How much VRAM does Qwen3-32B-abliterated need?

Q4_K_M is exactly 19,762,149,504 bytes (18.40 GiB) in weights. Add the KV cache, which depends on context length, plus roughly half a gigabyte of runtime overhead.

huihui-ai · text

Qwen3-32B-abliterated

huihui-ai/Qwen3-32B-abliterated

Qwen3-32B-abliterated at Q4_K_M is exactly 19,762,149,504 bytes (18.40 GiB / 19.76 GB) — an effective 4.826 bits per weight, not the nominal 4.

From the file· summed from 1 file(s)

Parameters

32.8B

Architecture

qwen3

Context

—

native (config.json)

License

apache-2.0

Shipped quantizations

● exact bytes, summed from published files

Quant	Size●	Exact bytes●	Effective bpw●	Tensors●	Publisher
Q4_K_M	18.40 GiB	19,762,149,504	4.826	—	RoadToNowhere

Compare with

same modality, comparable size

vs Qwen3-Coder-30B-A3B-Instruct vs Qwen3.6-27B vs Qwen3.8-27B vs gemma-4-E4B-it vs Qwen3-30B-A3B-Thinking-2507 vs Qwen3-4B All alternatives →Will it fit on my card? →

Why other calculators give a different number

A parameters × bits ÷ 8 estimate puts Q4_K_M at roughly 17.16 GiB. The real file is 18.40 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 Qwen3-32B-abliterated need?: Q4_K_M is exactly 19,762,149,504 bytes (18.40 GiB) in weights. Add the KV cache, which depends on your context length, plus roughly half a gigabyte of runtime overhead.
Which quantization of Qwen3-32B-abliterated 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.