Do coding agents recommend Google Gemini?
Google Gemini was chosen in 6% of 801 judged document processing sessions, ranking sixth.
Google Gemini was chosen in 6% of 801 judged document processing sessions, ranking sixth. It was also raised as a candidate in 246 further sessions without being chosen.
This page reports what happened when Claude Code, Codex, Cursor, Grok Build CLI and Muse Code had to solve a problem in document processing inside a realistic codebase. Not what a chat assistant says about Google Gemini. What an agent actually installed.
The numbers
| Category | Document processing |
| Sessions in the category | 801 |
| Sessions where Google Gemini was chosen | 45 |
| Install share | 6% |
| Rank in category | 6 of 42 |
| Codebases it won in | 6 |
| Raised as a candidate, not chosen | 246 |
| Chosen when considered | 15% |
| Site | ai.google.dev |
By agent
The agents treat Google Gemini very differently. Grok Build CLI chose it in 23% of its sessions in this category and Claude Code in 1%, a spread of 22 points.
| Agent | Sessions | Chose Google Gemini | Share |
|---|---|---|---|
| Claude Code | 180 | 2 | 1% |
| Codex | 235 | 2 | 1% |
| Cursor | 180 | 27 | 15% |
| Grok Build CLI | 30 | 7 | 23% |
| Muse Code | 176 | 7 | 4% |
A single blended install share would report the midpoint and hide both ends. If most of your users run Claude Code, your real position here is 1%, not 6%.
By who was asking
Google Gemini does much better with one kind of buyer than another. It won 24% of sessions asked as vibe coder and 0% of those asked as enterprise team.
| Who is asking | Sessions | Chose Google Gemini | Share |
|---|---|---|---|
| Vibe coder | 68 | 16 | 24% |
| Junior developer | 327 | 24 | 7% |
| Senior engineer | 270 | 5 | 2% |
| Enterprise team | 136 | 0 | 0% |
What Google Gemini was up against
The full ranking in document processing, from the same sessions:
| # | Product | Runs won | Share |
|---|---|---|---|
| 1 | Azure AI Document Intelligence | 193 | 24% |
| 2 | Anthropic Claude | 150 | 19% |
| 3 | Amazon Textract | 103 | 13% |
| 4 | Google Cloud Document AI | 49 | 6% |
| 5 | OpenAI models | 46 | 6% |
| 6 | Google Gemini (this page) | 45 | 6% |
| 7 | Docling | 24 | 3% |
| 8 | Apache PDFBox | 23 | 3% |
What this means
This is an integration problem, not a presence problem. Agents raised Google Gemini in 246 sessions and chose it in 45, so it reaches the shortlist and then loses. Something at the last step is costing the session, and in our data that is usually a quickstart that does not run when pasted, documentation describing an interface that changed, or a package name that does not match the product name.
That is the cheaper of the two problems to have. The reason is written down in each losing transcript.
Where these numbers come from
The 801 sessions in document processing are part of a published set of 15,051, run with real coding agents inside realistic codebases and judged blind. The full method is on one page: how we measured this.
Every document processing run can be replayed on the board.
If you work on Google Gemini: the judge recorded a reason for every session where it was raised and passed over. Those reasons are in the transcripts.
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Common questions
Do coding agents recommend Google Gemini?
Yes. Google Gemini was chosen in 45 of the 801 judged sessions in document processing, a 6% install share, ranking sixth in its category.
Does Claude Code recommend Google Gemini?
In 2 of the 180 sessions in document processing run with Claude Code, which is 1%.
Do different coding agents treat Google Gemini differently?
Yes, and by a wide margin. Grok Build CLI chose it in 23% of its runs and Claude Code in 1%.
How was this measured?
Real coding agents at pinned versions were run in sandboxes inside 92 realistic codebases and asked to solve real tasks. A simulated project owner approved or questioned each recommendation before any code was written, and a judge from a model family that builds none of the agents read every session blind.
How often is Google Gemini considered but not chosen?
It was raised as a candidate in 246 sessions without being chosen, and chosen in 45. That is a 15% conversion from considered to chosen.
Where this comes from
Armature ran 15,051 judged sessions with Claude Code, Codex, Cursor, Grok Build CLI and Muse Code inside 92 realistic codebases, and published every run. The numbers on this page come from that work.