GitHub Copilot vs Cody: Which AI Coding Assistant Should You Use in 2026?

A side-by-side comparison of GitHub Copilot and Cody (Sourcegraph) covering pricing, context handling, IDE support, and which tool fits your team's codebase size.

Updated 2026-09 · 2026

GitHub Copilot

AI pair programmer built into your editor

$10user/month (Individual, billed monthly); $19/user/mo Business; $39/user/mo Enterprise

Strengths

+Deepest IDE integration (VS Code, JetBrains, Neovim, Visual Studio)
+Fastest inline autocomplete of any major tool
+Copilot Chat and Copilot Workspace for multi-file edits

Weaknesses

-Limited whole-repo context compared to Cody's codebase-aware search
-Business/Enterprise tiers get expensive at scale
-Less transparent about which model powers a given response

Best for

Teams already living inside GitHub who want fast, low-friction autocomplete without extra setup.

Cody

AI code assistant with full codebase context

$0Free tier available; Pro $9/user/month; Enterprise custom pricing

Strengths

+Codebase-wide context via embeddings/search, not just open files
+Free tier is genuinely usable for solo devs and small teams
+Model flexibility (Claude, GPT-4o, Gemini depending on plan)

Weaknesses

-Smaller IDE plugin ecosystem than Copilot
-Autocomplete feels a step behind Copilot's latency in some editors
-Enterprise features require Sourcegraph deployment, adding ops overhead

Best for

Teams with large or multi-repo codebases who need an assistant that understands cross-file context, and want a free tier before committing.

Feature Comparison

Feature	GitHub Copilot	Cody
Free tier	Only for students/OSS maintainers	Yes, limited monthly usage
Inline autocomplete	Yes, very fast	Yes, slightly slower
Chat interface	Copilot Chat	Cody Chat
Codebase-wide context	Limited (open files/repo hints)	Strong (embeddings + code search)
Model choice	OpenAI models only (fixed by GitHub)	Choose between Claude, GPT-4o, Gemini
Multi-file edits	Copilot Workspace (preview)	Cody Edit / Batch changes
IDE support	VS Code, JetBrains, Visual Studio, Neovim	VS Code, JetBrains, Neovim (fewer editors overall)
Self-hosted option	No	Yes, via Sourcegraph Enterprise
GitHub integration (PRs, Actions)	Native	Via Sourcegraph integrations, less native
Pricing for teams (10 devs/mo)	$190-$390/mo depending on tier	$0-$90/mo depending on tier
Enterprise security/compliance	GitHub Enterprise controls	SOC 2, self-hosted deployment available

The Verdict

Copilot wins on raw autocomplete speed and GitHub-native workflow, making it the safer default for teams already deep in the GitHub ecosystem. Cody wins on cost and context — its free tier is real, and its codebase-wide understanding matters more once your repo gets big. If your team is small and budget-conscious, start with Cody's free plan; if you need Copilot's polish and already pay for GitHub Enterprise, stick with Copilot.

How to switch from GitHub Copilot to Cody

1Copy any persistent Copilot artifacts out of your repos — export `.github/copilot-instructions.md`, saved prompt snippets, and any custom chat instructions as plain text/markdown files, since Copilot has no built-in bulk export.
2Sign up for Cody at sourcegraph.com/cody (or cody.dev) and connect it to your GitHub/GitLab account so it can index your repositories for context.
3Install the Cody extension in your team's primary IDE (VS Code or JetBrains) and disable/uninstall the Copilot extension to avoid suggestion conflicts.
4Recreate your custom instructions inside Cody's context/config settings (Cody supports repo-level custom prompts similar to Copilot's instructions file).
5Re-point any CI or PR-review automations that referenced Copilot Workspace to use Sourcegraph's batch changes or Cody's CLI, testing on one repo before rolling out.
6Roll out to the team in stages — start with 2-3 developers on Cody Pro, gather feedback for a sprint, then cancel remaining Copilot seats once everyone confirms parity.

GitHub Copilot vs Cody: common questions

How do I export my GitHub Copilot chat history and settings before switching to Cody?+

GitHub Copilot doesn't offer a bulk export feature — chat sessions live in your editor's local history (e.g., VS Code's Copilot Chat panel) and aren't stored as portable files. Manually copy any saved prompts, custom instructions, or `.github/copilot-instructions.md` files from your repos, since those are the only persistent artifacts worth carrying over.

What do I lose by switching from Copilot to Cody?+

You lose Copilot Workspace's native GitHub PR/issue integration and slightly faster inline suggestion latency. You also lose the guarantee of a single consistent model — Cody lets you pick models, which is a feature but means output style can vary between sessions.

Is Cody's free tier enough for a small team of 3-5 developers?+

Cody's free tier gives each user a capped number of autocompletes and chat messages per month, which is workable for light usage or evaluation but will feel tight for daily heavy coding. Most small teams end up on the $9/user/month Pro tier once usage ramps up, which is still cheaper than Copilot Business at $19/user/month.

Does Cody integrate with GitHub the way Copilot does?+

Cody connects to GitHub repos for context and code search, but it doesn't have Copilot's native PR review or GitHub Actions hooks. If your workflow depends heavily on in-PR AI suggestions, you'll need to rely on Cody's IDE extension and chat instead of PR-level automation.

Is Cody actually cheaper than Copilot over a year for a growing team?+

Yes, for teams under ~10 people: Cody Free or Pro ($9/user/month) undercuts Copilot Business ($19/user/month) significantly, saving roughly $1,200/year for a 10-person team. At Enterprise scale the gap narrows since both require custom contracts, so re-evaluate pricing once you exceed 50+ seats.