Comprehensive side-by-side LLM comparison
Gemini 2.0 Flash-Lite leads with 29.4% higher average benchmark score. Gemini 2.0 Flash-Lite offers 800.8K more tokens in context window than DeepSeek R1 Distill Qwen 32B. Both models have similar pricing. Gemini 2.0 Flash-Lite supports multimodal inputs. Overall, Gemini 2.0 Flash-Lite is the stronger choice for coding tasks.
DeepSeek
DeepSeek R1 Distill Qwen 32B is a language model developed by DeepSeek. It achieves strong performance with an average score of 74.2% across 4 benchmarks. It excels particularly in MATH-500 (94.3%), AIME 2024 (83.3%), GPQA (62.1%). It supports a 256K 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 2025, it represents DeepSeek's latest advancement in AI technology.
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.
16 days newer
DeepSeek R1 Distill Qwen 32B
DeepSeek
2025-01-20
Gemini 2.0 Flash-Lite
2025-02-05
Cost per million tokens (USD)
DeepSeek R1 Distill Qwen 32B
Gemini 2.0 Flash-Lite
Context window and performance specifications
Average performance across 16 common benchmarks
DeepSeek R1 Distill Qwen 32B
Gemini 2.0 Flash-Lite
Gemini 2.0 Flash-Lite
2024-06-01
Available providers and their performance metrics
DeepSeek R1 Distill Qwen 32B
DeepInfra
Gemini 2.0 Flash-Lite
DeepSeek R1 Distill Qwen 32B
Gemini 2.0 Flash-Lite
DeepSeek R1 Distill Qwen 32B
Gemini 2.0 Flash-Lite