Model Comparison

Gemini Diffusion vs Qwen3-235B-A22B-Instruct-2507

Qwen3-235B-A22B-Instruct-2507 significantly outperforms across most benchmarks.

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Performance Benchmarks

Comparative analysis across standard metrics

2 benchmarks

Gemini Diffusion outperforms in 0 benchmarks, while Qwen3-235B-A22B-Instruct-2507 is better at 2 benchmarks (AIME 2025, GPQA).

Qwen3-235B-A22B-Instruct-2507 significantly outperforms across most benchmarks.

Mon May 25 2026 • llm-stats.com

Arena Performance

Human preference votes

Context Window

Maximum input and output token capacity

Only Qwen3-235B-A22B-Instruct-2507 specifies input context (262,144 tokens). Only Qwen3-235B-A22B-Instruct-2507 specifies output context (131,072 tokens).

Google
Gemini Diffusion
Input- tokens
Output- tokens
Alibaba Cloud / Qwen Team
Qwen3-235B-A22B-Instruct-2507
Input262,144 tokens
Output131,072 tokens
Mon May 25 2026 • llm-stats.com

License

Usage and distribution terms

Gemini Diffusion is licensed under a proprietary license, while Qwen3-235B-A22B-Instruct-2507 uses Apache 2.0.

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

Gemini Diffusion

Proprietary

Closed source

Qwen3-235B-A22B-Instruct-2507

Apache 2.0

Open weights

Release Timeline

When each model was launched

Gemini Diffusion was released on 2025-05-20, while Qwen3-235B-A22B-Instruct-2507 was released on 2025-07-22.

Qwen3-235B-A22B-Instruct-2507 is 2 months newer than Gemini Diffusion.

Gemini Diffusion

May 20, 2025

1.0 years ago

Qwen3-235B-A22B-Instruct-2507

Jul 22, 2025

10 months ago

2mo newer

Knowledge Cutoff

When training data ends

Neither model specifies a knowledge cutoff date.

Unable to compare the recency of their training data.

No cutoff dates available

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Key Takeaways

Google

No standout differentiators in the data we have for this pair.

Alibaba Cloud / Qwen Team
Larger context window (262,144 tokens)
Has open weights
Higher AIME 2025 score (70.3% vs 23.3%)
Higher GPQA score (77.5% vs 40.4%)

Detailed Comparison

AI Model Comparison Table
Feature
Google
Gemini Diffusion
Alibaba Cloud / Qwen Team
Qwen3-235B-A22B-Instruct-2507

FAQ

Common questions about Gemini Diffusion vs Qwen3-235B-A22B-Instruct-2507.

Which is better, Gemini Diffusion or Qwen3-235B-A22B-Instruct-2507?

Qwen3-235B-A22B-Instruct-2507 significantly outperforms across most benchmarks. Gemini Diffusion is made by Google and Qwen3-235B-A22B-Instruct-2507 is made by Alibaba Cloud / Qwen Team. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.

How does Gemini Diffusion compare to Qwen3-235B-A22B-Instruct-2507 in benchmarks?

Gemini Diffusion scores HumanEval: 89.6%, MBPP: 76.0%, Global-MMLU-Lite: 69.1%, LBPP (v2): 56.8%, BigCodeBench: 45.4%. Qwen3-235B-A22B-Instruct-2507 scores ZebraLogic: 95.0%, MMLU-Redux: 93.1%, IFEval: 88.7%, MultiPL-E: 87.9%, Creative Writing v3: 87.5%.

What are the context window sizes for Gemini Diffusion and Qwen3-235B-A22B-Instruct-2507?

Gemini Diffusion supports an unknown number of tokens and Qwen3-235B-A22B-Instruct-2507 supports 262K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between Gemini Diffusion and Qwen3-235B-A22B-Instruct-2507?

Key differences include licensing (Proprietary vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Who makes Gemini Diffusion and Qwen3-235B-A22B-Instruct-2507?

Gemini Diffusion is developed by Google and Qwen3-235B-A22B-Instruct-2507 is developed by Alibaba Cloud / Qwen Team.