Can I run it?
Can I run gemma 4 26B A4B it on GeForce RTX 4070?
Tight fit
Tight fit fully on your GeForce RTX 4070 at UD-Q2_K_XL, 4K context, about 52–71 tok/s. Weights 9.82 GB plus 0.35 GB of KV cache — 10.6 GB of 10.9 GB usable.
Best quantUD-Q2_K_XL
Working context4K
Max that fits4K
Speed52–71 tok/sEstimate from memory bandwidth, not a benchmark. Method.
Weights9.82 GB
KV cache0.35 GB
Total10.6 GB
Usable10.9 GB
gemma 4 26B A4B it details · GeForce RTX 4070 page · How this estimate is made
Run commands
llama.cpp
llama-server -hf unsloth/gemma-4-26B-A4B-it-GGUF:UD-Q2_K_XL -c 4096 -ngl 30
Ollama
ollama run gemma
LM Studio
lms get unsloth/gemma-4-26B-A4B-it-GGUF # Then load quant UD-Q2_K_XL
Assumptions
- Estimate from memory bandwidth, not a benchmark. Decode speed uses 55–75% of peak bandwidth.
- KV cache is FP16. Engine overhead assumes llama.cpp (0.3 GB + 1% of the weights). Ollama is closer to 0.9 GB + 3%, LM Studio closer to 1 GB + 3%.
- UD-Q2_K_XL size is the real GGUF file size from Hugging Face.
- 0.5 GB is reserved because this GPU also drives a display, then 5% of the rest is left free.
- Speed is quoted at 4K context, not at the maximum context that still fits.
Larger models that also fit
- Can I run Qwen3.8 27B on GeForce RTX 4070? — Tight fit, UD-Q2_K_XL, 27–36 tok/s (estimate)
- Can I run Qwen3.6 35B A3B on GeForce RTX 4070? — Heavily degraded, UD-IQ2_XXS, 61–83 tok/s (estimate)
- Can I run Qwen3.5 35B A3B on GeForce RTX 4070? — Heavily degraded, UD-IQ2_XXS, 62–84 tok/s (estimate)
Updated 2026-10-24. Profile on this page is the device default plus 32 GB of DDR5-5600 system RAM.