CodebuffAI/freebuffPublic

The free coding agent

AI summary: A suite of free, multi-agent AI tools for coding, building, and research using leading models like DeepSeek and Claude.

Stars
13.7K
+46 today
Forks
1.5K
Watchers
79
Open issues
172
Open PRs
86
Contributors
~36
Commits
12.4K
Branches
109

TypeScriptApache-2.0Created Jul 9, 2024Last push 1d ago+142 stars this week+1.2K this month

Quick answers

What is freebuff?
A suite of free, multi-agent AI tools for coding, building, and research using leading models like DeepSeek and Claude.
What does freebuff do?
Freebuff is a collection of five specialized AI tools (Desktop, CLI, Web, Cloud, and Chat) designed to provide free access to advanced coding and research agents. It leverages the Codebuff multi-agent framework to handle complex tasks by splitting them into specialized roles: gathering context, planning, executing code, and reviewing the results. Users can choose from a curated catalog of high-tier models, including GPT-5.6 Luna and DeepSeek V4 Pro, without subscriptions or API keys (supported by text ads). The platform supports parallel local agent workspaces on desktop, terminal-based codebase editing, and hosted sandbox environments for building full-stack applications.
Who is freebuff for?
Developers, researchers, and students seeking free access to high-tier AI models and multi-agent workflows. It is built for users who want powerful, autonomous coding assistants across their terminal, desktop, and web environments without subscription lock-in.
How do I get started with freebuff?
npm install -g freebuff && freebuff
How popular is freebuff on GitHub?
CodebuffAI/freebuff has 13,717 stars and 1,455 forks on GitHub, and gained 142 stars in the last 7 days.
What license does freebuff use?
CodebuffAI/freebuff is released under the Apache-2.0 license.

Star history

since Aug 20, 2026
05K10KAug 2026Sep 2026Oct 2026Oct 2026
13.7K stars as of Oct 24, 2026. Measured daily since Aug 20, 2026; GitHub no longer exposes earlier star timestamps.

Contribution activity

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8,991 commits in the last yearLessMore

Signals and awards

derived from tracked data
  • Widely adopted

    13,717 stars

  • Very active

    8,991 commits in 52 weeks

  • Permissive license

    Apache-2.0

  • Continuous integration

    Automated checks passing

  • Repeat trending

    5 trending appearances

What freebuff does

Freebuff is a collection of five specialized AI tools (Desktop, CLI, Web, Cloud, and Chat) designed to provide free access to advanced coding and research agents. It leverages the Codebuff multi-agent framework to handle complex tasks by splitting them into specialized roles: gathering context, planning, executing code, and reviewing the results. Users can choose from a curated catalog of high-tier models, including GPT-5.6 Luna and DeepSeek V4 Pro, without subscriptions or API keys (supported by text ads). The platform supports parallel local agent workspaces on desktop, terminal-based codebase editing, and hosted sandbox environments for building full-stack applications.

Developers, researchers, and students seeking free access to high-tier AI models and multi-agent workflows. It is built for users who want powerful, autonomous coding assistants across their terminal, desktop, and web environments without subscription lock-in.

  • Multi-Agent Orchestration: Divides complex tasks into specialized roles, including file-finding, implementation, and review agents.
  • Curated Model Catalog: Provides free access to leading models like GPT-5.6 Luna, DeepSeek V4 Pro, and MiMo 2.5 without API keys.
  • Cross-Platform Suite: Offers five distinct interfaces: a desktop app for parallel workspaces, a CLI, a web builder, a cloud repo connector, and a chat interface.
  • Parallel Local Workspaces: The desktop client isolates concurrent agents in separate workspaces to prevent context collision.
  • Hosted Sandboxes: The web and cloud products provide secure environments, live previews, terminals, and deployment workflows for full-stack apps.
  • Ad-Supported Free Access: Sustains free usage of high-tier models globally by displaying text ads and implementing fair-use session limits.

