How we review: this assessment is based on the product’s official documentation, current pricing and published independent evaluations; it is not a hands-on test. Read our review methodology.
GitHub Copilot was the product that made AI coding assistants mainstream, and it remains the one most developers encounter first. In 2026 it looks very different from the autocomplete tool of a few years ago: it now plans and edits across files, works in the terminal, reviews pull requests and runs as a cloud agent that hands back finished changes. GitHub has also moved its plans to a system of AI credits. This review assesses the product as GitHub documents it today.
What it is
Copilot is an AI assistant built into GitHub and into the editors developers already use. GitHub’s documentation describes it as helping you “write, understand, and ship software” within your code, issues, pull requests and automations. It is available in IDEs and editors, in a command-line tool, on GitHub.com and on mobile. Our GitHub Copilot directory entry gives a short overview.
Key features
- Code completion. Inline suggestions as you type. These are unlimited on paid plans and capped at 2,000 a month on Free.
- Chat. Questions about files, repositories and concepts, with explanations of code.
- Agent mode. You describe a goal; Copilot researches the repository, proposes a plan, edits files and runs tools, and you review and approve the result. It is available on every plan.
- Cloud agent. On Pro and above, you can assign an issue or task and Copilot works on it in the background, returning a pull request for review. Work can be tracked from the agents page, editors and third-party project tools.
- Code review. Pro and above include pull request and diff reviews, with custom instructions.
- Copilot CLI. Terminal use, task delegation, local or GitHub commits and a programmatic mode, on all plans.
- Models. GitHub’s plans page lists the same model catalogue on every individual plan, including models from Anthropic, OpenAI, Microsoft, Google, xAI and Moonshot’s Kimi. Different models consume credits at different rates.
- MCP and customization. MCP server integration, custom instructions, custom agents and Copilot Spaces are available across plans.
Pricing
At the time of writing (October 2026), GitHub’s official pages list the following. One GitHub AI Credit equals $0.01.
| Plan | Price | Monthly AI credits |
|---|---|---|
| Free | $0 | Limited chat and agent usage; 2,000 completions |
| Pro | $10/month | 1,500 (1,000 base + 500 flex) |
| Pro+ | $39/month | 7,000 (3,900 base + 3,100 flex) |
| Max | $100/month | 20,000 (10,000 base + 10,000 flex) |
| Business | $19/seat/month | 1,900 per user |
| Enterprise | $39/seat/month | 3,900 per user (requires GitHub Enterprise Cloud) |
Paid individual plans can buy extra credits. Verified students get Copilot Student free, and verified teachers and maintainers of popular open-source projects may qualify for free Pro.
Strengths
Integration is Copilot’s decisive advantage. Because it lives inside GitHub, it can be assigned an issue, open a pull request, review another developer’s changes and respond to comments — all in the place where teams already collaborate. Standalone AI editors can match or exceed it inside the editor, but none have the same access to the rest of the software workflow.
The pricing entry point is strong. At $10 a month, Pro gives unlimited inline suggestions, agent mode, the cloud agent and code review. The flex allotment effectively adds 50% more credits on top of the plan price.
Model choice is broad. Offering models from half a dozen providers under one subscription lets developers pick the right model for each task without managing separate accounts. A widely cited controlled experiment found that developers using Copilot finished a set coding task about 56% faster, with important caveats about how far that generalizes; we covered it in our Copilot productivity case study.
Limitations
AI credits change the economics. Under the credit system, the cost of a session depends on which model you pick and how much work the agent does. That is fair, but it makes monthly spend harder to predict than a flat request count, especially for teams running long agent tasks.
The free tier is capped tightly for anyone coding daily and excludes code review and the cloud agent. Delegation to third-party coding agents is limited to Pro+ and Max and still marked as preview. Enterprise-grade features such as IP indemnity, SAML SSO and usage metrics require the organization plans, and Copilot is not currently available on GitHub Enterprise Server.
As with every coding assistant, independent studies continue to show that AI-generated code can contain bugs and security issues. Agent mode requires review, and our guide on using AI coding assistants effectively covers sensible guardrails.
Who it’s for
- Teams on GitHub that want an assistant across editor, terminal and pull requests.
- Individual developers who want strong value at $10 a month.
- Students and open-source maintainers, who may qualify for free access.
- Enterprises on GitHub Enterprise Cloud needing policy control and indemnity.
Alternatives
- Cursor — an AI-first code editor with its own agents and usage-based plans.
- Claude — Claude Code offers a terminal-based coding agent within the Claude subscription.
- Replit — browser-based building and hosting for quick projects.
Verdict
GitHub Copilot earns 4.5 out of 5. Its documented feature set now spans the full development loop, from completions to cloud agents and code review, and its integration with GitHub is unmatched. Pro at $10 is one of the best-value subscriptions in AI. We hold back half a point because the move to AI credits makes heavy usage harder to budget and several advanced features remain in preview or locked to higher tiers.
