text model · Gemma · Windows
Can I run Gemma 4 26B-A4B on Nvidia GeForce RTX 4080 (16GB)?
No. Gemma 4 26B-A4B needs ~19 GB even at Q4_K_M, but Nvidia GeForce RTX 4080 (16GB) only has ~15 GB usable.
Needs ~19 GB even at Q4_K_M, but only ~15 GB is usable.
That figure is at a 4k context and moves about ±15% as context length changes.
The gap is about 4 GB: Gemma 4 26B-A4B needs roughly 19 GB at Q4_K_M and Nvidia GeForce RTX 4080 (16GB) leaves only about 15 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
- ~15 GB
- Device memory
- 16 GB
Which quant fits
- 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
- Memory
- 16 GB vram
- Usable for weights
- ~15 GB
- Power draw
- ~320 W
- Best runtime
- vLLM (Linux) / Ollama (CUDA)
What you can run instead
Run Gemma 4 26B-A4B on other hardware
FAQ
Can Nvidia GeForce RTX 4080 (16GB) run Gemma 4 26B-A4B?
No. Gemma 4 26B-A4B needs ~19 GB even at Q4_K_M, but Nvidia GeForce RTX 4080 (16GB) only has ~15 GB usable.
How much memory does Gemma 4 26B-A4B need?
Nvidia GeForce RTX 4080 (16GB) 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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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.