Family Pangu · 72B parameters

Pangu Pro MoE 72B

First open Huawei release. Optimized for Ascend chips. ⚠ Custom Pangu license.

🇨🇳 Huawei·License Pangu Model License·Context 32k tokens·Output April 2025·Fits within the 128 GB of the GIGABYTE AI TOP ATOM← Catalog

01What it can do

Strengths
  • 72B total MoE
  • Good for enterprise and code
  • Open-weight available
Limitations to know
  • —42 GB VRAM Q4
  • —32k context only
  • —Huawei license needs verification
Architecture
MoE · 72B · Huawei PanGu Pro · proprietary architecture
Training
Huawei — specialized in enterprise code and Chinese business scenarios.
Ideal for
Ascend chipsCN Enterprise

04Install

Install Ollama for your OS. Check the model and its quantization before downloading. Start with 4096 tokens of context, then check placement with ollama ps. A command below is not proof that a test was run on your machine.

$ollama pull hf.co/huawei/pangu-pro-moe-72b-GGUF
⚠
First download: between 2 and 40 GB depending on the selected quantization. Plan for sufficient disk space; a stable connection is recommended. Subsequent launches are instant.

02Required memory

Approximate GPU VRAM required to run this model, including 4k tokens of context overhead. For a longer context, add ~1 GB per 8k-token increment.

Q4_K_M
The lightest, ~5% loss
42 GB
Q5_K_M
Good quality/size compromise
50 GB
Q8_0
Nearly indistinguishable from FP16
78 GB
FP16
Full precision — server use
144 GB
Fallback CPU · If you don't have a GPU, allow 72 GB of RAM minimum to run this model at reduced speed.

What hardware do you need for Pangu Pro MoE 72B?

To run Pangu Pro MoE 72B locally with Q4 quantization, you need about 42 GB of VRAM. An option to compare: BOSGAME M5 128GB / 2TB (Ryzen AI Max+ 395) — leave some headroom for the system and context; check engine compatibility with the GPU.

Current offer: BOSGAME M5 128GB / 2TB (Ryzen AI Max+ 395)
AmazonSee price →

Why this choice? Our complete guide on BOSGAME M5 128GB / 2TB (Ryzen AI Max+ 395) →

Affiliate links — possible commission at no extra cost to you; independent recommendations. As an Amazon Associate, BestLLMfor earns from qualifying purchases.

This model in your private ChatGPT, without the cloud

Too large for your machine? The kit gives you the model that fits in your VRAM

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  • PDF + files
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03Expected speed

Tokens generated per second in Q4_K_M, 4k context. Beyond 20 t/s, reading is comfortable. Below 10 t/s, that's just for testing.

Entry-level
~3t/s
GTX 1650, RX 6600, MBA M2 8GB
Mid-range
~12t/s
RTX 4060, 4070, MBP M3 Pro
High-end
~28t/s
RTX 4090, M4 Max, Radeon 7900