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Mistral-Small-3.2-24B-Instruct-2507

mistralai/Mistral-Small-3.2-24B-Instruct-2507

Mistral-Small-3.2-24B-Instruct-2507 at Q4_K_M is exactly 14,333,910,048 bytes (13.35 GiB / 14.33 GB) — an effective 4.865 bits per weight, not the nominal 4.

From the file· summed from 1 file(s)
Parameters
23.6B
Architecture
llama
Context
native (config.json)
License

Shipped quantizations

exact bytes, summed from published files
QuantSizeExact bytesEffective bpwTensorsPublisher
Q2_K8.28 GiB8,890,326,0483.017TheDrummer
Q2_K8.28 GiB8,890,326,0483.017TheDrummer
Q2_K8.28 GiB8,890,326,0483.017TheDrummer
Q3_K_M10.69 GiB11,474,082,8483.894TheDrummer
Q3_K_M10.69 GiB11,474,082,8483.894TheDrummer
Q3_K_M10.69 GiB11,474,082,8483.894TheDrummer
Q4_K_M13.35 GiB14,333,910,0484.865TheDrummer
Q4_K_M13.35 GiB14,333,910,0484.865TheDrummer
Q4_K_M13.35 GiB14,333,910,0484.865TheDrummer
Q5_K_M15.61 GiB16,763,984,9285.689TheDrummer
Q5_K_M15.61 GiB16,763,984,9285.689TheDrummer
Q5_K_M15.61 GiB16,763,984,9285.689TheDrummer
Q6_K18.02 GiB19,345,939,4886.566TheDrummer
Q6_K18.02 GiB19,345,939,4886.566TheDrummer
Q6_K18.02 GiB19,345,939,4886.566TheDrummer
Q8_023.33 GiB25,054,780,4488.503TheDrummer
Q8_023.33 GiB25,054,780,4488.503TheDrummer
Q8_023.33 GiB25,054,780,4488.503TheDrummer

Compare with

same modality, comparable size

Will it run on your card?

full quant x context sweep

Why other calculators give a different number

A parameters × bits ÷ 8 estimate puts Q4_K_M at roughly 12.35 GiB. The real file is 13.35 GiB, because a quantization is a mixture and some tensors are always kept at higher precision.

Architecture

Architecture unavailable — this repository is gated and no ungated mirror was found. Exact file sizes above are still authoritative; only the KV math needs the config.

Questions people ask

How much VRAM does Mistral-Small-3.2-24B-Instruct-2507 need?
Q4_K_M is exactly 14,333,910,048 bytes (13.35 GiB) in weights. Add the KV cache, which depends on your context length, plus roughly half a gigabyte of runtime overhead.
Which quantization of Mistral-Small-3.2-24B-Instruct-2507 should I use?
Q4_K_M is the usual default. Pick the largest quantization that fits your card at the context you actually need — the table above gives exact sizes for every one published.