Gemini 3.6 Flash
Best for token efficiency in coding, knowledge work, and multimodal tasks
Our workhorse model that reduces output token usage by 17% compared to 3.5 Flash, according to Artificial Analysis Index.
Intelligence in a Flash
Get advanced reasoning at Flash-level latency and scale.
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Token Efficiency
Get better quality in coding, knowledge work, and multimodal tasks whilst reducing token usage.
Fast and smart
Speed and scale don’t have to come at the cost of intelligence.
Master complexity
Deep reasoning across long horizons and iterative coding tasks.
Truly multimodal
Multimodal understanding across text, audio, images, code, and video.
Hands-on
Here are a few ways you can use 3.6 Flash’s improved coding and knowledge work capabilities.
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3.6 Flash vs. 3.5 Flash token efficiency SxS (API)
3.6 Flash shows better token efficiency and reduced verbosity than 3.5 Flash in multi-step workflows, as seen in the OSWorld verified task
Financial data analysis (AIS)
3.6 Flash, using Managed Agents on AIS, can help parse through and analyze financial data and transcripts more efficiently and accurately than 3.5 Flash
Showcase
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“When evaluating models for Figma Make, we look for a balance of quality, speed, and cost. Gemini 3.6 Flash hits the sweet spot, offering a much faster way to explore and iterate on prototypes while upholding the quality of designs.”
Matt Colyer, Director of Product, Figma
Performance
3.6 Flash is more token efficient than 3.5 Flash and a step-up in coding and knowledge work.
| Benchmark | Notes | Gemini 3.6 Flash | Gemini 3.5 Flash | Gemini 3.1 Pro | GPT-5.6 Luna | Grok 4.5 | Claude Sonnet 5 |
|---|---|---|---|---|---|---|---|
| Input price $/1M tokens, no caching | $1.50 | $1.50 | $2.00 | $1.00 | $2.00 | $3.00 $2.00 (temp discount) | |
| Output price $/1M tokens | $7.50 | $9.00 | $12.00 | $6.00 | $6.00 | $15.00 $10.00 (temp discount) | |
| SWE-Bench Pro (Public) Diverse agentic coding tasks | 58.7% | 55.1% | 54.2% | 62.7% | 64.7% | 63.2% | |
| DeepSWE v1.1 Long-horizon software engineering | 49% | 37% | 12% | 67% | 54% | 54% | |
| Terminal-bench 2.1 Agentic terminal coding | Terminus-2 harness | 78.0% | 76.2% | 73.8% | 84.7% | 83.3% | 80.4% |
| MLE-Bench Machine Learning Engineering | 63.9% | 49.7% | 42.6% | 47.6% | 43.2% | 66.9% | |
| OSWorld-Verified Agentic computer use | 83.0% | 78.4% | 76.2% | 72.6% | — | 81.2% | |
| GDPVal-AA v2 Knowledge work | Elo | 1421 | 1349 | 965 | 1584 | 1535 | 1607 |
| CharXiv Reasoning Information synthesis from complex charts | No tools | 85.2% | 84.2% | 83.3% | 82.7% | 81.6% | 77.0% |
| With tools | 89.4% | 84.9% | 83.2% | — | — | 88.3% | |
| GDM-MRCR v2 (8-needle) Long context performance | 128k (average) | 91.8% | 77.3% | 84.9% | 74.8% | 81.4% | 71.6% |
| 1M (pointwise) | 54.0% | 26.6% | 26.3% | — | — | — |
For details on our evaluation methodology please see deepmind.google/models/evals-methodology/gemini-3-6-flash
Model information
- Name
- 3.6 Flash
- Status
- Preview
- Input
- Text
- Image
- Video
- Audio
- Output
- Text
- Input tokens
- 1M
- Output tokens
- 64k
- Tool use
- Function calling
- Structured output
- Search as a tool
- Code execution
- Best for
- Everyday tasks
- Agentic coding
- Advanced reasoning
- Multimodal understanding
- Long context understanding
- Availability
- Gemini App
- Gemini API
- Gemini Enterprise
- Gemini Enterprise Agent Platform
- Google AI Mode
- Google AI Studio
- Google Antigravity
- Android Studio
- Documentation
- View developer docs
- Model card
- View model card