Gemini 3.1 Pro vs Gemini 2.5 Pro Experimental

1. Google's most advanced reasoning Gemini model

• Designed to solve complex problems across multimodal inputs, including text, audio, images, video, PDFs, and full code repositories.
• Google highlights improved software engineering behavior, better agentic performance, and stronger usability in domains like finance and spreadsheets.

2. Large multimodal context with substantial output room

• Supports a 1,048,576 token input context window for large repositories, long documents, and multi-source workflows.
• Allows up to 65,536 output tokens for longer answers, plans, and code generations.

3. More efficient thinking with expanded controls

• Improves token efficiency and reasoning performance across use cases.
• Adds the MEDIUM thinking_level option to better balance cost, speed, and quality.

4. Strong support for production agents

• Supports grounding with Google Search, code execution, function calling, structured outputs, context caching, RAG, and chat completions.
• Also offers a custom-tools endpoint tuned for agentic workflows that mix bash-like tools with custom code tools.

1. State-of-the-art reasoning performance

• #1 on LMArena human preference leaderboard.
• Excels at advanced reasoning benchmarks like GPQA and AIME 2025.
• Achieves 18.8% on Humanity's Last Exam (no tools), representing frontier human-level reasoning.

2. New “thinking model” architecture

• Built with explicit reasoning steps internally before responding.
• Handles complex, multi-stage logic with higher accuracy and fewer hallucinations.

3. Elite science and mathematics capabilities

• Leads in math and science tasks across industry benchmarks.
• High performance without costly inference tricks like majority voting.

4. Exceptional coding abilities

• Major leap over Gemini 2.0 in coding performance.
• 63.8% on SWE-Bench Verified with custom agent setup.
• Strong at code transformation, debugging, and building agentic apps.
• Capable of generating full applications (e.g., a playable video game) from a single-line prompt.

5. Massive multimodal context

• Ships with a 1,000,000 token window (2M coming soon).
• Handles entire documents, datasets, video sequences, audio files, and large codebases.
• Maintains strong performance even at extreme context lengths.

6. Native multimodality across all inputs

• Understands and reasons over text, images, audio, video, and code.
• Designed for real-world, multi-source problem-solving and agent workflows.

7. Consistent high-quality outputs

• Improved post-training results in more accurate, coherent, and stylistically strong responses.
• Higher reliability across complex workloads.

8. Early availability for developers

• Available today in Google AI Studio for experimentation.
• Coming soon to Vertex AI with higher rate limits and production-ready access.