Local AI coding agents
Coding agents you can point at a model on your own computer, so prompts and code can stay on your machine and there is no per-token bill.
By weekly package downloads, the leaders are OpenAI Codex (25.6M), Pi (5.2M), mini-SWE-agent (3.4M). By VS Code extension installs, the leaders are GitHub Copilot (78.6M), OpenAI Codex (15.2M), Cline (5.5M). By GitHub stars, the leaders are OpenCode (212K), OpenAI Codex (128K), Pi (113K). The fastest grower over the last 30 days is Pi, with downloads up 52%. As of Oct 6, 2026.
| # | Agent | Category | Pulse | Downloads 7d | 7d | 30d | VS Code installs | Stars | Latest release | Price | Last 90 days |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 |
OpenAI CodexOpenAI |
Terminal | 82 | 25.6M | up 5.7% | up 21.2% | 15.2M | 128K+153/day | 0.160.1yesterday | Free + $8/mo | |
| 5 |
PiEarendil Inc. (created by Mario Zechner) |
Terminal | 75 | 5.2M | up 29.8% | up 52.1% | — | 113K+378/day | 1.0.4yesterday | Free (OSS) | |
| 7 |
OpenCodeAnomaly (SST team) |
Terminal | 73 | 3.3M | up 22.0% | up 6.1% | 1.2M | 212K+200/day | 1.18.346d ago | Free + $10/mo | |
| 9 |
GitHub CopilotGitHub (Microsoft) |
IDEs | 70 | — | — | — | 78.6M | — | — | Free + $10/mo | |
| 19 |
ZedZed Industries |
IDEs | 59 | — | — | — | — | 91.3K+54/day | 1.22.06d ago | Free + $10/mo | |
| 34 |
ClineCline Bot Inc. |
Terminal | 52 | 95K | up 10.1% | down 37.2% | 5.5M | 69.9K+63/day | 0.0.434d ago | Free + $9.99/mo | |
| 36 |
JunieJetBrains |
IDEs | 51 | 318 | down 58.6% | — | — | 469+1/day | 3651.1yesterday | Free + $10/mo | |
| 40 |
OpenHandsOpenHands (formerly All Hands AI) |
Terminal | 50 | 316K | — | — | — | 90.1K+98/day | 1.25.0today | Free | |
| 48 |
mini-SWE-agentPrinceton University & Stanford University (SWE-agent team) |
Terminal | 47 | 3.4M | up 58.9% | down 26.3% | — | 8,225+23/day | 2.4.62mo ago | Free (OSS) | |
| 51 |
Kilo CodeKilo Code (Anaconda) |
Terminal | 46 | 32.8K | down 32.4% | — | 1.6M | 27.5K+15/day | 7.8.35d ago | Free + $19/mo | |
| 52 |
GitHub Copilot CLIGitHub (Microsoft) |
Terminal | 46 | 1.7M | up 19.1% | down 36.3% | — | 11.2K+5/day | 1.0.92yesterday | Free + $10/mo | |
| 58 |
GooseBlock (now Agentic AI Foundation) |
Terminal | 43 | — | — | — | 7,358 | 55K+38/day | 1.53.04d ago | Free (OSS) | |
| 65 |
Qwen CodeAlibaba Cloud (Qwen) |
Terminal | 41 | 105K | up 30.8% | up 5.5% | 373K | 28.3K+20/day | 0.25.0yesterday | Bring your key | |
| 84 |
AiderAider-AI (Paul Gauthier) |
Terminal | 34 | 61.3K | down 1.5% | down 57.8% | — | 49.4K+23/day | 0.86.014mo ago | Free (OSS) | |
| 88 |
Mistral VibeMistral AI |
Terminal | 34 | 488K | down 30.9% | down 60.1% | 40.8K | 5,050+5/day | 2.25.813d ago | Free + $14.99/mo | |
| 90 |
CrushCharm |
Terminal | 33 | 7,773 | down 10.6% | — | — | 28.5K+25/day | 0.97.17d ago | Free | |
| 107 |
Open InterpreterOpen Interpreter (openinterpreter.com) |
Terminal | 26 | — | — | — | — | 68.5K+12/day | 0.0.556d ago | Free (OSS) | |
| No agents match that filter. | |||||||||||
Ranks are overall positions by Pulse Score. Click a column to sort by what matters to you. Methodology.
