Gemini 3.5 Flash (original) (raw)
Gemini 3.5 Flash
Best for frontier performance across agents and coding
Solve complex real world problems at speed.
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
Frontier-level understanding across text, audio, images, code, and video.
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Code faster through iterative loops
See how Gemini 3.5 Flash generates six payment UI options in under 60 seconds.
Develop multiple creative concepts in parallel
See how Gemini 3.5 Flash can create 64 fractal variations at a high speed.
Long horizon agentic execution
See how Gemini 3.5 Flash ingests the AlphaGo paper and builds an intelligent game autonomously.
Accelerate the creation of brand assets
Watch how Gemini 3.5 Flash coordinates multiple workflows to generate and refine a brand for a fundraiser with minimal input.
Generate interactive web animations in a single shot
See how Gemini 3.5 Flash turns a text description into fully interactive HTML components.
Create music through real-time collaboration
See how Gemini 3.5 Flash coordinates multiple agents to create a song using the Strudel music library.
Orchestrate multi-agent workflows
Watch Gemini 3.5 Flash coordinate a team of specialized agents to design and build a virtual city.
Organize large file collections efficiently
See how Gemini 3.5 Flash deploys parallel agents to automatically rename and structure messy datasets.
Build and improve a game with interactive agent loops
Watch Gemini 3.5 Flash deploy agents to continuously refine a game in real time.
| Benchmark | Gemini 3.5 Flash | Gemini 3 Flash | Gemini 3.1 Pro | Claude Sonnet 4.6 | Claude Opus 4.7 | GPT-5.5 | ||
|---|---|---|---|---|---|---|---|---|
| Coding | Terminal-bench 2.1 Agentic terminal coding | Terminus-2 harness | 76.2% | 58.0% | 70.3% | — | 66.1% | 78.2% |
| SWE-Bench Pro (Public) Diverse agentic coding tasks | Single attempt | 55.1% | 49.6% | 54.2% | — | 64.3% | 58.6% | |
| Agentic | MCP Atlas Multi-step workflows using MCP | 83.6% | 62.0% | 78.2% | 69.5% | 79.1% | 75.3% | |
| Toolathlon Real-world general tool use | 56.5% | 49.4% | — | — | — | 55.6% | ||
| UI Control | OSWorld-Verified Agentic computer use | 78.4% | 65.1% | 76.2% | 72.5% | 78.0% | 78.7% | |
| Expert tasks | Finance Agent v2 Financial analysis and decision-making | 57.9% | 42.6% | 43.0% | 51.0% | 51.5% | 51.8% | |
| GDPval-AA Economically valuable knowledge work | Elo | 1656 | 1204 | 1314 | 1676 | 1753 | 1769 | |
| Multimodal | CharXiv Reasoning Information synthesis from complex charts | No tools | 84.2% | 80.3% | 83.3% | 72.4% | 82.1% | 84.1% |
| MMMU-Pro Multimodal understanding and reasoning | No tools | 83.6% | 81.2% | 80.5% | 74.5% | 75.2% | 81.2% | |
| Blueprint-Bench 2 Agentic spatial reasoning | Normalized score | 33.6% | 0.0% | 26.5% | 6.7% | 24.5% | 36.2% | |
| Long context | MRCR v2 (8-needle) Long context performance | 128k (average) | 77.3% | 67.2% | 84.9% | 84.9% | 59.3% | 94.8% |
| 1M (pointwise) | 26.6% | 22.1% | 26.3% | — | — | — | ||
| Reasoning | Humanity’s Last Exam Academic reasoning (full set, text + MM) | 40.2% | 33.7% | 44.4% | 33.2% | 46.9% | 41.4% | |
| ARC-AGI-2 Abstract reasoning puzzles | 72.1% | 33.6% | 77.1% | 58.3% | 75.8% | 84.6% |
Name
3.5 Flash
Status
Preview
Input
- Text
- Image
- Video
- Audio
Output
- Text
Input tokens
1M
Output tokens
64k
Knowledge cutoff
January 2025
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
Model card