Alibaba Cloud32B~21 GB VRAM at Q4_K_M

Qwen 3 32B — VRAM, speed & local setup

Name: LLM Configurator — GPU VRAM Checker
Author: LLM Configurator

Written by Jakub Rusinowski · Last updated April 28, 2025

The largest dense Qwen 3 model. Exceptional reasoning with hybrid thinking. Rivals DeepSeek R1 671B distills at a fraction of the compute. For RTX 4090 or Apple M2/M3 Max users.

Qwen 3 32B needs about 21 GB of VRAM at Q4_K_M — quantized weights plus framework overhead, before any KV cache. On Apple Silicon that figure comes out of unified memory.

Logic97

Creative88

Coding96

VRAM and speed by quantization

Quoted against NVIDIA RTX 4090 (24 GB). Includes the KV cache at 8K context, so it reads higher than the headline figure.

Quant	VRAM	Speed (est.)	Fit
Q2_K 2.63 bpw	13.7 GB	~56 tok/s	Fits
Q3_K_M 3.41 bpw	16.9 GB	~45 tok/s	Fits
Q4_K_M 4.83 bpw	22.8 GB	~33 tok/s	Tight
Q5_K_M 5.67 bpw	26.2 GB	~4 tok/s	Offload
Q6_K 6.56 bpw	29.8 GB	~4 tok/s	Offload
Q8_0 8.50 bpw	37.8 GB	~3 tok/s	Offload
F16 16.00 bpw	68.5 GB	—	Too big

Black marker = usable memory on the NVIDIA RTX 4090 (24 GB). Estimates from the memory-bandwidth roofline on the methodology page. Qwen 3 32B VRAM calculator →

Get Qwen 3 32B running

The cheapest catalogued GPU that runs Qwen 3 32B is the AMD Radeon RX 7900 XTX (24 GB).

Buy this hardware AMD Radeon RX 7900 XTX 24GB — 24 GB VRAM · 355 W board power Deploy in the cloud now RTX 4090 on RunPod — from $0.34/hr · rate checked 2026-07

or compare on Vast.ai from $0.35/hr (typical low · varies)

As an Amazon Associate we earn from qualifying purchases. Cloud GPU links are referral links — we may earn a commission at no extra cost to you.

Affiliate disclosure: Some links on this page are affiliate links — if you buy through them, LLM Configurator may earn a commission at no extra cost to you. As an Amazon Associate, LLM Configurator earns from qualifying purchases.

AMD Radeon RX 7900 XTX 24GB

24 GB VRAM · 355 W board power

2026 prices are volatile — check the current listing.

Check price on Amazon

How to run Qwen 3 32B

Install Ollama, then run:

$ollama run qwen3:32b

Weights on Hugging Face: Qwen/Qwen3-32B ↗

Specifications

Curated — A hand-written entry from before this catalogue recorded its sources. The figures are long-standing but their provenance is not on file.

Parameters: 32 Billion
Context window: 128,000
Architecture: Dense
Provider: Alibaba Cloud
Licence: Apache 2.0
Practical deployment: Single consumer GPU
Specified at: Q4_K_M
System RAM: 32 GB
Record updated: 2025-04-28

LicenceApache-2.0Commercial use permitted

Commercial use permitted. No usage restrictions beyond attribution.

Quality and use cases

Scores as published by the model’s authors or an independent evaluator — quality, not throughput, and not measured by us.

Best forcomplex reasoningcodingmathagents

Can I run Qwen 3 32B on my GPU?

Other Qwen 3 sizes

Qwen 3 32B — frequently asked questions

How much VRAM does Qwen 3 32B need?

About 21 GB at Q4_K_M — quantized weights plus framework overhead, before any KV cache. The cache grows with context length and is added on top; the table above folds it in. Apple Silicon counts unified memory toward the same figure.

Does Qwen 3 32B run on an RTX 4090 (24 GB)?

Yes. Qwen 3 32B needs about 21 GB at Q4_K_M, inside a 24 GB card, at an estimated 33 tokens/sec.

How do I run Qwen 3 32B locally?

Install Ollama and run `ollama run qwen3:32b`. That pulls the weights and starts a local OpenAI-compatible endpoint; after the download nothing leaves the machine.

What other sizes does Qwen 3 come in?

Qwen 3 8B (6 GB), Qwen 3 14B (10 GB), Qwen 3 32B (21 GB), Qwen 3 30B-A3B (MoE) (19 GB), Qwen 3 235B-A22B (MoE) (143 GB). Every size shares the family's training and licence; the larger ones score higher and need proportionally more memory.