Comprehensive side-by-side LLM comparison
Gemini 3.1 Pro offers 849.9K more tokens in context window than Devstral-2-123B. Devstral-2-123B is $10.00 cheaper per million tokens. Gemini 3.1 Pro supports multimodal inputs. Both models have their strengths depending on your specific coding needs.
Mistral AI
Devstral 2, released by Mistral AI on December 9, 2025, is a 123 billion parameter dense transformer model specifically designed for software engineering tasks. It features a 256K token context window and achieved 72.2% on SWE-bench Verified at release, making it a competitive open-weight option for automated coding and agentic development. Devstral 2 targets code generation, multi-file software engineering, and agentic development workflows under a modified 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.
2 months newer

Devstral-2-123B
Mistral AI
2025-12-09

Gemini 3.1 Pro
Google DeepMind
2026-02-19
Cost per million tokens (USD)
Devstral-2-123B
Gemini 3.1 Pro
Context window and performance specifications
Gemini 3.1 Pro
2025-01
Available providers and their performance metrics
Devstral-2-123B
OpenRouter
Gemini 3.1 Pro
Devstral-2-123B
Gemini 3.1 Pro
Devstral-2-123B
Gemini 3.1 Pro