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text model · Gemma · Windows

Can I run Gemma 4 26B-A4B on Nvidia GeForce RTX 3060 (12GB)?

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

No. Gemma 4 26B-A4B needs ~19 GB even at Q4_K_M, but Nvidia GeForce RTX 3060 (12GB) only has ~11 GB usable.

Needs ~19 GB Device usable ~11 GB

Needs ~19 GB even at Q4_K_M, but only ~11 GB is usable.

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

The gap is about 8 GB: Gemma 4 26B-A4B needs roughly 19 GB at Q4_K_M and Nvidia GeForce RTX 3060 (12GB) leaves only about 11 GB usable for a model. The lightest tracked hardware that runs Gemma 4 26B-A4B is the Nvidia GeForce RTX 4090 (24GB) at 24 GB. See Gemma 4 26B-A4B on Nvidia GeForce RTX 4090 (24GB).

Q4_K_M needed
~19 GB
Usable on device
~11 GB
Device memory
12 GB
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Which quant fits

Quant ladder vs ~11 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 Nvidia GeForce RTX 3060 (12GB)'s ~11 GB budget; rungs past it are too large.
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
12 GB vram
Usable for weights
~11 GB
Power draw
~170 W
Best runtime
Ollama (CUDA) / llama.cpp CUDA
Best models for Nvidia GeForce RTX 3060 (12GB) →

What you can run instead

Run Gemma 4 26B-A4B on other hardware

FAQ

Can Nvidia GeForce RTX 3060 (12GB) run Gemma 4 26B-A4B?

No. Gemma 4 26B-A4B needs ~19 GB even at Q4_K_M, but Nvidia GeForce RTX 3060 (12GB) only has ~11 GB usable.

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

Nvidia GeForce RTX 3060 (12GB) does not have enough memory. 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.