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

Gemini 2.5 Flash-Lite
Gemini 2.5 Flash-Lite is a multimodal language model developed by Google. The model shows competitive results across 13 benchmarks. It excels particularly in FACTS Grounding (84.1%), Global-MMLU-Lite (81.1%), MMMU (72.9%). With a 1.1M token context window, it can handle extensive documents and complex multi-turn conversations. The model is available through 1 API provider. 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.

Qwen3-235B-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.

Gemini 2.5 Flash-Lite
2025-06-17

Qwen3-235B-A22B-Instruct-2507
Alibaba
2025-07-22
1 month newer
Performance Metrics
Context window and performance specifications

Gemini 2.5 Flash-Lite

Qwen3-235B-A22B-Instruct-2507
Average performance across 3 common benchmarks

Gemini 2.5 Flash-Lite

Qwen3-235B-A22B-Instruct-2507
Performance comparison across key benchmark categories

Gemini 2.5 Flash-Lite

Qwen3-235B-A22B-Instruct-2507
Gemini 2.5 Flash-Lite
2025-01-01
Provider Availability & Performance
Available providers and their performance metrics

Gemini 2.5 Flash-Lite

Qwen3-235B-A22B-Instruct-2507

Gemini 2.5 Flash-Lite

Qwen3-235B-A22B-Instruct-2507