Where teams use it

Terminal-Based Code Editing

Allows developers to run Freebuff directly in their local project directory to have an agent autonomously find files, make changes, and run tests.

Cost-Free Prototyping

Enables indie hackers and students to build and ship full-stack applications in hosted sandboxes using premium LLMs without paying subscription fees.

Parallel Task Execution

Permits power users to run multiple isolated agents simultaneously on their desktop to tackle different features or bugs concurrently.

Deep Research Operations

Utilizes specialized research agents equipped with browser use capabilities to autonomously investigate documentation and test applications.

Getting started: npm install -g freebuff && freebuff

README

main branch

Freebuff

English | 简体中文

Five free AI products for coding, building, and research. No subscription, credits, or API key required.

Freebuff brings specialized agents and a choice of leading models to your terminal, desktop, browser, and GitHub repositories. Text ads support access to the included models.

Choose your Freebuff

Product What it does Get started
Freebuff Desktop Run parallel agents locally Download for macOS, Windows, or Linux
Freebuff CLI Code from your terminal Install the CLI
Freebuff Web Build and ship full-stack apps Build an app
Freebuff Cloud Run agents on any GitHub repository Connect a repository
Freebuff Chat Research and think with AI Start a chat

Quick start

Run Freebuff in any project from your terminal:

npm install -g freebuff
cd ~/my-project
freebuff

Then describe what you want. Freebuff finds the relevant files, makes changes, and runs the checks that matter for your project.

Models

Freebuff includes a curated model catalog. The regular picker currently offers:

Model Access Best for
MiMo v2.6 Flash Fast Full and limited access The default everywhere; balanced performance with image support
GLM 5.3 Flash Full and limited access Deepest reasoning, unmetered
DeepSeek V4.1 Flash 10/17 Full and limited access Fast coding and tool use, unmetered
DeepSeek V4.1 Flash Fast 10/17 Full access; paid plans at limited access Fast mode: the same model on DeepSeek's own API, splitting work across parallel subagents and verifying the result; priced on DeepSeek's peak and off-peak hours
GPT-6 Luna Full access Strong all-around with native images; runs on OpenAI flex capacity
MiMo 2.6 Pro Full access Xiaomi's stronger reasoning model, with image support
Solar Mini 4 Full and limited access Upstage's fast, compact model; 524K context, text only
Solar Pro 4 Full and limited access Upstage's larger, stronger model; 524K context, text only
Gemini 3.8 Flash Paid plans 1M context, and the only model that accepts audio, video and PDF
Muse Spark 1.3 Paid plans Meta's agentic coding model; 1M context. When it is busy or unavailable, it answers on DeepSeek V4.1 Flash rather than making you wait
Gemini 4 Argon US, or paid plans elsewhere Google's flagship reasoning model at a temporary promotional price, one session a day for every account; 1M context, images
GPT-6.1 Sol US, or paid plans elsewhere OpenAI's flagship, one session a day for every account; 1M context, images

Most models draw on your normal daily sessions rather than a separate limit. GLM 5.3 Flash, DeepSeek V4.1 Flash, MiMo v2.6 Flash Fast, Solar Mini 4 and Solar Pro 4 are unmetered at full access and cost no session at all. Models may still serve from a quantized (Q8_0) build.

DeepSeek V4 Pro was retired from the catalog; GLM 5.3 Flash replaces it as the deep-reasoning pick.

Beyond the regular picker:

  • Referrals and bounties earn extra sessions on top of the free daily allowance.
  • Gemini 3.1 Flash Lite powers specialist tasks such as file finding and research rather than appearing in the main picker.

Availability and limits depend on your access tier, product, and current capacity. Freebuff Desktop can also run locally installed Claude Code and Codex agents using your existing provider account; those connected models are separate from Freebuff's included catalog.

How Freebuff works

Freebuff uses specialized agents instead of sending every task through one model and one prompt. Depending on the task, agents gather context, plan, edit or research, run tools, and review the result.

