Qwen 2.5 Coder 32B — VRAM, Speed & Local Setup

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

作者： Jakub Rusinowski · 最后更新： 2024年11月12日

Model library → Qwen 2.5 Family → Qwen 2.5 Coder 32B

The current SOTA for local coding. Matches GPT-4 in many coding benchmarks. Fits on 24GB cards.

Qwen 2.5 Coder 32B needs about 20 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.

Specifications

Parameters	32 Billion
Context window	128,000
Architecture	Dense
Provider	Alibaba Cloud
Licence	Apache 2.0
Specified at	Q4_K_M
System RAM	32 GB
Record updated	2024-11-12

Licence

Apache-2.0 — commercial use permitted. Commercial use permitted. No usage restrictions beyond attribution.

VRAM and Speed by Quantization

Modelled on a reference NVIDIA RTX 4090 (24 GB), at 8K context. Speed figures are ESTIMATES from the memory-bandwidth roofline described on the methodology page, not benchmarks we ran — rows marked measured come from published or reader-submitted runs. VRAM here includes the KV cache, so it reads higher than the headline figure above, which does not.

Quant	Weights	VRAM needed	Est. speed	Fit on 24 GB
Q2_K	10.5 GB	13.5 GB	~57 tok/s (est.)	Fits comfortably
Q3_K_M	13.6 GB	16.6 GB	~46 tok/s (est.)	Fits comfortably
Q4_K_M	19.3 GB	22.3 GB	~34 tok/s (est.)	Tight fit
Q5_K_M	22.7 GB	25.6 GB	~4 tok/s (est.)	Offloads to system RAM (slow)
Q6_K	26.2 GB	29.2 GB	~4 tok/s (est.)	Offloads to system RAM (slow)
Q8_0	34.0 GB	36.9 GB	~3 tok/s (est.)	Offloads to system RAM (slow)
F16	64.0 GB	66.9 GB	—	Won't fit

Want the memory numbers alone, at every quantization level and your own context length? Use the Qwen 2.5 Coder 32B VRAM calculator.

Buy This HardwareAMD Radeon RX 7900 XTX 24GB — 24 GB VRAM · 355 W board power Deploy in the Cloud NowRTX 4090 on RunPod — from $0.34/hr · rate checked 2026-07

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

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Recommended GPU

The cheapest catalogued GPU that runs Qwen 2.5 Coder 32B is the AMD Radeon RX 7900 XT (20 GB).

联盟营销声明: 本页部分链接为联盟推广链接——如果你通过它们购买，LLM Configurator 可能会获得佣金，而你无需支付任何额外费用。作为亚马逊联盟成员（Amazon Associate），LLM Configurator 会从符合条件的购买中获得收益。

AMD Radeon RX 7900 XT 20GB

20 GB VRAM · 315 W board power

2026年价格波动较大——请以当前商品页价格为准。

在亚马逊查看价格

How to Run Qwen 2.5 Coder 32B

Install Ollama, then run:

ollama run qwen2.5-coder:32b

Weights on Hugging Face: Qwen/Qwen2.5-Coder-32B-Instruct.

Best for: coding agent, dev work.

Can I Run Qwen 2.5 Coder 32B on My GPU?

Other Qwen 2.5 Family Sizes

Qwen 2.5 14B Instruct — about 9 GB VRAM at Q4_K_M
Qwen 2.5 7B Instruct — about 5 GB VRAM at Q4_K_M
Qwen 2.5 72B Instruct — about 44 GB VRAM at Q4_K_M

Qwen 2.5 Coder 32B — Frequently Asked Questions

How much VRAM does Qwen 2.5 Coder 32B need?

About 20 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 2.5 Coder 32B run on an RTX 4090 (24 GB)?

Yes. Qwen 2.5 Coder 32B needs about 20 GB at Q4_K_M, inside a 24 GB card, at an estimated 34 tokens/sec.

How do I run Qwen 2.5 Coder 32B locally?

Install Ollama and run `ollama run qwen2.5-coder:32b`. That pulls the weights and starts a local OpenAI-compatible endpoint; after the download nothing leaves the machine.

What other sizes does Qwen 2.5 Family come in?

Qwen 2.5 Coder 32B (20 GB), Qwen 2.5 14B Instruct (9 GB), Qwen 2.5 7B Instruct (5 GB), Qwen 2.5 72B Instruct (44 GB). Every size shares the family's training and licence; the larger ones score higher and need proportionally more memory.

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