Can I run it?
Can I run Qwen3.8 4B Distill on GeForce RTX 4090?
Runs great
Runs great fully on your GeForce RTX 4090 at BF16, 8K context, about 62–85 tok/s. Weights 8.07 GB plus 0.27 GB of KV cache — 8.72 GB of 22.3 GB usable. Up to 256K context still fits.
Best quantBF16
Working context8K
Max that fits256K
Speed62–85 tok/sEstimate from memory bandwidth, not a benchmark. Method.
Weights8.07 GB
KV cache0.27 GB
Total8.72 GB
Usable22.3 GB
Qwen3.8 4B Distill details · GeForce RTX 4090 page · How this estimate is made
Run commands
llama.cpp
llama-server -hf empero-ai/Qwen3.8-4B-Distill-GGUF:BF16 -c 8192 -ngl 32
Ollama
ollama run qwen3.8
LM Studio
lms get empero-ai/Qwen3.8-4B-Distill-GGUF # Then load quant BF16
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%.
- BF16 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 8K context, not at the maximum context that still fits.
Larger models that also fit
- Can I run Qwen3.8 27B on GeForce RTX 4090? — Tight fit, UD-Q6_K, 25–34 tok/s (estimate)
- Can I run gemma 4 12b it on GeForce RTX 4090? — Runs, UD-Q8_K_XL, 33–45 tok/s (estimate)
- Can I run Qwen3.5 9B on GeForce RTX 4090? — Runs, BF16, 30–42 tok/s (estimate)
Updated 2026-10-24. Profile on this page is the device default plus 32 GB of DDR5-5600 system RAM.