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Description
Kimchi serves as a centralized platform designed for overseeing both SaaS and self-hosted AI models, enabling teams to deploy, route, optimize, and scale their LLM infrastructure seamlessly, all while maintaining their established developer workflows. This solution provides a unified control layer for managing AI coding agents, open-source models, commercial offerings, and internal inference, allowing organizations to blend cost-effective open-source solutions with premium providers like Claude, OpenAI, and Gemini when necessary. By prioritizing the reduction of LLM costs, Kimchi enhances the autonomy of development processes through efficient model routing, coding-focused inference, integration with multi-cloud platforms, support for multi-agent workflows, and the ability to interchange OSS and commercial models, all with minimal setup friction. Additionally, it facilitates the operation of the Kimchi coding agent across various teams, thereby broadening access to AI coding capabilities for engineering organizations while ensuring transparency in usage attribution, visibility into costs, and maintained operational governance. This comprehensive approach not only streamlines AI integration but also empowers teams to leverage the best resources available for their specific needs.
Description
Muse Code is a beta terminal coding agent from Meta designed to help developers complete complex software engineering work across large codebases. Powered by Muse Spark 1.2, the agent can plan repository changes, write code, run validation steps, and coordinate persistent subagents for difficult development tasks. Muse Code uses a simple main agent loop supported by async background agents that remain active throughout each session. These background agents can gather information, carry out next steps, and decide when to report back to the main agent, reducing latency and unnecessary user steering. The runtime is built around a local event log where every model call, tool run, approval, and edit is appended. This event log makes Muse Code replay-exact and restart-safe, allowing it to resume from the point of failure after a crash. Muse Code also ships with default skills, including /plan, /grill, and /goal, to support structured planning, plan validation, and objective completion. It can be installed on macOS or Linux and is integrated with Meta’s AI developer ecosystem. By combining terminal-based coding, persistent subagents, replay-safe execution, bundled skills, and Muse Spark 1.2, Muse Code helps developers automate larger and longer software engineering workflows.
API Access
Has API
API Access
Has API
Integrations
Claude Code
Cursor
GSD 2
GSD Pi
Gemini
Meta AI
Model Context Protocol (MCP)
Muse Glimmer
Muse Spark
Muse Spark 1.1
Integrations
Claude Code
Cursor
GSD 2
GSD Pi
Gemini
Meta AI
Model Context Protocol (MCP)
Muse Glimmer
Muse Spark
Muse Spark 1.1
Pricing Details
Free
Free Trial
Free Version
Pricing Details
$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.
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 Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
Kimchi
Country
United States
Website
kimchi.dev/
Vendor Details
Company Name
Meta
Founded
2004
Country
United States
Website
meta.ai