How each agent connects to a local model
Only agents whose own documentation describes a local setup are listed; each link goes to that page. Checked Oct 6, 2026.
| Agent | How it connects | Setup docs |
|---|---|---|
| OpenAI Codex | --oss mode with Ollama or LM Studio |
official docs |
| Pi | llama.cpp, Ollama, LM Studio and vLLM via a custom base URL | official docs |
| OpenCode | Ollama, LM Studio, llama.cpp or any OpenAI-compatible local server | official docs |
| GitHub Copilot | VS Code bring-your-own-model with the Ollama extension | official docs |
| Zed | Ollama, LM Studio, llama.cpp and other local OpenAI-compatible servers | official docs |
| Cline | Ollama and LM Studio providers | official docs |
| Junie | Junie CLI with LM Studio or Ollama | official docs |
| OpenHands | LM Studio, Ollama, vLLM and SGLang | official docs |
| mini-SWE-agent | Local servers such as vLLM through LiteLLM | official docs |
| Kilo Code | Ollama and LM Studio providers | official docs |
| GitHub Copilot CLI | Bring your own model: Ollama, vLLM, Foundry Local or any OpenAI-compatible endpoint | official docs |
| Goose | Ollama, Docker Model Runner and Ramalama providers | official docs |
| Qwen Code | Ollama or vLLM through an OpenAI-compatible provider | official docs |
| Aider | Ollama, or any OpenAI-compatible local server | official docs |
| Mistral Vibe | Any OpenAI-compatible local server (vLLM, llama.cpp, LM Studio, Ollama) | official docs |
| Crush | Auto-discovers Ollama, LM Studio and llama.cpp servers | official docs |
| Open Interpreter | Built-in Ollama and LM Studio providers | official docs |
Why run a coding agent locally
Privacy. With a local model, your code and prompts are not sent to a model provider. (Check the agent's own telemetry settings too.) That matters for client code, regulated work, or a company policy that forbids sending source to third parties.
Cost. There is no per-token bill. You pay once, in hardware, and in electricity.
Offline work. Once the model is downloaded, open-source agents can keep working without a connection. Extensions of commercial products may still need you to be signed in.
What to expect
Local models are smaller than the frontier models behind commercial agents, and coding agents are demanding: they read many files, keep a long context and call tools in loops. In practice that means:
- Hardware decides what you can run. A laptop with 16 GB of memory runs small models that can handle simple edits and explanations. Models that can drive a multi-step agent loop reliably need much more memory, typically a workstation GPU or a recent Mac with a large amount of unified memory.
- Context length matters as much as model size. Local servers often start with a short default context window; agents need a long one to see enough of the codebase. Check your server's context setting before judging a model.
- Tool calling must be supported by the model and the server, or the agent cannot run commands or edit files.
A common setup is hybrid: a local model for routine or sensitive work, a hosted model for the hard tasks. Agents that let you switch models mid-session make that easy.
Agents that do not run locally
Some popular agents work only with their vendor's hosted models, or reach a model on your machine only through a public tunnel. For example, Claude Code documents that it does not route to non-Claude models, and Gemini CLI connects only to Google's backends. Their pages on this site list which models they support.
Questions about local AI coding agents
Which AI coding agents can run with a local model?
17 agents tracked here document local-model support, including OpenAI Codex, Pi, OpenCode, GitHub Copilot, Zed. Most connect through Ollama, LM Studio or another OpenAI-compatible server running on your machine.
Is a local coding agent completely free?
The open-source agents are free to install, and a local model has no per-token cost. You still need hardware capable of running a useful model, and some agents (such as editor extensions of commercial products) may require an account or plan for other features.
Can Claude Code or Cursor use a local model?
Not as a documented local setup. Claude Code's documentation says it does not route to non-Claude models. For Cursor, staff on its official forum explain that requests go through Cursor's servers, so a model on your machine would need a public HTTPS tunnel.