  • Codebase context — File-finding agents map the relevant parts of a project before editing.
  • Implementation and review — Agents can divide work, make changes, run commands, and inspect the result.
  • Research and browser use — Agents can investigate documentation and test applications in a real browser.
  • Parallel local work — Desktop isolates concurrent agents in separate workspaces.
  • Hosted environments — Web and Cloud provide sandboxes, previews, terminals, and deployment workflows.

Free access

Freebuff is available in every country. Supported regions receive full access; other regions and VPN users receive limited access to GLM 5.3 Flash, DeepSeek V4.1 Flash 10/17, MiMo v2.6 Flash Fast, Solar Mini 4, and Solar Pro 4. Every model is paid for in hours at the multiplier shown in the picker: an hour of MiMo v2.6 Flash Slow uses one hour of balance, a 3x model uses three. The free limited-access allowance is 5 hours a day, or 4 on a VPN or proxy, spent first on every model, GLM included; earned hours go into your wallet and are used after it. (Balances read in hours since 2026-10-15; 1 hour = 5 Freebucks.)

Text ads support the included models. Freebuff shows the applicable session limits and any model-specific data-use notice before you start.

Is my data used to train AI? Only when a model or feature says data may be used for AI training. Freebuff or the provider may then keep submissions to develop, train, test, evaluate, fine-tune, and improve AI models or products, and Freebuff may share or sell them to third parties. Separately, Freebuff may use your data to train the models that choose and measure ads.

How is my data used and stored? Freebuff uses your messages, agent traces, and files to run the service and respond to your requests. We may analyze this data, and how you use the app, to personalize ads and train ad models. We do not give separately uploaded files, project files, or connected repositories to advertising providers. Restricted partners may evaluate repositories you connect to Freebuff Cloud, but cannot otherwise use, broadly share, or train on them. See the Privacy Policy for details.

Does Freebuff read files outside my project? No, with a few exceptions, such as files an agent reads in the conversation, files you share, and settings like your agent instructions and skills. See the Privacy Policy for details.

See the Privacy Policy for complete details.

Contributing

Freebuff is a TypeScript monorepo built with Bun. Contributions to the products, agents, tools, documentation, and underlying runtime are welcome.

Local development requires Docker and a configured .env.local; see the Contributing Guide before starting the services.

git clone https://github.com/CodebuffAI/freebuff.git
cd freebuff
bun install
bun up

Start the CLI separately with:

bun start-cli

See the Contributing Guide, development guide, and testing guide for environment setup and the checks to run before opening a pull request.

Built on Codebuff

Freebuff is built on Codebuff, the open multi-agent framework that powers its orchestration, tools, and SDK. To create custom agents or embed them in another application, see the Codebuff documentation and @codebuff/sdk.

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  1. Codecane v1.0.420-beta.185 (Staging)v1.0.420-beta.185Oct 21, 2025pre-release1K downloads

    ## Codecane v${VERSION} (Staging) **⚠️ This is a staging build intended for internal testing.** ### Included Binaries - `codecane-linux-x64.tar.gz` - `codecane-linux-arm64.tar.gz` - `codecane-darwin-x64.tar.gz` - `codecane-darwin-arm64.tar.gz` - `codecane-win32-x64.tar.gz` After downloading, extract the tarball, add the binary to your PATH, and run `codecane --help` for usage.

  2. Codecane v1.0.420-beta.184 (Staging)v1.0.420-beta.184Oct 21, 2025pre-release50 downloads

    ## Codecane v${VERSION} (Staging) **⚠️ This is a staging build intended for internal testing.** ### Included Binaries - `codecane-linux-x64.tar.gz` - `codecane-linux-arm64.tar.gz` - `codecane-darwin-x64.tar.gz` - `codecane-darwin-arm64.tar.gz` - `codecane-win32-x64.tar.gz` After downloading, extract the tarball, add the binary to your PATH, and run `codecane --help` for usage.

