Model Comparison

Gemini 3.1 Pro vs Qwen3.6-35B-A3B

Gemini 3.1 Pro significantly outperforms across most benchmarks.

Performance Benchmarks

Comparative analysis across standard metrics

7 benchmarks

Gemini 3.1 Pro outperforms in 7 benchmarks (GPQA, Humanity's Last Exam, MCP Atlas, MMMU-Pro, SWE-Bench Pro, SWE-Bench Verified, Terminal-Bench 2.0), while Qwen3.6-35B-A3B is better at 0 benchmarks.

Gemini 3.1 Pro significantly outperforms across most benchmarks.

Sat Apr 18 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Cost data unavailable.

Lowest available price from all providers
Sat Apr 18 2026 • llm-stats.com
Google
Gemini 3.1 Pro
Input tokens$2.50
Output tokens$15.00
Best providerGoogle
Alibaba Cloud / Qwen Team
Qwen3.6-35B-A3B
Input tokens$0.00
Output tokens$0.00
Best providerUnknown Organization
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Context Window

Maximum input and output token capacity

Only Gemini 3.1 Pro specifies input context (1,048,576 tokens). Only Gemini 3.1 Pro specifies output context (65,536 tokens).

Google
Gemini 3.1 Pro
Input1,048,576 tokens
Output65,536 tokens
Alibaba Cloud / Qwen Team
Qwen3.6-35B-A3B
Input- tokens
Output- tokens
Sat Apr 18 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Both Gemini 3.1 Pro and Qwen3.6-35B-A3B support multimodal inputs.

They are both capable of processing various types of data, offering versatility in application.

Gemini 3.1 Pro

Text
Images
Audio
Video

Qwen3.6-35B-A3B

Text
Images
Audio
Video

License

Usage and distribution terms

Gemini 3.1 Pro is licensed under a proprietary license, while Qwen3.6-35B-A3B uses Apache 2.0.

License differences may affect how you can use these models in commercial or open-source projects.

Gemini 3.1 Pro

Proprietary

Closed source

Qwen3.6-35B-A3B

Apache 2.0

Open weights

Release Timeline

When each model was launched

Gemini 3.1 Pro was released on 2026-02-19, while Qwen3.6-35B-A3B was released on 2026-04-16.

Qwen3.6-35B-A3B is 2 months newer than Gemini 3.1 Pro.

Gemini 3.1 Pro

Feb 19, 2026

1 months ago

Qwen3.6-35B-A3B

Apr 16, 2026

2 days ago

1mo newer

Knowledge Cutoff

When training data ends

Gemini 3.1 Pro has a documented knowledge cutoff of 2025-01-31, while Qwen3.6-35B-A3B's cutoff date is not specified.

We can confirm Gemini 3.1 Pro's training data extends to 2025-01-31, but cannot make a direct comparison without Qwen3.6-35B-A3B's cutoff date.

Gemini 3.1 Pro

Jan 2025

Qwen3.6-35B-A3B

Outputs Comparison

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Key Takeaways

Larger context window (1,048,576 tokens)
Higher GPQA score (94.3% vs 86.0%)
Higher Humanity's Last Exam score (51.4% vs 21.4%)
Higher MCP Atlas score (69.2% vs 62.8%)
Higher MMMU-Pro score (80.5% vs 75.3%)
Higher SWE-Bench Pro score (54.2% vs 49.5%)
Higher SWE-Bench Verified score (80.6% vs 73.4%)
Higher Terminal-Bench 2.0 score (68.5% vs 51.5%)
Alibaba Cloud / Qwen Team

Qwen3.6-35B-A3B

View details

Alibaba Cloud / Qwen Team

Has open weights

Detailed Comparison

AI Model Comparison Table
Feature
Google
Gemini 3.1 Pro
Alibaba Cloud / Qwen Team
Qwen3.6-35B-A3B

FAQ

Common questions about Gemini 3.1 Pro vs Qwen3.6-35B-A3B

Gemini 3.1 Pro significantly outperforms across most benchmarks. Gemini 3.1 Pro is made by Google and Qwen3.6-35B-A3B is made by Alibaba Cloud / Qwen Team. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.
Gemini 3.1 Pro scores t2-bench: 99.3%, LiveCodeBench Pro: 96.2%, GPQA: 94.3%, MMMLU: 92.6%, BrowseComp: 85.9%. Qwen3.6-35B-A3B scores MMLU-Redux: 93.3%, MMBench-V1.1: 92.8%, AI2D: 92.7%, AIME 2026: 92.7%, RefCOCO-avg: 92.0%.
Gemini 3.1 Pro supports 1.0M tokens and Qwen3.6-35B-A3B supports an unknown number of tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.
Key differences include licensing (Proprietary vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.
Gemini 3.1 Pro is developed by Google and Qwen3.6-35B-A3B is developed by Alibaba Cloud / Qwen Team.