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Gemini 2.0 Flash Thinking vs Qwen3-235B-A22B-Instruct-2507

Gemini 2.0 Flash Thinking and Qwen3-235B-A22B-Instruct-2507 are closely matched at 16.7 and 24.2 on the LLM Stats Score.

Google · Alibaba Cloud / Qwen Team · Updated for 2026

Which is better?

Gemini 2.0 Flash Thinking and Qwen3-235B-A22B-Instruct-2507 are closely matched on the overall LLM Stats Score at 16.7 and 24.2.

In the 1 individual benchmarks reported for both models, Qwen3-235B-A22B-Instruct-2507 wins 1; this is a narrower head-to-head signal than the composite indexes.

Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.

Choose Gemini 2.0 Flash Thinking

  • you are already invested in the Google ecosystem

Choose Qwen3-235B-A22B-Instruct-2507

  • you value its reported benchmark strengths — it wins 1 of 1 exact shared results
  • you want the most recent training data — it shipped Jul 2025
  • you need open weights you can self-host or fine-tune

At a glance

The differences that matter most.

Gemini 2.0 Flash Thinking
Google
Qwen3-235B-A22B-Instruct-2507
Alibaba Cloud / Qwen Team
Core performance indexes
LLM Stats Score
16.7
#219
24.2
#166
Reasoning
17.0
#212
23.9
#161
Cost, coverage & limits
Benchmark wins
0 of 1
1 of 1
Input price
— / M
$0.09 / M
Output price
— / M
$0.55 / M
Context window
—
262,144

Individual benchmarks

3 reported for Gemini 2.0 Flash Thinking · 25 for Qwen3-235B-A22B-Instruct-2507

1 shared

Gemini 2.0 Flash Thinking outperforms in 0 benchmarks, while Qwen3-235B-A22B-Instruct-2507 is better at 1 benchmark (GPQA).

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

Mon Sep 21 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

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 (262,144 tokens).

Google
Gemini 2.0 Flash Thinking
Input- tokens
Output- tokens
Alibaba Cloud / Qwen Team
Qwen3-235B-A22B-Instruct-2507
Input262,144 tokens
Output262,144 tokens
Mon Sep 21 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Gemini 2.0 Flash Thinking supports multimodal inputs, whereas Qwen3-235B-A22B-Instruct-2507 does not.

Gemini 2.0 Flash Thinking can handle both text and other forms of data like images, making it suitable for multimodal applications.

Gemini 2.0 Flash Thinking

Text
Images
Audio
Video

Qwen3-235B-A22B-Instruct-2507

Text
Images
Audio
Video

License

Usage and distribution terms

Gemini 2.0 Flash Thinking 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 2.0 Flash Thinking

Proprietary

Closed source

Qwen3-235B-A22B-Instruct-2507

Apache 2.0

Open weights

Release Timeline

When each model was launched

Gemini 2.0 Flash Thinking was released on 2025-01-21, while Qwen3-235B-A22B-Instruct-2507 was released on 2025-07-22.

Qwen3-235B-A22B-Instruct-2507 is 6 months newer than Gemini 2.0 Flash Thinking.

Gemini 2.0 Flash Thinking

Jan 21, 2025

1.7 years ago

Qwen3-235B-A22B-Instruct-2507

Jul 22, 2025

1.2 years ago

6mo newer

Knowledge Cutoff

When training data ends

Gemini 2.0 Flash Thinking has a documented knowledge cutoff of 2024-08-01, while Qwen3-235B-A22B-Instruct-2507's cutoff date is not specified.

We can confirm Gemini 2.0 Flash Thinking's training data extends to 2024-08-01, but cannot make a direct comparison without Qwen3-235B-A22B-Instruct-2507's cutoff date.

Gemini 2.0 Flash Thinking

Aug 2024

Qwen3-235B-A22B-Instruct-2507

—

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Judge for yourself.

Run your own prompts against Gemini 2.0 Flash Thinking and Qwen3-235B-A22B-Instruct-2507 side-by-side, then vote on the output you prefer.

Gemini 2.0 Flash Thinking
✓ Preferred
Qwen3-235B-A22B-Instruct-2507
Open in Playground

FAQ

Common questions about Gemini 2.0 Flash Thinking vs Qwen3-235B-A22B-Instruct-2507.

Which is better, Gemini 2.0 Flash Thinking or Qwen3-235B-A22B-Instruct-2507?

Gemini 2.0 Flash Thinking and Qwen3-235B-A22B-Instruct-2507 are closely matched on the LLM Stats Score at 16.7 and 24.2. Gemini 2.0 Flash Thinking 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 capability indexes, individual benchmarks, pricing, and limits above.

How does Gemini 2.0 Flash Thinking compare to Qwen3-235B-A22B-Instruct-2507 in benchmarks?

Gemini 2.0 Flash Thinking scores MMMU: 75.4%, GPQA: 74.2%, AIME 2024: 73.3%. 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 2.0 Flash Thinking and Qwen3-235B-A22B-Instruct-2507?

Gemini 2.0 Flash Thinking 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 2.0 Flash Thinking and Qwen3-235B-A22B-Instruct-2507?

Key differences include LLM Stats Score (16.7 vs 24.2), multimodal support (yes vs no), licensing (Proprietary vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Who makes Gemini 2.0 Flash Thinking and Qwen3-235B-A22B-Instruct-2507?

Gemini 2.0 Flash Thinking is developed by Google and Qwen3-235B-A22B-Instruct-2507 is developed by Alibaba Cloud / Qwen Team.

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