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

DeepSeek-V3.1
DeepSeek
DeepSeek-V3.1 is a language model developed by DeepSeek. The model shows competitive results across 16 benchmarks. It excels particularly in SimpleQA (93.4%), MMLU-Redux (91.8%), MMLU-Pro (83.7%). The model shows particular specialization in factuality tasks with an average performance of 92.6%. It supports a 328K token context window for handling large documents. The model is available through 2 API providers. 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 2.5 Flash
Gemini 2.5 Flash is a multimodal language model developed by Google. It achieves strong performance with an average score of 62.5% across 14 benchmarks. It excels particularly in Global-MMLU-Lite (88.4%), AIME 2024 (88.0%), FACTS Grounding (85.3%). With a 1.1M token context window, it can handle extensive documents and complex multi-turn conversations. The model is available through 2 API providers. 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-V3.1
DeepSeek
2025-01-10

Gemini 2.5 Flash
2025-05-20
4 months newer
Pricing Comparison
Cost per million tokens (USD)

DeepSeek-V3.1

Gemini 2.5 Flash
Performance Metrics
Context window and performance specifications

DeepSeek-V3.1

Gemini 2.5 Flash
Average performance across 6 common benchmarks

DeepSeek-V3.1

Gemini 2.5 Flash
Performance comparison across key benchmark categories

DeepSeek-V3.1

Gemini 2.5 Flash
Gemini 2.5 Flash
2025-01-31
Provider Availability & Performance
Available providers and their performance metrics

DeepSeek-V3.1
DeepInfra
Novita

Gemini 2.5 Flash
ZeroEval

DeepSeek-V3.1

Gemini 2.5 Flash