Comprehensive side-by-side LLM comparison
GPT-4.1 nano offers 816.2K more tokens in context window than Devstral-2-123B. GPT-4.1 nano is $3.50 cheaper per million tokens. GPT-4.1 nano 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.
OpenAI
GPT-4.1 nano is OpenAI's smallest member of the GPT-4.1 family, released in April 2025 alongside GPT-4.1 and GPT-4.1 mini as the latency-optimized, cost-minimized option for high-throughput applications. Positioned below GPT-4.1 mini in both size and cost, it was designed for use cases where speed and affordability dominate over raw capability — including tool calling, intent classification, short-form instruction following, and retrieval-augmented lookup tasks. Unlike its larger siblings, it supports fine-tuning, making it a practical candidate for task-specific customization at scale without incurring the cost of fine-tuning larger models.
7 months newer

GPT-4.1 nano
OpenAI
2025-04-14

Devstral-2-123B
Mistral AI
2025-12-09
Cost per million tokens (USD)
Devstral-2-123B
GPT-4.1 nano
Context window and performance specifications
GPT-4.1 nano
2024-06
Available providers and their performance metrics
Devstral-2-123B
OpenRouter
GPT-4.1 nano
Devstral-2-123B
GPT-4.1 nano
Devstral-2-123B
GPT-4.1 nano
OpenAI