GPT-5 Nano vs Gemini 3.1 Pro

1. Extremely fast performance

• Fastest model in the GPT-5 family.
• Great for real-time workflows, rapid responses, and high-throughput systems.

2. Most cost-efficient GPT-5 model

• Lowest input and output token costs.
• Suitable for large-scale or budget-sensitive applications.

3. Ideal for lightweight, well-scoped tasks

• Excels at summarization, classification, text extraction, and simple logic tasks.
• Best used when tasks are narrow and well-defined.

4. Multimodal input

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

5. Broad tool support

• Supports Web Search, File Search, Image Generation (as a tool), Code Interpreter, and MCP.
• (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.