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Can I run GLM-5.3-Flash on AMD Ryzen AI Halo (128GB)?

Compatibility verdict VRAM threshold engine
No, not enough memory would not load

No. GLM-5.3-Flash needs ~204.8 GB even at Q4_K_M, but AMD Ryzen AI Halo (128GB) only has ~96 GB usable.

Needs ~204.8 GB Device usable ~96 GB

Needs ~204.8 GB even at Q4_K_M, but only ~96 GB is usable.

That figure is at a 4k context and moves about ±15% as context length changes.

The gap is about 108.8 GB: GLM-5.3-Flash needs roughly 204.8 GB at Q4_K_M and AMD Ryzen AI Halo (128GB) leaves only about 96 GB usable for a model. No single tracked device has enough memory; GLM-5.3-Flash needs a multi-GPU or high-memory rig.

Q4_K_M needed
~204.8 GB
Usable on device
~96 GB
Device memory
128 GB
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Which quant fits

Quant ladder vs ~96 GB usable
Q2_K
~139.1 GB
Q3_K_M
~161.5 GB
Q4_K_M
~204.8 GB
Q5_K_M
~233.1 GB
Q6_K
~267.5 GB
Q8_0
~322.7 GB
FP16
~647.9 GB
The line marks AMD Ryzen AI Halo (128GB)'s ~96 GB budget; rungs past it are too large.

How to run it

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

Model GLM
Parameters
320B (MoE, 18B active)
Q4_K_M size
199.71 GB
Q8_0 size
317.56 GB
Context
1000k
Full GLM-5.3-Flash 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) →

What you can run instead

FAQ

Can AMD Ryzen AI Halo (128GB) run GLM-5.3-Flash?

No. GLM-5.3-Flash needs ~204.8 GB even at Q4_K_M, but AMD Ryzen AI Halo (128GB) only has ~96 GB usable.

How much memory does GLM-5.3-Flash need?

AMD Ryzen AI Halo (128GB) does not have enough memory. At Q4_K_M the weights are ~199.71 GB; with KV cache and runtime overhead, budget ~204.8 GB at a 4k context. It is a Mixture-of-Experts model (320B total / 18B active), so all experts must stay in memory; memory tracks total params, not active params.

What is the best tool to run GLM-5.3-Flash 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.