Comprehensive side-by-side LLM comparison
. 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.
NVIDIA
Llama-3.1-Nemotron-Nano-8B-v1 is an 8-billion-parameter model from NVIDIA, developed as a fine-tuned variant of Meta's Llama 3.1 8B using NVIDIA's Nemotron post-training methodology, which applies reinforcement learning and process reward modeling to enhance instruction-following and reasoning capability over the base model. The Nano designation marks it as the entry-level member of the Nemotron family, optimized for efficient inference on a single GPU while delivering meaningfully improved performance on instruction alignment and agentic tasks compared to standard Llama 3.1. Released open-weight on HuggingFace, it is designed for deployment in NVIDIA-accelerated environments and supports NVIDIA NIM for enterprise inference.
11 months newer

Llama 3.1 Nemotron Nano 8B
NVIDIA
2025-01-06

Devstral-2-123B
Mistral AI
2025-12-09
Context window and performance specifications
Available providers and their performance metrics
Devstral-2-123B
OpenRouter
Llama 3.1 Nemotron Nano 8B
Devstral-2-123B
Llama 3.1 Nemotron Nano 8B
Devstral-2-123B
Llama 3.1 Nemotron Nano 8B