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

DeepSeek R1 Zero
DeepSeek
DeepSeek R1 Zero is a language model developed by DeepSeek. It achieves strong performance with an average score of 76.5% across 4 benchmarks. It excels particularly in MATH-500 (95.9%), AIME 2024 (86.7%), GPQA (73.3%). 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
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.

DeepSeek R1 Zero
DeepSeek
2025-01-20

Gemini 2.0 Flash-Lite
2025-02-05
16 days newer
Performance Metrics
Context window and performance specifications

DeepSeek R1 Zero

Gemini 2.0 Flash-Lite
Average performance across 1 common benchmarks

DeepSeek R1 Zero

Gemini 2.0 Flash-Lite
Performance comparison across key benchmark categories

DeepSeek R1 Zero

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

DeepSeek R1 Zero

Gemini 2.0 Flash-Lite

DeepSeek R1 Zero

Gemini 2.0 Flash-Lite