Comprehensive side-by-side LLM comparison
Gemini 3.1 Pro offers 978.1K more tokens in context window than DeepSeek-R1. DeepSeek-R1 is $11.26 cheaper per million tokens. Gemini 3.1 Pro supports multimodal inputs. Both models have their strengths depending on your specific coding needs.
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 3.1 Pro is a multimodal language model from Google DeepMind, released in preview in February 2026 as a point-version upgrade to Gemini 3 Pro focused on improving reasoning depth, factual grounding, and coding and agentic task performance. The model accepts text, images, video, audio, and PDFs as inputs across a 1M token context window, extending the multimodal breadth of the Gemini 3 series with a companion endpoint specifically optimized for custom tool use in agentic pipelines. Google describes it as built to refine the reliability and performance of the Gemini 3 Pro series, reflecting an incremental engineering iteration rather than an architectural overhaul.
1 year newer

DeepSeek-R1
DeepSeek
2025-01-20

Gemini 3.1 Pro
Google DeepMind
2026-02-19
Cost per million tokens (USD)
DeepSeek-R1
Gemini 3.1 Pro
Context window and performance specifications
Gemini 3.1 Pro
2025-01
Available providers and their performance metrics
DeepSeek-R1
DeepSeek
Gemini 3.1 Pro
DeepSeek-R1
Gemini 3.1 Pro
DeepSeek-R1
Gemini 3.1 Pro