--- title: "whichllm vs code-server" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/andyyyy64-whichllm-vs-coder-code-server" tools: ["andyyyy64-whichllm", "coder-code-server"] --- # whichllm vs code-server *GraphCanon updated Jul 15, 2026* ## Verdict Pick whichllm when whichllm is primarily Python; code-server is TypeScript; pick code-server when code-server is primarily TypeScript; whichllm is Python. [whichllm](https://github.com/Andyyyy64/whichllm) reports 5.8k GitHub stars, 309 forks, and 16 open issues, last pushed Jul 8, 2026. [code-server](https://coder.com) has 78k stars, 6.7k forks, and 157 open issues, last pushed Jul 11, 2026. Figures are from public GitHub metadata via [whichllm's repository](https://github.com/Andyyyy64/whichllm) and [code-server's repository](https://github.com/coder/code-server). | | [whichllm](/tools/andyyyy64-whichllm.md) | [code-server](/tools/coder-code-server.md) | | --- | --- | --- | | Tagline | Find the local LLM that actually runs and performs best on your hardware. Ranked by real, recency-aware benchmarks, not parameter count. One command, run it instantly. | VS Code in the browser | | Stars | 5,812 | 78,364 | | Forks | 309 | 6,748 | | Open issues | 16 | 157 | | Language | Python | TypeScript | | Adopt for | - | - | | Persona | - | - | | Runtime | - | - | | License | MIT | MIT | | Categories | Developer Tools, Inference & Serving, LLM Frameworks | Developer Tools, Inference & Serving | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [whichllm](/tools/andyyyy64-whichllm.md) | [code-server](/tools/coder-code-server.md) | | --- | --- | --- | | Days since push | 6d | 0d | | Open issues (now) | 16 | 157 | | Owner type | User | Organization | | Full report | [trust report](/tools/andyyyy64-whichllm/trust.md) | [trust report](/tools/coder-code-server/trust.md) | ## Choose when ### Choose whichllm if… - whichllm is primarily Python; code-server is TypeScript. - Tags unique to whichllm: ai, apple-silicon, benchmarks, cli. - Also covers LLM Frameworks. ### Choose code-server if… - code-server is primarily TypeScript; whichllm is Python. - Tags unique to code-server: browser-ide, dev-tools, development-environment, ide. - More GitHub stars (78k vs 5.8k) - visibility, not fit. ## When NOT to use whichllm - Developer Tools: A gateway is overkill when you're pinned to a single provider and model. - Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. - LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. ## When NOT to use code-server - Developer Tools: A gateway is overkill when you're pinned to a single provider and model. - Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. ## Common questions ### What is the difference between whichllm and code-server? whichllm: Find the local LLM that actually runs and performs best on your hardware. Ranked by real, recency-aware benchmarks, not parameter count. One command, run it instantly.. code-server: VS Code in the browser. See the comparison table for live GitHub stats and shared categories. ### When should I choose whichllm over code-server? Choose whichllm over code-server when whichllm is primarily Python; code-server is TypeScript; Tags unique to whichllm: ai, apple-silicon, benchmarks, cli; Also covers LLM Frameworks. ### When should I choose code-server over whichllm? Choose code-server over whichllm when code-server is primarily TypeScript; whichllm is Python; Tags unique to code-server: browser-ide, dev-tools, development-environment, ide; More GitHub stars (78k vs 5.8k) - visibility, not fit. ### When should I avoid whichllm? Developer Tools: A gateway is overkill when you're pinned to a single provider and model. Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. ### When should I avoid code-server? Developer Tools: A gateway is overkill when you're pinned to a single provider and model. Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. ### Is whichllm or code-server more popular on GitHub? code-server has more GitHub stars (78,364 vs 5,812). Stars measure visibility, not whether either tool fits your constraints. ### Are whichllm and code-server open source? Yes - both are open-source projects on GitHub (whichllm: MIT, code-server: MIT). ### Where can I find alternatives to whichllm or code-server? GraphCanon lists graph-backed alternatives at [whichllm alternatives](/tools/andyyyy64-whichllm/alternatives) and [code-server alternatives](/tools/coder-code-server/alternatives) ([whichllm markdown twin](/tools/andyyyy64-whichllm/alternatives.md), [code-server markdown twin](/tools/coder-code-server/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/andyyyy64-whichllm-vs-coder-code-server.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, whichllm or code-server? whichllm: Very active. code-server: 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 whichllm and code-server? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [whichllm trust report](/tools/andyyyy64-whichllm/trust); [code-server trust report](/tools/coder-code-server/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=andyyyy64-whichllm`](/api/graphcanon/graph?tool=andyyyy64-whichllm) - 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/_