Comprehensive side-by-side LLM comparison
Gemini 2.5 Pro leads with 9.8% higher average benchmark score. Gemini 2.5 Pro offers 872.2K more tokens in context window than DeepSeek-R1. DeepSeek-R1 is $8.51 cheaper per million tokens. Gemini 2.5 Pro supports multimodal inputs. Overall, Gemini 2.5 Pro is the stronger choice for coding tasks.
DeepSeek
DeepSeek-R1, released by DeepSeek on January 20, 2025, is a large reasoning model with 671 billion total parameters (37 billion active in its MoE architecture) designed for extended chain-of-thought reasoning. It features a 128K token context window and demonstrated strong performance on mathematics, coding, and scientific reasoning benchmarks at its release. DeepSeek-R1 targets complex analytical tasks, competitive programming, and applications requiring deep deliberative reasoning under an open MIT license.
Google DeepMind
Gemini 2.5 Pro, released by Google in May 2025, is a large language model from the Gemini 2.5 family designed for complex reasoning, coding, and long-context analysis tasks. It features a 1M token context window, native support for text, image, video, and audio input, and integrated thinking capabilities for multi-step problem solving. Gemini 2.5 Pro targets advanced coding workflows, scientific reasoning, and applications requiring deep understanding across large, mixed-modality contexts.
4 months newer

DeepSeek-R1
DeepSeek
2025-01-20

Gemini 2.5 Pro
Google DeepMind
2025-05-20
Cost per million tokens (USD)
DeepSeek-R1
Gemini 2.5 Pro
Context window and performance specifications
Average performance across 2 common benchmarks
DeepSeek-R1
Gemini 2.5 Pro
Performance comparison across key benchmark categories
DeepSeek-R1
Gemini 2.5 Pro
Available providers and their performance metrics
DeepSeek-R1
DeepSeek
Gemini 2.5 Pro
DeepSeek-R1
Gemini 2.5 Pro
DeepSeek-R1
Gemini 2.5 Pro
Google Cloud Vertex AI