Gemini 3.1 Pro vs Qwen3-Flash

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. Enhanced Flash-generation performance

• Better factual accuracy and reasoning.

2. Very inexpensive

• Perfect for high-volume automation and micro-agents.

3. Hybrid thinking mode

• Not typical for small models.

4. Large context capacity

• Up to 1M tokens.