Gemini 3.7 Flash
Google · released Aug 13, 2026
Gemini 3.7 Flash is a multimodal model from Google for fast agentic workflows, coding, and complex multi-step reasoning. It is designed for tasks that require responsive performance and reliable multi-step...
Specification
- Context window
- 1.05M
- Max output
- 66K
- Knowledge cutoff
- Not stated
- Parameters
- Undisclosed
- Licence
- Proprietary
- Serving providers
- 2
- Moderated
- No
- Uptime
- 100.0%
Intelligence
39.1
90th percentile
Coding
76.1
Coding Index
Agentic
35.2
Agentic Index
Output speed
86 t/s
Median across providers
Latency
1.82s
Time to first token
Cost per task
$0.34
Estimated
Benchmarks
Where the score comes from
The Intelligence Index is a composite. These are the underlying evaluations this model was actually measured on.
Evaluation scores
Percentage correct · higher is better
- GPQA Diamond94.5%
- AA-LCR (long context)81.7%
- SciCode57.2%
- Humanity's Last Exam47.9%
- τ²-bench (Telecom)32.8%
An evaluation missing from this list was not run for this model — it is not a zero.
View as table
| Evaluation | Score |
|---|---|
| GPQA Diamond | 94.5% |
| AA-LCR (long context) | 81.7% |
| SciCode | 57.2% |
| Humanity's Last Exam | 47.9% |
| τ²-bench (Telecom) | 32.8% |
Against its peers
Intelligence Index · this model highlighted, nearest peers in grey
- 39.9
- Muse Spark 1.2Meta39.6
- V4.1 FlashDeepSeek39.5
- Gemini 3.7 FlashGoogle39.1
- GPT-5.4OpenAI39.0
- Grok 4.5xAI38.8
- GPT-5.5OpenAI38.4
- Claude Sonnet 5Anthropic38.2
Peers are the models sitting closest on the Intelligence Index — the set you would realistically choose between.
View as table
| Model | Intelligence |
|---|---|
| Qwen3.8 2.4T A95B | 39.9 |
| Muse Spark 1.2 | 39.6 |
| V4.1 Flash | 39.5 |
| Gemini 3.7 Flash | 39.1 |
| GPT-5.4 | 39.0 |
| Grok 4.5 | 38.8 |
| GPT-5.5 | 38.4 |
| Claude Sonnet 5 | 38.2 |
Percentile among all indexed models
Pricing
What it costs to run
List prices per million tokens, plus what one representative task works out to.
List price
- Input / 1M tokens
- $0.75
- Output / 1M tokens
- $3.75
- Cached input / 1M
- $0.075
- Blended 3:1
- $1.5
One task, estimated
$0.34
- Input tokens
- 50,000
- Output tokens
- 80,000
- Profile
- Reasoning
Estimated from list pricing: 50K input tokens plus 80K output tokens for reasoning models (25K for non-reasoning).
Serving providers
Speed and latency figures are medians across these providers, so a widely-served model reports a blend rather than any single endpoint.
Arena
Head-to-head generation quality
Elo from pairwise judgements, broken out by the kind of thing the model was asked to build.
- Overall Elo
- 1,322
- Win rate
- 53.5%
- Strongest at
- Game development
- Tournaments
- 13,833
Elo by category
Dot position on a 1,200–1,325 scale · Elo has no meaningful zero
- 1,322
- 1,317
- 1,308
- 1,305
- 1,303
- 1,280
- 1,227
- 1,209
Agent categories (full-stack apps, mobile apps) are only scored for models tested in agent harnesses.
View as table
| Category | Elo | Win rate |
|---|---|---|
| Game development | 1322 | 53.5% |
| Data visualisation | 1317 | 55.3% |
| 3D scenes | 1308 | 53.8% |
| Websites | 1305 | 54.0% |
| UI components | 1303 | 52.2% |
| SVG | 1280 | 53.5% |
| Mobile apps | 1227 | 52.9% |
| Full-stack apps | 1209 | 43.5% |