The AI coding tool index
Which AI coding tools are actually used?
Every leading AI coding tool leaves a small mark on the commits it helps write — a “Co-authored-by” line in the git history. So we counted those marks across millions of real public commits. The result is lopsided: one tool has run away with it, and it is still pulling ahead.
Figures are estimates from GitHub commit search, as of 2 August 2026. How we measure ↓
Runaway leader
Claude Code
Around 20× the commit footprint of the next tool — two orders of magnitude ahead.
And still accelerating
≈ 32× in a year
Claude Code-authored commits went from ≈ 130K to ≈ 4.1M a week, year on year.
One tool has run away with it
Counting the same way over the same month (July 2026), Claude Code’s footprint isn’t a little bigger than the rest — it’s in a different league.
Claude Code, July 2026
≈ 9.4M
commits carrying its trailer (est.)
Next best (Cursor Agent)
≈ 480K
≈ 20× smaller
The race for second
Set Claude Code aside and the rest of the field is both far behind and closely bunched. Here they are to scale against each other (July 2026).
Bars are to scale within this group only — Claude Code would be roughly 20× the longest bar here. All figures are estimates.
The growth is the real story
The same search, one year apart, on the leader. The gap is so large that even a noisy estimate can’t hide it.
week of 26 Jul–01 Aug 2025
≈ 130K
commits / week
week of 26 Jul–01 Aug 2026
≈ 4.1M
commits / week
≈ 32×
in twelve months
The full field
Every tool stamps its own line into the commits it writes. We show the exact string we count and the July 2026 estimate, so the ranking is like-for-like.
| # | Tool | Maker | What we count | July 2026 (est.) |
|---|---|---|---|---|
| 1 | Claude Code | Anthropic | Co-authored-by: Claude | ≈ 9.4M |
| 2 | Cursor Agent | Anysphere | Co-authored-by: Cursor Agent | ≈ 480K |
| 3 | Devin | Cognition | Co-authored-by: Devin | ≈ 58K |
| 4 | Copilot Agent | GitHub | Co-authored-by: copilot-swe-agent | ≈ 16K |
| 5 | OpenAI Codex | OpenAI | Co-authored-by: openai-codex | ≈ 14K |
| 6 | aider | open source | aider (aider.chat) | ≈ 7.3K |
| 7 | Gemini CLI | Co-authored-by: gemini-cli | ≈ 310 |
How we measure — and what this can’t tell you
What we count
Agentic AI coding tools add a line like Co-authored-by: Claude to the commits they help write. We count how many public commits carry each tool’s line, using GitHub’s commit search. It is the same idea behind our language index: count what’s actually in the repositories, not opinions about it.
The numbers are estimates, and we won’t pretend otherwise
GitHub’s search returns an approximate count for large queries. Run the identical search twice and it moves a lot — we saw the same July 2026 total come back as ≈ 9.5M and then ≈ 11M seconds apart (a 13% swing). So we do two things: rank every tool over the same single month for a fair frame, and publish only the order and the direction of growth — both robust here because the tools sit orders of magnitude apart. An exact, reproducible version is on our roadmap and needs its own data pipeline.
This measures tools that sign their work
We can only see tools that leave a trailer — Claude Code, Cursor Agent, Devin, Copilot Agent, OpenAI Codex, aider, Gemini CLI. It is blind to plain GitHub Copilot autocomplete and to code pasted from a chat window, which leave no mark. Read this as “which agentic tools show up in commit history”, not “which AI is most popular overall”.
It ranks tools, not the models underneath
Cursor or a CLI can run different models under the hood, and the trailer names the tool, not the model. A model-by-model view is a harder, separate question.
Keep reading
- Compare AI coding assistants — features, pricing and what each is best for.
- Which languages AI writes best — language support, tool by tool.
- How AI is reshaping language popularity — the wider picture.