GPT-5 vs Gemini 3.1 Pro

1. High reasoning capability

• Designed for intelligent reasoning across complex domains.
• Supports reasoning tokens and adjustable reasoning effort.

2. Strong coding and agentic performance

• Optimized for multi-step coding tasks, tool-use chains, and agent workflows.
• Handles complex logic, planning, and structured problem solving reliably.

3. Multimodal input

• Accepts text + image as input.
• Produces text outputs with strong instruction following.

4. Extensive tool support

• Works with Web Search, File Search, Image Generation (as a tool), Code Interpreter, MCP, and more.
• Integrated across Chat Completions, Responses API, Realtime, Assistants, Batch, Embeddings, etc.

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.