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text model · GLM · Windows

Can I run GLM-4-32B-0414 on AMD Ryzen AI Halo (128GB)?

Compatibility verdict VRAM threshold engine
Yes, it runs GPU accelerated ~9 tok/s est.

Yes. GLM-4-32B-0414 runs on AMD Ryzen AI Halo (128GB) at Q4_K_M (~20.5 GB of ~96 GB usable).

Needs ~20.5 GB Device usable ~96 GB

Runs at Q4_K_M using ~20.5 GB of ~96 GB usable. You have room for FP16 for higher quality.

That figure is at a 4k context and moves about ±15% as context length changes. AMD Ryzen AI Halo (128GB) leaves ~75.5 GB of headroom, room to step up to FP16 for higher quality.

Q4_K_M needed
~20.5 GB
Usable on device
~96 GB
Device memory
128 GB
Best quant
Q4_K_M
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Which quant fits

Quant ladder vs ~96 GB usable
Q2_K
~15.6 GB
Q3_K_M
~17.8 GB
Q4_K_M
~20.5 GB
Q5_K_M
~25 GB
Q6_K
~28.4 GB
Q8_0
~34.4 GB
FP16
~67.3 GB
The line marks AMD Ryzen AI Halo (128GB)'s ~96 GB budget; rungs past it are too large.

Running cost · estimate

Power & economics est.
Power draw
~120 W
Electricity / 1M tokens
~$0.56

At ~$0.15/kWh and the estimated ~9 tok/s, a million generated tokens costs about $0.56 in electricity. TDP is the peak draw, so this is an upper bound. Assumptions.

Run it

Install commands Windows

Pick your tool. All 2 load the same Q4_K_M weights.

llama.cpp
$ llama-cli -hf bartowski/THUDM_GLM-4-32B-0414-GGUF:Q4_K_M
LM Studio
$ lms get bartowski/THUDM_GLM-4-32B-0414-GGUF

How to run it

On Windows use LM Studio (Best GUI on Windows, auto-detects CUDA/Vulkan backends.).

Model GLM
Parameters
32B
Q4_K_M size
18.33 GB
Q8_0 size
32.24 GB
Context
32k
Full GLM-4-32B-0414 requirements →
Device Windows
Memory
128 GB unified
Usable for weights
~96 GB
Power draw
~120 W
Best runtime
llama.cpp (Vulkan/ROCm) / LM Studio
Best models for AMD Ryzen AI Halo (128GB) →

You could also run

Run GLM-4-32B-0414 on other hardware

FAQ

Can AMD Ryzen AI Halo (128GB) run GLM-4-32B-0414?

Yes. GLM-4-32B-0414 runs on AMD Ryzen AI Halo (128GB) at Q4_K_M (~20.5 GB of ~96 GB usable).

How much memory does GLM-4-32B-0414 need?

AMD Ryzen AI Halo (128GB) has room to spare. At Q4_K_M the weights are ~18.33 GB; with KV cache and runtime overhead, budget ~20.5 GB at a 4k context.

What is the best tool to run GLM-4-32B-0414 on Windows?

LM Studio for a simple setup; Ollama (CUDA) for the most speed. AMD GPUs run via Vulkan/ROCm at roughly half CUDA throughput. NVIDIA is the smooth path on Windows.

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Sources

Weights are measured from GGUF files; KV cache and overhead are computed, so totals can vary ~15% with context and runtime. Any tok/s is a bandwidth estimate. See methodology.