GitHub Copilot vs Sourcegraph Cody
Both are built for Code — here's how GitHub Copilot and Sourcegraph Cody actually differ on pricing, platform reach and where each one is strongest.
At a glance
| Attribute | GitHub Copilot | Sourcegraph Cody |
|---|---|---|
| Pricing | From $10/mo | Contact for pricing |
| Platforms | Web, API, macOS, Windows, iOS, Android | Web, Self-hosted, macOS, Windows |
| Categories | Code | Code |
| Integrations | Not listed | Not listed |
Where each stands
GitHub Copilot
Pros
- Tightest integration with GitHub itself, from pull requests to Actions
- Supported across the widest range of editors and IDEs of any assistant here
- Frequent access to multiple frontier models (GPT, Claude, Gemini) under one subscription
Cons
- The 2026 move to usage-based billing for chat and agent requests makes monthly cost harder to predict
- Code completions and Next Edit Suggestions are free of charge, but agentic work now draws down metered credits fast
- Suggested code still needs review — it can be verbose or subtly wrong, especially in less common languages
Sourcegraph Cody
Pros
- Context quality benefits directly from Sourcegraph's mature code search and indexing
- Strong option for very large, sprawling codebases where single-file context tools struggle
- Robust self-hosted and air-gapped deployment for regulated industries
Cons
- No longer available to individuals or small teams — free and Pro plans were discontinued in mid-2025
- Enterprise contracts start high, putting it out of reach for most teams under a few hundred seats
- Agentic, multi-file editing capability trails newer agent-first tools like Cursor or Copilot's agent mode
Which should you choose?
GitHub Copilot is the better fit for:
- Speeding up boilerplate and repetitive code writing
- Getting a first-pass explanation of unfamiliar code
- Drafting tests and documentation alongside a change
- Getting a first-pass review on a pull request before a human looks
- Holding suggestions to a team's conventions with repository instructions
- Adding tests to code that shipped without any
Sourcegraph Cody is the better fit for:
- Large organizations with monorepos where context across the whole codebase matters
- Regulated enterprises that need self-hosted or air-gapped AI coding tools
- Teams already using Sourcegraph code search who want AI chat layered on top
- Answering where is this used across hundreds of repositories
- Standardising common AI prompts across an engineering organisation
- Assessing the blast radius of a change before making it
Looking for more options? Browse every tool in the Code category.
Related comparisons
Other head-to-heads involving GitHub Copilot or Sourcegraph Cody.


