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Ministral 3 3B

Ministral 3 3B loads in 3 GB at Q4_K_M, comfortably from 8 GB of memory, Macs included, starting at the Mac Mini M6 16GB. Below is the memory math we ran for it, the smallest card that fits, and the fastest machine we track.

PARAMETERS
3.4B
FORMAT
Q4_K_M
MIN MEMORY
6 GB
BEST FOR
Chat, Vision, Edge

How much memory does Ministral 3 3B need?

Ministral 3 3B is a 3.4B dense model built for chat, vision, edge. The weights alone take 3 GB at Q4_K_M; add context and the OS, and it belongs in the 8 GB memory class. Every number below comes from the ModelFit engine: speeds are estimates, labeled est., because we do not benchmark hardware ourselves.

Weights (Q4_K_M)
3 GB
+ KV cache (16k)
~1.8 GB
Total at 16k
~4.8 GB
Comfortable from
8 GB

KV = fp16 estimate (q8_0 cache roughly halves it). "Comfortable" = weights + KV within the engine's tiered budget (~70-85% of memory).

Which machines run Ministral 3 3B?

Smallest GPU
~62 tok/s est. · 8 GB VRAM
Fastest
~300 tok/s est.
Runs on a Mac?
~66 tok/s est.

Verdicts come from the same engine that powers our fit checker: memory capacity first, bandwidth for speed. How we compute these numbers · Hugging Face model card

More Mistral models

Frequently asked questions

How much memory does Ministral 3 3B need?

3 GB for the Q4_K_M weights, plus ~1.8 GB of KV-cache at 16k context, about 4.8 GB total. Comfortable from 8 GB of VRAM or unified memory.

Does Ministral 3 3B run on a Mac?

Yes, from the Mac Mini M6 16GB (~66 tok/s est.). Unified memory means the RAM budget is the only limit.

What is the smallest GPU for Ministral 3 3B?

The NVIDIA GeForce RTX 4060 (8 GB VRAM) is the smallest tracked card that runs Ministral 3 3B comfortably, ~62 tok/s est.

Cite this page

ModelFit: Ministral 3 3B, specs, memory math and hardware verdicts.
https://modelfit.io/models/ministral-3-3b/ (dataset updated 2026-10-13, CC BY 4.0).