Family Mistral · 119B parameters★ Made in France

Mistral Small 4

119B/6.5B active MoE unifies chat + reasoning + vision + code. The French flagship of 2026.

🇫🇷 Mistral AI·License Apache 2.0·Context 250k tokens·Output March 2026·Fits within the 128 GB of the GIGABYTE AI TOP ATOM← Catalog

01What it can do

Strengths
  • Flagship French MoE
  • Unifies 4 Mistral products
  • 256k ctx
  • Apache 2.0
Limitations to know
  • —72+ GB in Q4 — prosumer workstation
  • —Breaks Small 3.x continuity
Architecture
119B/6.5B active MoE · 256k ctx · unifies instruct+reasoning+vision+code
Training
Replaces Small 3.x and Pixtral in a single model.
Ideal for
AgentsVisionCodeReasoning

04Install

Install Ollama for your OS. Check the model and its quantization before downloading. Start with 4096 tokens of context, then check placement with ollama ps. A command below is not proof that a test was run on your machine.

$# HuggingFace : mistralai/Mistral-Small-4 (pas encore de tag Ollama officiel)
⚠
First download: between 2 and 40 GB depending on the selected quantization. Plan for sufficient disk space; a stable connection is recommended. Subsequent launches are instant.

02Required memory

Approximate GPU VRAM required to run this model, including 4k tokens of context overhead. For a longer context, add ~1 GB per 8k-token increment.

Q4_K_M
The lightest, ~5% loss
72 GB
Q5_K_M
Good quality/size compromise
86 GB
Q8_0
Nearly indistinguishable from FP16
128 GB
FP16
Full precision — server use
238 GB
Fallback CPU · If you don't have a GPU, allow 96 GB of RAM minimum to run this model at reduced speed.

What hardware do you need for Mistral Small 4?

To run Mistral Small 4 locally with Q4 quantization, you need about 72 GB of VRAM. An option to compare: BOSGAME M5 128GB / 2TB (Ryzen AI Max+ 395) — leave some headroom for the system and context; check engine compatibility with the GPU.

Current offer: BOSGAME M5 128GB / 2TB (Ryzen AI Max+ 395)
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Why this choice? Our complete guide on BOSGAME M5 128GB / 2TB (Ryzen AI Max+ 395) →

Affiliate links — commission possible at no extra cost to you; independent recommendations. As an Amazon Associate, BestLLMfor earns from qualifying purchases.

03Expected speed

Tokens generated per second in Q4_K_M, 4k context. Beyond 20 t/s, reading is comfortable. Below 10 t/s, that's just for testing.

Entry-level
~3t/s
GTX 1650, RX 6600, MBA M2 8GB
Mid-range
~12t/s
RTX 4060, 4070, MBP M3 Pro
High-end
~30t/s
RTX 4090, M4 Max, Radeon 7900