Model Comparison

Comprehensive side-by-side analysis of model capabilities and performance

Google

Gemini 2.0 Flash Thinking

Google

Gemini 2.0 Flash Thinking is a multimodal language model developed by Google. It achieves strong performance with an average score of 74.3% across 3 benchmarks. Notable strengths include MMMU (75.4%), GPQA (74.2%), AIME 2024 (73.3%). As a multimodal model, it can process and understand text, images, and other input formats seamlessly. Released in 2025, it represents Google's latest advancement in AI technology.

Alibaba

Qwen3-235B-A22B-Instruct-2507

Alibaba

Qwen3-235B-A22B-Instruct-2507 is a language model developed by Alibaba. It achieves strong performance with an average score of 72.1% across 25 benchmarks. It excels particularly in ZebraLogic (95.0%), MMLU-Redux (93.1%), IFEval (88.7%). It's licensed for commercial use, making it suitable for enterprise applications. Released in 2025, it represents Alibaba's latest advancement in AI technology.

Google

Gemini 2.0 Flash Thinking

Google

2025-01-21

Alibaba

Qwen3-235B-A22B-Instruct-2507

Alibaba

2025-07-22

6 months newer

Average performance across 1 common benchmarks

Google

Gemini 2.0 Flash Thinking

Average Score:74.2%
Alibaba

Qwen3-235B-A22B-Instruct-2507

+3.3%
Average Score:77.5%

Performance comparison across key benchmark categories

Google

Gemini 2.0 Flash Thinking

general
+0.1%
73.8%
Alibaba

Qwen3-235B-A22B-Instruct-2507

general
73.7%
Benchmark Scores - Detailed View
Side-by-side comparison of all benchmark scores
Knowledge Cutoff
Training data recency comparison

Gemini 2.0 Flash Thinking

2024-08-01

More recent knowledge cutoff means awareness of newer technologies and frameworks

Provider Availability & Performance

Available providers and their performance metrics

Google

Gemini 2.0 Flash Thinking

0 providers
Alibaba

Qwen3-235B-A22B-Instruct-2507

0 providers
Google

Gemini 2.0 Flash Thinking

Avg Score:74.2%
Providers:0
Alibaba

Qwen3-235B-A22B-Instruct-2507

+3.3%
Avg Score:77.5%
Providers:0