--- title: "claude-code-local vs llm" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/nicedreamzapp-claude-code-local-vs-simonw-llm" tools: ["nicedreamzapp-claude-code-local", "simonw-llm"] --- # claude-code-local vs llm *GraphCanon updated Sep 20, 2026* ## Verdict Pick claude-code-local if claude-code-local offers an MLX-native Anthropic-API server and support for running large models locally on Apple Silicon with high token throughput and privacy guarantees; pick llm if decision-critical facts for 'llm'. [claude-code-local](https://www.youtube.com/@nicedreamzapps) reports 3.3k GitHub stars, 627 forks, and 2 open issues, last pushed Sep 19, 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 [claude-code-local's repository](https://github.com/nicedreamzapp/claude-code-local) and [llm's repository](https://github.com/simonw/llm). | | [claude-code-local](/tools/nicedreamzapp-claude-code-local.md) | [llm](/tools/simonw-llm.md) | | --- | --- | --- | | Tagline | Run Claude Code on-device using local AI models for privacy-sensitive workflows. | Access large language models from the command-line | | Stars | 3,321 | 12,473 | | Forks | 627 | 978 | | Open issues | 2 | 689 | | Language | Python | Python | | Adopt for | claude-code-local offers an MLX-native Anthropic-API server and support for running large models locally on Apple Silicon with high token throughput and privacy guarantees. | 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._ | | [claude-code-local](/tools/nicedreamzapp-claude-code-local.md) | [llm](/tools/simonw-llm.md) | | --- | --- | --- | | Days since push | 0d | 4d | | Open issues (now) | 2 | 689 | | Stars delta | +128 (30d) | +149 (30d) | | Open issues delta | +1 (30d) | +25 (30d) | | Full report | [trust report](/tools/nicedreamzapp-claude-code-local/trust.md) | [trust report](/tools/simonw-llm/trust.md) | ## Decision facts: claude-code-local - **Pricing:** freemium - Free to use under the MIT license; premium support or features may incur costs not detailed in the repository. - **Requirements:** - Needs Apple Silicon hardware.; - Compatible with Python. - **Adopt for:** claude-code-local offers an MLX-native Anthropic-API server and support for running large models locally on Apple Silicon with high token throughput and privacy guarantees. ## 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 claude-code-local if… - License: claude-code-local is MIT, llm is Apache-2.0. - Pricing: Free to use under the MIT license; premium support or features may incur costs not detailed in the repository.. - Requirements: - Needs Apple Silicon hardware.; - Compatible with Python.. - Tags unique to claude-code-local: ai-privacy, airgap, anthropic-api, apple-silicon. - - You need to conduct NDA, legal or healthcare projects that require strict data privacy and airgapping. ### Choose llm if… - License: llm is Apache-2.0, claude-code-local 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 claude-code-local - - If you are not working within the Apple ecosystem as it primarily supports devices running Apple Silicon. - - For workflows where real-time collaboration and cloud-sharing features are integral to your operations, as claude-code-local focuses on local execution. ## 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 claude-code-local and llm? claude-code-local: Run Claude Code on-device using local AI models for privacy-sensitive workflows.. llm: Access large language models from the command-line. See the comparison table for live GitHub stats and shared categories. ### When should I choose claude-code-local over llm? Choose claude-code-local over llm when License: claude-code-local is MIT, llm is Apache-2.0; Pricing: Free to use under the MIT license; premium support or features may incur costs not detailed in the repository.; Requirements: - Needs Apple Silicon hardware.; - Compatible with Python.; Tags unique to claude-code-local: ai-privacy, airgap, anthropic-api, apple-silicon; - You need to conduct NDA, legal or healthcare projects that require strict data privacy and airgapping. ### When should I choose llm over claude-code-local? Choose llm over claude-code-local when License: llm is Apache-2.0, claude-code-local 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 claude-code-local? - If you are not working within the Apple ecosystem as it primarily supports devices running Apple Silicon. - For workflows where real-time collaboration and cloud-sharing features are integral to your operations, as claude-code-local focuses on local execution. ### 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 claude-code-local or llm more popular on GitHub? llm has more GitHub stars (12,473 vs 3,321). Stars measure visibility, not whether either tool fits your constraints. ### Are claude-code-local and llm open source? Yes - both are open-source projects on GitHub (claude-code-local: MIT, llm: Apache-2.0). ### Where can I find alternatives to claude-code-local or llm? GraphCanon lists graph-backed alternatives at [claude-code-local alternatives](/tools/nicedreamzapp-claude-code-local/alternatives) and [llm alternatives](/tools/simonw-llm/alternatives) ([claude-code-local markdown twin](/tools/nicedreamzapp-claude-code-local/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/nicedreamzapp-claude-code-local-vs-simonw-llm.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, claude-code-local or llm? claude-code-local: 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 claude-code-local and llm? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [claude-code-local trust report](/tools/nicedreamzapp-claude-code-local/trust); [llm trust report](/tools/simonw-llm/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=nicedreamzapp-claude-code-local`](/api/graphcanon/graph?tool=nicedreamzapp-claude-code-local) - 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/_