GPT-5 Mini vs Gemini 3.1 Pro

1. High reasoning performance

• Retains strong reasoning capabilities despite being a smaller, faster model.
• Suitable for tasks requiring accurate logic and structured thinking.

2. Fast and cost-efficient

• Optimized for speed, making it ideal for real-time or high-volume workloads.
• Far cheaper than GPT-5 while maintaining solid capability.

3. Great for well-defined tasks

• Excels when prompts are precise and objectives are clearly specified.
• More predictable and stable for deterministic workflows.

4. Multimodal input

• Accepts text + image as input.
• Outputs text only.

5. Tool support

• Works with Web Search, File Search, Code Interpreter, MCP.
• (Does not support Image Generation as a tool and does not support Computer Use.)

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.