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.

Qwen2.5 7B Instruct
Alibaba
Qwen2.5 7B Instruct is a language model developed by Alibaba. It achieves strong performance with an average score of 65.6% across 14 benchmarks. It excels particularly in GSM8k (91.6%), MT-Bench (87.5%), HumanEval (84.8%). The model shows particular specialization in math tasks with an average performance of 83.5%. It supports a 139K 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 2024, it represents Alibaba's latest advancement in AI technology.

Qwen2.5 7B Instruct
Alibaba
2024-09-19

Gemini 2.5 Flash-Lite
2025-06-17
9 months newer
Pricing Comparison
Cost per million tokens (USD)

Gemini 2.5 Flash-Lite

Qwen2.5 7B Instruct
Performance Metrics
Context window and performance specifications

Gemini 2.5 Flash-Lite

Qwen2.5 7B Instruct
Average performance across 2 common benchmarks

Gemini 2.5 Flash-Lite

Qwen2.5 7B Instruct
Performance comparison across key benchmark categories

Gemini 2.5 Flash-Lite

Qwen2.5 7B Instruct
Gemini 2.5 Flash-Lite
2025-01-01
Provider Availability & Performance
Available providers and their performance metrics

Gemini 2.5 Flash-Lite

Qwen2.5 7B Instruct
Together

Gemini 2.5 Flash-Lite

Qwen2.5 7B Instruct