Can an NVIDIA GeForce RTX 5080 run gemma-4-26B-A4B-it?
Yes, with CPU offload. gemma-4-26B-A4B-it needs 19.0GB at MXFP4_MOE with llama.cpp and 8K context; the NVIDIA GeForce RTX 5080 has 16GB of VRAM (15.5GB usable), so part of the model spills to system RAM — it loads, but expect the interactive speed tier.
NVIDIA GeForce RTX 5080 · gemma-4-26B-A4B-it · MXFP4_MOE
⚠️ Tight — grade C
InteractivebetaHybrid attention — KV computed as full-cache upper bound · MoE speed estimate — wide error bars · CPU offload — speed varies heavily with layer split
weights 16.6 GBKV cache 2.01 GBoverhead 0.44 GBpool 15.5 GBneeds 19.0 GB — spills to system RAM
assumes llama.cpp · batch 1 · 8K context · fp16 KV cache · 64GB system RAM (CPU offload)
$999 MSRP · as of 2026-07-08
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Every quant, graded
NVIDIA GeForce RTX 5080 × gemma-4-26B-A4B-it, llama.cpp, 8K context.
| Quant | File size | Fit | Speed tier |
|---|---|---|---|
| Q8_0 | 26.9 GB | Tight · C | interactive · offload · beta |
| UD-Q5_K_M | 21.1 GB | Tight · C | interactive · offload · beta |
| UD-Q4_K_M | 16.9 GB | Tight · C | interactive · offload · beta |
| MXFP4_MOE | 16.6 GB | Tight · C | interactive · offload · beta |
gemma-4-26B-A4B-it on similar hardware
More models on the NVIDIA GeForce RTX 5080
Verdict computed from published specs and measured GGUF file sizes — see how the math works.