Written by Jakub Rusinowski · Last updated July 30, 2026
Mistral AI's March 16, 2026 release unifying its former Magistral/Pixtral/Devstral lines into a single 119B-total / ~6.5B-active MoE model (128 experts, 4 active per token) with text + image input, reasoning, and agentic coding. Apache 2.0 licensed, 256K context. At Q4 it fits a single 24GB GPU (RTX 4090).
| Mistral Small 4 119B-A6.5B | Min 73 GB VRAM · Q4_K_M · 256,000 ctx · ollama run mistral-small (community GGUF quants; check tag for 119B build) |
The cheapest GPU that runs Mistral Small 4 locally (min 73 GB VRAM) is the AMD Ryzen AI Max+ 395 (96 GB).
Install Ollama then run: ollama run mistral-small (community GGUF quants; check tag for 119B build)
Minimum VRAM: 73 GB. For best results use Q4_K_M quantization.
Mistral Small 4 needs about 73 GB VRAM at Q4_K_M quantization for its smallest variant. Variants: Mistral Small 4 119B-A6.5B (73 GB, Q4_K_M). On Apple Silicon, unified memory counts toward this requirement.
Mistral Small 4's smallest variant needs about 73 GB, which exceeds a single RTX 4090 (24 GB). Use multiple GPUs, a higher-VRAM card, or Apple Silicon with large unified memory.
Q4_K_M is the best balance of quality and VRAM for Mistral Small 4 in most cases. Choose Q8_0 for near-lossless quality if you have spare VRAM, or smaller quants (Q3/Q2) only when memory is tight.
Install Ollama, then run: ollama run mistral-small (community GGUF quants; check tag for 119B build). This downloads Mistral Small 4 and starts a local, OpenAI-compatible endpoint — no internet connection is needed after the initial download.