  3. Codecane v1.0.420-beta.180 (Staging)v1.0.420-beta.180Oct 19, 2025pre-release64 downloads

    ## Codecane v${VERSION} (Staging) **⚠️ This is a staging build intended for internal testing.** ### Included Binaries - `codecane-linux-x64.tar.gz` - `codecane-linux-arm64.tar.gz` - `codecane-darwin-x64.tar.gz` - `codecane-darwin-arm64.tar.gz` - `codecane-win32-x64.tar.gz` After downloading, extract the tarball, add the binary to your PATH, and run `codecane --help` for usage.

  4. Codecane v1.0.420-beta.179 (Staging)v1.0.420-beta.179Oct 19, 2025pre-release34 downloads

    ## Codecane v${VERSION} (Staging) **⚠️ This is a staging build intended for internal testing.** ### Included Binaries - `codecane-linux-x64.tar.gz` - `codecane-linux-arm64.tar.gz` - `codecane-darwin-x64.tar.gz` - `codecane-darwin-arm64.tar.gz` - `codecane-win32-x64.tar.gz` After downloading, extract the tarball, add the binary to your PATH, and run `codecane --help` for usage.

  5. Codecane v1.0.420-beta.178 (Staging)v1.0.420-beta.178Oct 19, 2025pre-release23 downloads

    ## Codecane v${VERSION} (Staging) **⚠️ This is a staging build intended for internal testing.** ### Included Binaries - `codecane-linux-x64.tar.gz` - `codecane-linux-arm64.tar.gz` - `codecane-darwin-x64.tar.gz` - `codecane-darwin-arm64.tar.gz` - `codecane-win32-x64.tar.gz` After downloading, extract the tarball, add the binary to your PATH, and run `codecane --help` for usage.

Commits per week

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9K commits in the last 52 weeks.

