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About

GitHub Copilot is an AI-powered development assistant designed to accelerate software workflows from the editor to the enterprise. It works directly inside popular IDEs, terminals, and GitHub itself to help developers write, understand, and improve code faster. Copilot supports multiple leading large language models, allowing users to optimize for speed, accuracy, or cost. Developers can use Copilot to complete code, explain concepts, propose edits, and validate files in real time. It also enables agent-based workflows where Copilot can autonomously handle issues, write code, and create pull requests. With seamless integration across tools, Copilot keeps developers focused without breaking their flow. GitHub Copilot is built to scale from individual developers to large organizations with enterprise-grade controls.

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

Software developers, engineering teams, startups, and enterprises seeking to accelerate coding, automate development tasks, and improve productivity with AI-assisted workflows

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

$10 per month
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 4.0 / 5
ease 4.2 / 5
features 4.0 / 5
design 4.2 / 5
support 3.6 / 5

Reviews/Ratings

Overall 5.0 / 5
ease 5.0 / 5

Pros & Cons from Real Users

Pros

  • - It gives accurate suggestions and auto-completion almost all the time. - It works with almost all the new and old libraries and frameworks. - it gives not only obvious suggestions for auto-completion but also relevant and customized suggestions according to the project. - It is quite straightforward to use just install the extension on the code editor and it starts working like a charm.
  • I am afraid there is nothing positive to say unfortunately. It's not even close to being as good as ChatGPT.
  • - Easy to use, uses context of File currently in use and others in the project. - sometimes need some little things added, but generally can create fully working functions by just a name.
  • Guesses what code you want to generate from context. Good choices as it suggests code from what you have written. Good for tedious coding. Works seamlessly in VS Code.
  • GitHub Copilot works pretty well, and works better than I thought it would when I first decided to try it. It's snappy, works with a variety of IDEs, and is pretty accurate and efficient.

Cons

  • - One thing I noticed is if I am creating a project from scratch it does not give accurate auto-completion right from the start instead it takes time to analyze the project and then provides relevant suggestions. - Pricing can be a bit better.
  • - Doesn't reply 80% of the times - In the 20% of times it does reply it's mostly unusable code
  • - So far haven't found any. - Maybe creates a risk of relying on it to much for some people.
  • Expensive. Unable to trigger on demand. More settings/customizations would be nice.
  • Haven't used it long enough to find any red flags yet, but I will update my review if I come across any cons.

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

GitHub
Founded: 2008
United States
github.com/features/copilot

Company Information

Meta
Founded: 2004
United States
meta.ai

Alternatives

JetBrains Junie

JetBrains Junie

JetBrains

Alternatives

Claude Code

Claude Code

Anthropic
Perplexity

Perplexity

Perplexity AI

Categories

Categories

Integrations

Acuvity
Claude Sonnet 3.7
CodeGuide
GPT-4.1 mini
GPT-5.2 Pro
GPT-5.2-Codex
GPT-5.5
GPT-5.5 Pro
GPT‑5.4 Thinking
Golf
GuardionAI
IntelliSense
MAI-Image-2.5-Pro
Microsoft Azure
Neovim
OpenSpec
Pillar Security
Pinecone Rerank v0
Python
Ruby on Rails

Integrations

Acuvity
Claude Sonnet 3.7
CodeGuide
GPT-4.1 mini
GPT-5.2 Pro
GPT-5.2-Codex
GPT-5.5
GPT-5.5 Pro
GPT‑5.4 Thinking
Golf
GuardionAI
IntelliSense
MAI-Image-2.5-Pro
Microsoft Azure
Neovim
OpenSpec
Pillar Security
Pinecone Rerank v0
Python
Ruby on Rails
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