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

Gemini 2.0 Flash Thinking
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.

Qwen3 32B
Alibaba
Qwen3 32B is a language model developed by Alibaba. It achieves strong performance with an average score of 75.3% across 9 benchmarks. It excels particularly in CodeForces (95.2%), Arena Hard (93.8%), AIME 2024 (81.4%). The model shows particular specialization in code tasks with an average performance of 80.4%. It supports a 256K token context window for handling large documents. The model is available through 3 API providers. It's licensed for commercial use, making it suitable for enterprise applications. Released in 2025, it represents Alibaba's latest advancement in AI technology.

Gemini 2.0 Flash Thinking
2025-01-21

Qwen3 32B
Alibaba
2025-04-29
3 months newer
Performance Metrics
Context window and performance specifications

Gemini 2.0 Flash Thinking

Qwen3 32B
Average performance across 1 common benchmarks

Gemini 2.0 Flash Thinking

Qwen3 32B
Performance comparison across key benchmark categories

Gemini 2.0 Flash Thinking

Qwen3 32B
Gemini 2.0 Flash Thinking
2024-08-01
Provider Availability & Performance
Available providers and their performance metrics

Gemini 2.0 Flash Thinking

Qwen3 32B
Sambanova
DeepInfra
Novita

Gemini 2.0 Flash Thinking

Qwen3 32B