; OfflineLLM is Kotlin. - License: ChatMock is MIT, OfflineLLM is Other. - 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: ai, chatgpt, codex, gpt-5. - 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 NOT to use OfflineLLM - Seeking real-time updates or cloud-based AI services - Prioritize integration with web-based features or platforms - Running x86 architecture, as the tool is optimised for ARM ## 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. ## Common questions ### What is the difference between OfflineLLM and ChatMock? OfflineLLM: Private on-device AI chat for Android with local LLM support via ARM-optimised llama.cpp. ChatMock: OpenAI & Ollama compatible API powered by Codex. See the comparison table for live GitHub stats and shared categories. ### When should I choose OfflineLLM over ChatMock? Choose OfflineLLM over ChatMock when OfflineLLM is primarily Kotlin; ChatMock is Python; License: OfflineLLM is Other, ChatMock is MIT; Tags unique to OfflineLLM: android, local-llm, on-device-ai, privacy-first-ai; Need a privacy-first solution that operates fully offline. ### When should I choose ChatMock over OfflineLLM? Choose ChatMock over OfflineLLM when ChatMock is primarily Python; OfflineLLM is Kotlin; License: ChatMock is MIT, OfflineLLM is Other; 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: ai, chatgpt, codex, gpt-5; 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 avoid OfflineLLM? Seeking real-time updates or cloud-based AI services Prioritize integration with web-based features or platforms Running x86 architecture, as the tool is optimised for ARM ### 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. ### Is OfflineLLM or ChatMock more popular on GitHub? ChatMock has more GitHub stars (1,545 vs 240). Stars measure visibility, not whether either tool fits your constraints. ### Are OfflineLLM and ChatMock open source? Yes - both are open-source projects on GitHub (OfflineLLM: Other, ChatMock: MIT). ### Where can I find alternatives to OfflineLLM or ChatMock? GraphCanon lists graph-backed alternatives at [OfflineLLM alternatives](/tools/jegly-offlinellm/alternatives) and [ChatMock alternatives](/tools/raybytes-chatmock/alternatives) ([OfflineLLM markdown twin](/tools/jegly-offlinellm/alternatives.md), [ChatMock markdown twin](/tools/raybytes-chatmock/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/jegly-offlinellm-vs-raybytes-chatmock.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, OfflineLLM or ChatMock? OfflineLLM: Steady. ChatMock: 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 OfflineLLM and ChatMock? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [OfflineLLM trust report](/tools/jegly-offlinellm/trust); [ChatMock trust report](/tools/raybytes-chatmock/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=jegly-offlinellm`](/api/graphcanon/graph?tool=jegly-offlinellm) - 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/_