When work happens

weekday and hour
SunMonTueWedThuFriSat036912151821Sun 0:00 — 47 commitsSun 1:00 — 50 commitsSun 2:00 — 25 commitsSun 3:00 — 19 commitsSun 4:00 — 25 commitsSun 5:00 — 37 commitsSun 6:00 — 27 commitsSun 7:00 — 34 commitsSun 8:00 — 38 commitsSun 9:00 — 28 commitsSun 10:00 — 23 commitsSun 11:00 — 37 commitsSun 12:00 — 39 commitsSun 13:00 — 42 commitsSun 14:00 — 48 commitsSun 15:00 — 49 commitsSun 16:00 — 37 commitsSun 17:00 — 63 commitsSun 18:00 — 44 commitsSun 19:00 — 37 commitsSun 20:00 — 26 commitsSun 21:00 — 46 commitsSun 22:00 — 64 commitsSun 23:00 — 66 commitsMon 0:00 — 73 commitsMon 1:00 — 68 commitsMon 2:00 — 36 commitsMon 3:00 — 30 commitsMon 4:00 — 28 commitsMon 5:00 — 29 commitsMon 6:00 — 31 commitsMon 7:00 — 30 commitsMon 8:00 — 44 commitsMon 9:00 — 38 commitsMon 10:00 — 64 commitsMon 11:00 — 86 commitsMon 12:00 — 60 commitsMon 13:00 — 81 commitsMon 14:00 — 125 commitsMon 15:00 — 145 commitsMon 16:00 — 162 commitsMon 17:00 — 159 commitsMon 18:00 — 160 commitsMon 19:00 — 85 commitsMon 20:00 — 64 commitsMon 21:00 — 105 commitsMon 22:00 — 123 commitsMon 23:00 — 96 commitsTue 0:00 — 127 commitsTue 1:00 — 71 commitsTue 2:00 — 38 commitsTue 3:00 — 32 commitsTue 4:00 — 45 commitsTue 5:00 — 39 commitsTue 6:00 — 39 commitsTue 7:00 — 37 commitsTue 8:00 — 36 commitsTue 9:00 — 29 commitsTue 10:00 — 61 commitsTue 11:00 — 108 commitsTue 12:00 — 83 commitsTue 13:00 — 93 commitsTue 14:00 — 163 commitsTue 15:00 — 164 commitsTue 16:00 — 172 commitsTue 17:00 — 132 commitsTue 18:00 — 119 commitsTue 19:00 — 86 commitsTue 20:00 — 96 commitsTue 21:00 — 100 commitsTue 22:00 — 110 commitsTue 23:00 — 134 commitsWed 0:00 — 147 commitsWed 1:00 — 77 commitsWed 2:00 — 42 commitsWed 3:00 — 37 commitsWed 4:00 — 42 commitsWed 5:00 — 51 commitsWed 6:00 — 35 commitsWed 7:00 — 43 commitsWed 8:00 — 40 commitsWed 9:00 — 34 commitsWed 10:00 — 56 commitsWed 11:00 — 91 commitsWed 12:00 — 88 commitsWed 13:00 — 77 commitsWed 14:00 — 138 commitsWed 15:00 — 158 commitsWed 16:00 — 155 commitsWed 17:00 — 141 commitsWed 18:00 — 135 commitsWed 19:00 — 132 commitsWed 20:00 — 110 commitsWed 21:00 — 106 commitsWed 22:00 — 163 commitsWed 23:00 — 155 commitsThu 0:00 — 142 commitsThu 1:00 — 86 commitsThu 2:00 — 44 commitsThu 3:00 — 49 commitsThu 4:00 — 41 commitsThu 5:00 — 36 commitsThu 6:00 — 35 commitsThu 7:00 — 41 commitsThu 8:00 — 44 commitsThu 9:00 — 34 commitsThu 10:00 — 55 commitsThu 11:00 — 115 commitsThu 12:00 — 66 commitsThu 13:00 — 86 commitsThu 14:00 — 110 commitsThu 15:00 — 169 commitsThu 16:00 — 166 commitsThu 17:00 — 138 commitsThu 18:00 — 104 commitsThu 19:00 — 72 commitsThu 20:00 — 73 commitsThu 21:00 — 99 commitsThu 22:00 — 117 commitsThu 23:00 — 117 commitsFri 0:00 — 131 commitsFri 1:00 — 78 commitsFri 2:00 — 57 commitsFri 3:00 — 44 commitsFri 4:00 — 35 commitsFri 5:00 — 61 commitsFri 6:00 — 50 commitsFri 7:00 — 40 commitsFri 8:00 — 50 commitsFri 9:00 — 27 commitsFri 10:00 — 61 commitsFri 11:00 — 80 commitsFri 12:00 — 86 commitsFri 13:00 — 62 commitsFri 14:00 — 149 commitsFri 15:00 — 160 commitsFri 16:00 — 152 commitsFri 17:00 — 134 commitsFri 18:00 — 129 commitsFri 19:00 — 79 commitsFri 20:00 — 58 commitsFri 21:00 — 94 commitsFri 22:00 — 107 commitsFri 23:00 — 82 commitsSat 0:00 — 117 commitsSat 1:00 — 71 commitsSat 2:00 — 46 commitsSat 3:00 — 23 commitsSat 4:00 — 36 commitsSat 5:00 — 28 commitsSat 6:00 — 34 commitsSat 7:00 — 33 commitsSat 8:00 — 28 commitsSat 9:00 — 21 commitsSat 10:00 — 41 commitsSat 11:00 — 45 commitsSat 12:00 — 48 commitsSat 13:00 — 51 commitsSat 14:00 — 37 commitsSat 15:00 — 37 commitsSat 16:00 — 54 commitsSat 17:00 — 55 commitsSat 18:00 — 60 commitsSat 19:00 — 38 commitsSat 20:00 — 46 commitsSat 21:00 — 55 commitsSat 22:00 — 75 commitsSat 23:00 — 43 commits
Commit volume by weekday and hour (UTC). Larger dots mean more commits.
DateListRankStars gained
Sep 1, 2026monthly#19+3,236
Aug 31, 2026monthly#19+3,236
Aug 22, 2026weekly#13+1,133
Aug 21, 2026weekly#13+1,133
Aug 20, 2026weekly#11+1,037
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