Can I run it?
Can I run Qwen3 VL 4B Instruct on RTX 6000 Ada?
Runs great
Runs great fully on your RTX 6000 Ada at BF16, 8K context, about 57–78 tok/s. Weights 7.50 GB plus 1.13 GB of KV cache — 9.00 GB of 45.1 GB usable. Up to 256K context still fits.
Best quantBF16
Working context8K
Max that fits256K
Speed57–78 tok/sEstimate from memory bandwidth, not a benchmark. Method.
Weights7.50 GB
KV cache1.13 GB
Total9.00 GB
Usable45.1 GB
Qwen3 VL 4B Instruct details · RTX 6000 Ada page · How this estimate is made
Run commands
llama.cpp
llama-server -hf unsloth/Qwen3-VL-4B-Instruct-GGUF:BF16 -c 8192 -ngl 36
Ollama
ollama run qwen3
LM Studio
lms get unsloth/Qwen3-VL-4B-Instruct-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 RTX 6000 Ada? — Runs, UD-Q8_K_L, 18–25 tok/s (estimate)
- Can I run gemma 4 12b it on RTX 6000 Ada? — Runs great, BF16, 20–27 tok/s (estimate)
- Can I run Qwen3.5 9B on RTX 6000 Ada? — Runs great, BF16, 29–40 tok/s (estimate)
Updated 2026-10-24. Profile on this page is the device default plus 32 GB of DDR5-5600 system RAM.