LLM ComparisonGemini 3.1 ProQwen3-Max

Gemini 3.1 Pro vs Qwen3-Max

Compare Gemini 3.1 Pro and Qwen3-Max. Build AI products powered by either model on Appaca.

Model Comparison

FeatureGemini 3.1 ProQwen3-Max
ProviderGoogleAlibaba Cloud
Model Typetexttext
Context Window1,048,576 tokens262,144 tokens
Input Cost
$4.00/ 1M tokens
$0.86/ 1M tokens
Output Cost
$18.00/ 1M tokens
$3.44/ 1M tokens

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Strengths & Best Use Cases

Gemini 3.1 Pro

Google

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.

Qwen3-Max

Alibaba Cloud

1. Best performance in Qwen3 series

  • Handles complex multi-step reasoning.
  • Excellent for agent programming and tool calling.

2. Massive context window

  • 262K tokens enable long multi-document tasks.
  • Useful for RAG pipelines, analysis, and long-form workflows.

3. Tiered pricing support

  • More cost-efficient for small requests.
  • Supports context caching for repeated inputs.

4. Strong general-purpose intelligence

  • High accuracy in coding, reasoning, and structured tasks.
  • Reliable for enterprise automation.

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