How much memory does Mistral Small 3.2 24B need at Q4?

The Q4 figure used here is 15.7 GB. GGUF file size plus an FP16 KV-cache estimate at 8,192 tokens. The cache counts only the layers and heads named in the method on the About page.

What is the cheapest catalog device that runs Mistral Small 3.2 24B at Q4?

Mac mini M4 24GB, list price $799.

How fast is Mistral Small 3.2 24B on the GeForce RTX 4060 Ti 16GB, as a bandwidth estimate?

About 20.1 tok/s at Q4. That is device bandwidth divided by active weight bytes, not a measured run.

No. Mistral Small 3.2 24B does not fit on the GeForce RTX 4060 Ti 16GB at Q4. The estimate is 15.7 GB and usable memory is 15.2 GB.

Can the GeForce RTX 4060 Ti 16GB run Mistral Small 3.2 24B?

Data updated 16 October 2026. Last reviewed the same day, when this catalog snapshot was written.

Usable memory on this 16 GB VRAM config is 15.2 GB (95% of the sticker figure). A result under 2 GB of headroom is labeled tight.

Quant ladder

Estimated memory for Mistral Small 3.2 24B on GeForce RTX 4060 Ti 16GB
Quant	Estimate	Headroom	Est. tok/s	Verdict
Q4	15.7 GB	-0.5 GB	20.1 tok/s	No
Q8	26.4 GB	-11.2 GB	11.5 tok/s	No
FP16	57.6 GB	-42.4 GB	6.00 tok/s	No

GGUF file size plus an FP16 KV-cache estimate at 8,192 tokens. The cache counts only the layers and heads named in the method on the About page.
Formula estimate: parameter count × bytes per weight × 1.20. No GGUF file size is stored for this quant.
Tokens/sec is a bandwidth roofline: GB/s divided by active weight GB. It is not a measured generation speed.

KV cache at 8K and 32K

FP16 KV-cache estimate: 1.3 GB at 8,192 tokens and 5.4 GB at 32,768 tokens. GQA counts two tensors (K and V) for the stored KV heads and head dimension.

Offload

The Q4 weight estimate fits in usable VRAM, so this page does not assume a system-RAM offload.

Ollama

This command pulls the Q4_K_M file from unsloth/Mistral-Small-3.2-24B-Instruct-2506-GGUF, the Hub repo whose file size is used above. It is not an official Ollama library tag.

ollama run hf.co/unsloth/Mistral-Small-3.2-24B-Instruct-2506-GGUF:Q4_K_M

What fits instead

Cheapest catalog device at Q4: Mac mini M4 24GB
Closest catalog model that still fits at Q4: gpt-oss-20b.

All hardware for Mistral Small 3.2 24B · All models for the GeForce RTX 4060 Ti 16GB

Questions

How much memory does Mistral Small 3.2 24B need at Q4?: The Q4 figure used here is 15.7 GB. GGUF file size plus an FP16 KV-cache estimate at 8,192 tokens. The cache counts only the layers and heads named in the method on the About page.
Can the GeForce RTX 4060 Ti 16GB run Mistral Small 3.2 24B?: No. Mistral Small 3.2 24B does not fit on the GeForce RTX 4060 Ti 16GB at Q4. The estimate is 15.7 GB and usable memory is 15.2 GB.
What is the cheapest catalog device that runs Mistral Small 3.2 24B at Q4?: Mac mini M4 24GB, list price $799.
How fast is Mistral Small 3.2 24B on the GeForce RTX 4060 Ti 16GB, as a bandwidth estimate?: About 20.1 tok/s at Q4. That is device bandwidth divided by active weight bytes, not a measured run.