Learn anything
Understand complex topics in a way that makes sense for you – with clear, concise, and helpful responses
Gemini 3.1 Pro
Best for complex tasks and bringing creative concepts to life
A smarter model to help you learn, plan, and build like never before.
Partner with a pro
With state-of-the-art reasoning capabilities
Build anything
Bring your ideas to life – from sketches and prompts to interactive tools and experiences
Plan anything
Delegate tasks and multi-step projects to get things done faster than ever before
Capabilities
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Reasoning with unprecedented depth and nuance
Smart, concise, direct responses – with genuine insight over cliche and flattery.
Advanced multimodal understanding
Text, images, video, audio – even code. Gemini 3.1 Pro is state-of-the-art on reasoning with unprecedented depth and nuance.
Our best model for vibe coding and agentic coding
Gemini 3.1 brings exceptional instruction following – with meaningful improved tool use and agentic coding.
Improved agentic capabilities
Better tool use. Simultaneous, multi-step tasks. Gemini 3.1’s agentic capabilities can build more helpful and intelligent personal AI assistants.
Hands-on
Explore what you can do with Gemini 3.1 Pro
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Transform real-time data into a stunning, interactive visualization
Gemini 3.1 Pro uses advanced reasoning to configure live telemetry streams to build dynamic applications like this aerospace dashboard.
Prototype sensory-rich interfaces with complex, interactive 3D simulations
Gemini 3.1 Pro codes an immersive starling murmuration, complete with hand-tracking manipulation and dynamic generative audio.
Generate complex, believable environments
From terrain generation to traffic flow, Gemini 3.1 Pro uses advanced reasoning to code and assemble the many layers of a simulated city.
Build lightweight, scalable animations directly into your codebase
Gemini 3.1 Pro understands design intent, converting static SVGs into animated, code-based graphics for faster, cleaner web development.
Translate complex literary themes into functional code and sleek, contemporary interfaces
Gemini 3.1 Pro reasons through the atmospheric tone of a novel to build a modern, personalized portfolio.
Get started
Build with Gemini 3.1
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New
Google Antigravity
Build with our new agentic development platform
Google AI Studio
Leap from prompt to production
Gemini API
Get started building with cutting-edge AI models
Performance
Gemini 3.1 raises the bar across a wide range of benchmarks.
| Benchmark | Notes | Gemini 3.1 Pro Thinking (High) | Gemini 3 Pro Thinking (High) | Sonnet 4.6 Thinking (Max) | Opus 4.6 Thinking (Max) | GPT-5.2 Thinking (xhigh) | GPT-5.3-Codex Thinking (xhigh) |
|---|---|---|---|---|---|---|---|
| Humanity's Last Exam Academic reasoning (full set, text + MM) | No tools | 44.4% | 37.5% | 33.2% | 40.0% | 34.5% | — |
| Search (blocklist) + Code | 51.4% | 45.8% | 49.0% | 53.1% | 45.5% | — | |
| ARC-AGI-2 Abstract reasoning puzzles | ARC Prize Verified | 77.1% | 31.1% | 58.3% | 68.8% | 52.9% | — |
| GPQA Diamond Scientific knowledge | No tools | 94.3% | 91.9% | 89.9% | 91.3% | 92.4% | — |
| Terminal-Bench 2.0 Agentic terminal coding | Terminus-2 harness | 68.5% | 56.9% | 59.1% | 65.4% | 54.0% | 64.7% |
| Other best self-reported harness | — | — | — | — | 62.2% (Codex) | 77.3% (Codex) | |
| SWE-Bench Verified Agentic coding | Single attempt | 80.6% | 76.2% | 79.6% | 80.8% | 80.0% | — |
| SWE-Bench Pro (Public) Diverse agentic coding tasks | Single attempt | 54.2% | 43.3% | — | — | 55.6% | 56.8% |
| LiveCodeBench Pro Competitive coding problems from Codeforces, ICPC, and IOI | Elo | 2887 | 2439 | — | — | 2393 | — |
| SciCode Scientific research coding | 59% | 56% | 47% | 52% | 52% | — | |
| APEX-Agents Long horizon professional tasks | 33.5% | 18.4% | — | 29.8% | 23.0% | — | |
| GDPval-AA Elo Expert tasks | 1317 | 1195 | 1633 | 1606 | 1462 | — | |
| τ2-bench Agentic and tool use | Retail | 90.8% | 85.3% | 91.7% | 91.9% | 82.0% | — |
| Telecom | 99.3% | 98.0% | 97.9% | 99.3% | 98.7% | — | |
| MCP Atlas Multi-step workflows using MCP | 69.2% | 54.1% | 61.3% | 59.5% | 60.6% | — | |
| BrowseComp Agentic search | Search + Python + Browse | 85.9% | 59.2% | 74.7% | 84.0% | 65.8% | — |
| MMMU-Pro Multimodal understanding and reasoning | No tools | 80.5% | 81.0% | 74.5% | 73.9% | 79.5% | — |
| MMMLU Multilingual Q&A | 92.6% | 91.8% | 89.3% | 91.1% | 89.6% | — | |
| MRCR v2 (8-needle) Long context performance | 128k (average) | 84.9% | 77.0% | 84.9% | 84.0% | 83.8% | — |
| 1M (pointwise) | 26.3% | 26.3% | Not supported | Not supported | Not supported | — |
Model information
- Name
- 3.1 Pro
- 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
- Agentic
- Advanced coding
- Long context understanding
- Multimodal understanding
- Algorithmic development
- Availability
- Gemini App
- Google Cloud / Vertex AI
- Google AI Studio
- Gemini API
- Google AI Mode
- Google Antigravity
- Documentation
- View developer docs
- Model card
- View model card