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.

Qwen3 235B A22B
Alibaba
Qwen3 235B A22B is a language model developed by Alibaba. It achieves strong performance with an average score of 76.2% across 23 benchmarks. It excels particularly in Arena Hard (95.6%), GSM8k (94.4%), BBH (88.9%). The model shows particular specialization in math tasks with an average performance of 83.3%. It supports a 256K token context window for handling large documents. The model is available through 4 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-Lite
2025-02-05

Qwen3 235B A22B
Alibaba
2025-04-29
2 months newer
Pricing Comparison
Cost per million tokens (USD)

Gemini 2.0 Flash-Lite

Qwen3 235B A22B
Performance Metrics
Context window and performance specifications

Gemini 2.0 Flash-Lite

Qwen3 235B A22B
Average performance across 3 common benchmarks

Gemini 2.0 Flash-Lite

Qwen3 235B A22B
Performance comparison across key benchmark categories

Gemini 2.0 Flash-Lite

Qwen3 235B A22B
Gemini 2.0 Flash-Lite
2024-06-01
Provider Availability & Performance
Available providers and their performance metrics

Gemini 2.0 Flash-Lite

Qwen3 235B A22B
Together
DeepInfra
Fireworks
Novita

Gemini 2.0 Flash-Lite

Qwen3 235B A22B