Comprehensive side-by-side LLM comparison
Gemini 2.5 Flash-Lite leads with 18.3% higher average benchmark score. Gemini 2.5 Flash-Lite offers 1.0M more tokens in context window than QwQ-32B-Preview. Both models have similar pricing. Gemini 2.5 Flash-Lite supports multimodal inputs. QwQ-32B-Preview is available on 4 providers. Overall, Gemini 2.5 Flash-Lite is the stronger choice for coding tasks.
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.
Alibaba Cloud / Qwen Team
QwQ-32B-Preview is a language model developed by Alibaba Cloud / Qwen Team. It achieves strong performance with an average score of 64.0% across 4 benchmarks. It excels particularly in MATH-500 (90.6%), GPQA (65.2%), AIME 2024 (50.0%). The model is available through 4 API providers. It's licensed for commercial use, making it suitable for enterprise applications. Released in 2024, it represents Alibaba Cloud / Qwen Team's latest advancement in AI technology.
6 months newer
QwQ-32B-Preview
Alibaba Cloud / Qwen Team
2024-11-28
Gemini 2.5 Flash-Lite
2025-06-17
Cost per million tokens (USD)
Gemini 2.5 Flash-Lite
QwQ-32B-Preview
Context window and performance specifications
Average performance across 15 common benchmarks
Gemini 2.5 Flash-Lite
QwQ-32B-Preview
QwQ-32B-Preview
2024-11-28
Gemini 2.5 Flash-Lite
2025-01-01
Available providers and their performance metrics
Gemini 2.5 Flash-Lite
QwQ-32B-Preview
Gemini 2.5 Flash-Lite
QwQ-32B-Preview
Gemini 2.5 Flash-Lite
QwQ-32B-Preview
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