Alibaba
Qwen 2.5 VL 72B (72B parameters) requires approximately 50.3 GB of VRAM with Q4_K_M quantization. For the best balance of quality and speed, we recommend hardware with at least 58 GB of VRAM.
Get started
— copy & paste to run locallyCopy-paste commands to run Qwen 2.5 VL 72B on your machine.
Run
lms load Qwen2.5-VL-72B-Instruct && lms server startQuick specs
About this model
Related models
Quick picks
Best hardware
Run this model
Quantization options
No hardware detected — fit column shows raw VRAM estimates
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 28.1 GB | Low | — |
Q3_K_S | 3 | 35.3 GB | Low | — |
NVFP4 | 4 | 40.3 GB | Medium | — |
Q4_K_M | 4 | 43.9 GB | Medium | — |
Q5_K_M | 5 | 51.8 GB | High | — |
Q6_K | 6 | 59.0 GB | High | — |
Q8_0 | 8 | 77.0 GB | Very High | — |
F16 | 16 | 147.6 GB | Maximum | — |
Quality benchmarks
Reasoning
Source: community · 2025-01-26
Hardware compatibility
Computing compatibility...
Memory breakdown
Frequently asked questions
Qwen 2.5 VL 72B (72B parameters) requires approximately 50.3 GB of VRAM with Q4_K_M quantization. Lower quantizations like Q4_K_M use less memory but may reduce quality.
Yes, MacBook Pro M4 Max 96GB can run Qwen 2.5 VL 72B with a compatibility score of 88/100. It provides 96 GB of memory and achieves approximately 14.9 tokens per second.
The recommended quantization for Qwen 2.5 VL 72B is Q4_K_M, which offers the best balance between model quality and memory efficiency. Higher quantizations preserve more quality but require more VRAM.
The top recommended hardware for Qwen 2.5 VL 72B: NVIDIA H100 80GB (score: 96/100), NVIDIA H800 80GB (score: 96/100), NVIDIA GH200 96GB (score: 95/100). These provide the best combination of memory, bandwidth, and compute for running this model locally.
Yes, Qwen 2.5 VL 72B is well-suited for chat as well as vision, reasoning. It was designed with these use cases in mind.
See also
