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

DeepSeek-R1
DeepSeek
DeepSeek-R1 is a language model developed by DeepSeek. It achieves strong performance with an average score of 74.1% across 20 benchmarks. It excels particularly in MATH-500 (97.3%), MMLU-Redux (92.9%), CLUEWSC (92.8%). It supports a 262K token context window for handling large documents. The model is available through 4 API providers. Released in 2025, it represents DeepSeek's latest advancement in AI technology.

Gemini 2.0 Flash
Gemini 2.0 Flash is a multimodal language model developed by Google. It achieves strong performance with an average score of 66.7% across 13 benchmarks. It excels particularly in Natural2Code (92.9%), MATH (89.7%), FACTS Grounding (83.6%). 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 2024, it represents Google's latest advancement in AI technology.

Gemini 2.0 Flash
2024-12-01

DeepSeek-R1
DeepSeek
2025-01-20
1 month newer
Pricing Comparison
Cost per million tokens (USD)

DeepSeek-R1

Gemini 2.0 Flash
Performance Metrics
Context window and performance specifications

DeepSeek-R1

Gemini 2.0 Flash
Average performance across 3 common benchmarks

DeepSeek-R1

Gemini 2.0 Flash
Performance comparison across key benchmark categories

DeepSeek-R1

Gemini 2.0 Flash
Gemini 2.0 Flash
2024-08-01
Provider Availability & Performance
Available providers and their performance metrics

DeepSeek-R1
Together
DeepInfra
Fireworks
DeepSeek

Gemini 2.0 Flash

DeepSeek-R1

Gemini 2.0 Flash