GPT-5.1 vs Gemini 2.5 Pro Experimental

1. Configurable Reasoning for Agentic Tasks

• Built to excel in autonomous or semi-autonomous coding workflows, with adjustable reasoning effort for planning, refactoring and debugging.

2. Fast Multi-Modal Input with Large Output

• Accepts both text and image inputs while producing text outputs.
• Offers up to 128 k output tokens, allowing long responses and code generation across multiple files.

3. Large Context & Knowledge Cut-Off

• 400 k token context window supports processing large codebases or documents.
• Knowledge cut-off of Sep 30 2024 ensures familiarity with recent tools and frameworks.

4. Reasoning Token Support

• Provides explicit support for reasoning tokens, enabling developers to fine-tune the balance between reasoning depth and speed.

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.