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About

Kimchi is a centralized gateway for managing SaaS and self-hosted AI models, built to help teams deploy, route, optimize, and scale LLM infrastructure without changing the developer workflow. It gives organizations one control layer for AI coding agents, open-source models, commercial models, and internal inference, allowing teams to combine lower-cost OSS models with higher-tier providers such as Claude, OpenAI, Gemini, and others when the task requires it. Kimchi focuses on reducing LLM cost while making development more autonomous, with fast model routing, coding-oriented inference, MCP integration, multi-agent workflows, interchangeable OSS and commercial models, and low-friction local setup. It supports running the Kimchi coding agent across teams, giving engineering organizations broader access to AI coding while preserving team-wide usage attribution, cost visibility, and operational control.

About

Muse Code is Meta’s terminal coding agent, powered by Muse Spark 1.2, for handling complex software engineering tasks across large repositories. The agent can plan changes, write code, validate results, and coordinate multiple persistent subagents during development sessions. Muse Code uses async background agents that stay active throughout a session to reduce repeated information gathering and help complete multi-step tasks with less steering. Its runtime uses a local event log that records model calls, tool runs, approvals, and edits so sessions can be replayed and resumed after failures. Muse Code includes bundled skills such as /plan for approval-gated planning, /grill for stress-testing plans, and /goal for working toward completion. Built for AI developers and software teams, Muse Code helps automate coding workflows, long-running engineering tasks, debugging, and repository-level development.

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Audience

Engineering teams and AI infrastructure leaders that need a centralized gateway to run coding agents, route across models, reduce LLM costs, and manage AI development usage at scale

Audience

Software engineers, AI developers, coding agent users, platform teams, DevOps teams, ML engineers, research teams, enterprise development teams, and organizations that need terminal coding agents, repository automation, code generation, debugging, validation, persistent subagents, replay-safe execution, long-running coding workflows, and end-to-end software development support

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

API

Offers API

API

Offers API

Screenshots and Videos

Screenshots and Videos

Pricing

Free
Free Version
Free Trial

Pricing

$1.25 per 1M tokens (input)
Standard pricing: $1.25 per million input tokens and $4.25 per million output tokens

Discounted "contributor" tier costing $0.10 per million input tokens and $0.20 per million output tokens for users who agree to share feedback to improve the AI.
Free Version
Free Trial

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

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Reviews/Ratings

Overall 5.0 / 5
ease 5.0 / 5

Pros & Cons from Real Users

Pros

  • Muse Code looks exciting because Meta is finally going after coding agents directly, not just releasing another general AI model. A terminal-based agent that can write code, inspect software, run tests, and validate changes is exactly the kind of workflow developers actually care about. The pricing angle is a big deal. Meta is pitching Muse Code as one of the more affordable coding agents, with a lower-cost tier that is reportedly less than one-tenth the cost of its general Muse Spark model. That matters if you use coding agents all day instead of just for the occasional refactor. I also like that it is powered by Muse Spark 1.2, which sounds more focused on software engineering than earlier Muse Spark releases. If Meta can make the agent reliable inside real repos, Muse Code could become a serious daily tool.

Cons

  • It is still in beta, so I would not trust it blindly yet. Coding agents need to prove themselves on messy codebases, failing tests, weird dependencies, security-sensitive changes, and long multi-step tasks. I would also want to see more independent developer feedback. Meta’s pricing and positioning are interesting, but the real test is whether Muse Code can consistently make good changes without wasting time or creating cleanup work.

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

Kimchi
United States
kimchi.dev/

Company Information

Meta
Founded: 2004
United States
meta.ai

Alternatives

Alternatives

Claude Code

Claude Code

Anthropic
Cline

Cline

Cline AI Coding Agent
Amp

Amp

Amp Code
Gemini CLI

Gemini CLI

Google
OpenCode

OpenCode

Anomaly Innovations

Categories

Categories

Integrations

Claude Code
Cursor
GSD 2
GSD Pi
Gemini
Meta AI
Model Context Protocol (MCP)
Muse Spark
Muse Spark 1.1
Muse Spark 1.2
OpenAI
OpenClaw
OpenCode

Integrations

Claude Code
Cursor
GSD 2
GSD Pi
Gemini
Meta AI
Model Context Protocol (MCP)
Muse Spark
Muse Spark 1.1
Muse Spark 1.2
OpenAI
OpenClaw
OpenCode
Claim Kimchi and update features and information
Claim Kimchi and update features and information
Claim Muse Code and update features and information
Claim Muse Code and update features and information