Comprehensive side-by-side LLM comparison
. Both models have their strengths depending on your specific coding needs.
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.
Mistral AI
Mistral Small 3.1 is a 24-billion-parameter multimodal model from Mistral AI, released in March 2025 as an update to Mistral Small 3 that added vision understanding and expanded the context window from 32K to 128K tokens. The model accepts both text and image inputs, broadening its applicability to document analysis, image-grounded reasoning, and mixed-media workflows without requiring an increase in parameter count. Released under Apache 2.0, it continued Mistral's pattern of incremental capability gains delivered in compact, practically deployable open-weight packages.
28 days newer

Mistral Small 3.1 24B Instruct
Mistral AI
2025-03-17

GPT-4.1 nano
OpenAI
2025-04-14
Context window and performance specifications
GPT-4.1 nano
2024-06
Available providers and their performance metrics
GPT-4.1 nano
OpenAI
Mistral Small 3.1 24B Instruct
GPT-4.1 nano
Mistral Small 3.1 24B Instruct
GPT-4.1 nano
Mistral Small 3.1 24B Instruct