devstral-medium-2507 vs llama-3.1-405b-instruct

Devstral Medium 2507 is a high-performance, code-centric large language model designed for agentic coding capabilities and enterprise use. It features a 128k token context window and achieves a 61.6% score on SWE-Bench Verified, outperforming several commercial models like Gemini 2.5 Pro and GPT-4.1. The model excels at code generation, multi-file editing, and powering software engineering agents with structured outputs and tool integration.

The Meta Llama 3.1 collection of multilingual large language models (LLMs) is a collection of pretrained and instruction tuned generative models in 8B, 70B and 405B sizes (text in/text out). The Llama 3.1 instruction tuned text only models (8B, 70B, 405B) are optimized for multilingual dialogue use cases and outperform many of the available open source and closed chat models on common industry benchmarks.