Comprehensive side-by-side LLM comparison
Gemini 2.5 Pro leads with 6.5% higher average benchmark score. Gemini 2.5 Pro offers 872.2K more tokens in context window than DeepSeek-V3.1. DeepSeek-V3.1 is $9.88 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-V3.1, released by DeepSeek in August 2025, is a hybrid large language model with 671 billion total parameters (37 billion active) that unifies the capabilities of DeepSeek-V3 and DeepSeek-R1 in a single model. It features a 128K token context window and supports both direct generation and extended reasoning modes selectable via the chat template. DeepSeek-V3.1 targets general-purpose tasks, coding, and complex 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.
3 months newer

Gemini 2.5 Pro
Google DeepMind
2025-05-20

DeepSeek-V3.1
DeepSeek
2025-08-21
Cost per million tokens (USD)
DeepSeek-V3.1
Gemini 2.5 Pro
Context window and performance specifications
Average performance across 1 common benchmarks
DeepSeek-V3.1
Gemini 2.5 Pro
Performance comparison across key benchmark categories
DeepSeek-V3.1
Gemini 2.5 Pro
Available providers and their performance metrics
DeepSeek-V3.1
DeepSeek
Gemini 2.5 Pro
DeepSeek-V3.1
Gemini 2.5 Pro
DeepSeek-V3.1
Gemini 2.5 Pro
Google Cloud Vertex AI