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text model · Gemma · Windows

Can I run Gemma 4 26B-A4B on AMD Ryzen AI Halo (128GB)?

Compatibility verdict VRAM threshold engine
Yes, it runs GPU accelerated

Yes. Gemma 4 26B-A4B runs on AMD Ryzen AI Halo (128GB) at Q4_K_M (~19 GB of ~96 GB usable).

Needs ~19 GB Device usable ~96 GB

Runs at Q4_K_M using ~19 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 ~77 GB of headroom, room to step up to FP16 for higher quality.

Q4_K_M needed
~19 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
~13.1 GB
Q3_K_M
~15 GB
Q4_K_M
~19 GB
Q5_K_M
~20.9 GB
Q6_K
~23.7 GB
Q8_0
~28.9 GB
FP16
~52.5 GB
The line marks AMD Ryzen AI Halo (128GB)'s ~96 GB budget; rungs past it are too large.

Run it

Install commands Windows

Pick your tool. All 3 load the same Q4_K_M weights.

Ollama
$ ollama run gemma4:26b-a4b
llama.cpp
$ llama-cli -hf bartowski/google_gemma-4-26B-A4B-it-GGUF:Q4_K_M
LM Studio
$ lms get bartowski/google_gemma-4-26B-A4B-it-GGUF
Model Gemma
Parameters
26.5B (MoE, 3.8B active)
Q4_K_M size
17.04 GB
Q8_0 size
26.86 GB
Context
256k
Ollama tag
gemma4:26b-a4b
Full Gemma 4 26B-A4B 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 Gemma 4 26B-A4B on other hardware

FAQ

Can AMD Ryzen AI Halo (128GB) run Gemma 4 26B-A4B?

Yes. Gemma 4 26B-A4B runs on AMD Ryzen AI Halo (128GB) at Q4_K_M (~19 GB of ~96 GB usable).

How much memory does Gemma 4 26B-A4B need?

AMD Ryzen AI Halo (128GB) has room to spare. At Q4_K_M the weights are ~17.04 GB; with KV cache and runtime overhead, budget ~19 GB at a 4k context. It is a Mixture-of-Experts model (26.5B total / 3.8B active), so all experts must stay in memory; memory tracks total params, not active params.

What is the best tool to run Gemma 4 26B-A4B 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.