Comprehensive side-by-side LLM comparison
Qwen3-235B-A22B-Thinking-2507 leads with 55.8% higher average benchmark score. Gemini 2.0 Flash Thinking supports multimodal inputs. Overall, Qwen3-235B-A22B-Thinking-2507 is the stronger choice for coding tasks.
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 Cloud / Qwen Team
Qwen3-235B-A22B-Thinking-2507 is a language model developed by Alibaba Cloud / Qwen Team. It achieves strong performance with an average score of 69.2% across 25 benchmarks. It excels particularly in MMLU-Redux (93.8%), AIME 2025 (92.3%), WritingBench (88.3%). It supports a 387K token context window for handling large documents. The model is available through 1 API provider. It's licensed for commercial use, making it suitable for enterprise applications. Released in 2025, it represents Alibaba Cloud / Qwen Team's latest advancement in AI technology.
6 months newer
Gemini 2.0 Flash Thinking
2025-01-21
Qwen3-235B-A22B-Thinking-2507
Alibaba Cloud / Qwen Team
2025-07-25
Context window and performance specifications
Average performance across 27 common benchmarks
Gemini 2.0 Flash Thinking
Qwen3-235B-A22B-Thinking-2507
Gemini 2.0 Flash Thinking
2024-08-01
Available providers and their performance metrics
Gemini 2.0 Flash Thinking
Qwen3-235B-A22B-Thinking-2507
Novita
Gemini 2.0 Flash Thinking
Qwen3-235B-A22B-Thinking-2507
Gemini 2.0 Flash Thinking
Qwen3-235B-A22B-Thinking-2507