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

Gemini 2.0 Flash-Lite
Gemini 2.0 Flash-Lite is a multimodal language model developed by Google. The model shows competitive results across 13 benchmarks. It excels particularly in MATH (86.8%), FACTS Grounding (83.6%), Global-MMLU-Lite (78.2%). 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.

Qwen2.5 VL 32B Instruct
Alibaba
Qwen2.5 VL 32B Instruct is a multimodal language model developed by Alibaba. It achieves strong performance with an average score of 63.6% across 28 benchmarks. It excels particularly in DocVQA (94.8%), Android Control Low_EM (93.3%), HumanEval (91.5%). The model shows particular specialization in code tasks with an average performance of 87.8%. As a multimodal model, it can process and understand text, images, and other input formats seamlessly. 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-Lite
2025-02-05

Qwen2.5 VL 32B Instruct
Alibaba
2025-02-28
23 days newer
Performance Metrics
Context window and performance specifications

Gemini 2.0 Flash-Lite

Qwen2.5 VL 32B Instruct
Average performance across 4 common benchmarks

Gemini 2.0 Flash-Lite

Qwen2.5 VL 32B Instruct
Performance comparison across key benchmark categories

Gemini 2.0 Flash-Lite

Qwen2.5 VL 32B Instruct
Gemini 2.0 Flash-Lite
2024-06-01
Provider Availability & Performance
Available providers and their performance metrics

Gemini 2.0 Flash-Lite

Qwen2.5 VL 32B Instruct

Gemini 2.0 Flash-Lite

Qwen2.5 VL 32B Instruct