Can I run it?

Can I run Qwen3.8 2B Distill on GeForce RTX 5090?

Runs great

Runs great fully on your GeForce RTX 5090 at BF16, 8K context, about 247–336 tok/s. Weights 3.63 GB plus 0.10 GB of KV cache — 4.07 GB of 29.9 GB usable. Up to 256K context still fits.

Qwen3.8 2B Distill details · GeForce RTX 5090 page · How this estimate is made

Run commands

llama-server -hf empero-ai/Qwen3.8-2B-Distill-GGUF:BF16 -c 8192 -ngl 24

ollama run qwen3.8

lms get empero-ai/Qwen3.8-2B-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 5090? — Tight fit, UD-Q8_K_L, 34–47 tok/s (estimate)
• Can I run gemma 4 12b it on GeForce RTX 5090? — Runs, BF16, 36–50 tok/s (estimate)
• Can I run Qwen3.5 9B on GeForce RTX 5090? — Runs great, BF16, 54–74 tok/s (estimate)

Updated 2026-10-24. Profile on this page is the device default plus 32 GB of DDR5-5600 system RAM.