Can I run it?
Can I run Swift Qwen3.8 27B on RTX 6000 Ada?
Runs
Runs fully on your RTX 6000 Ada at Q8_0, 8K context, about 18–24 tok/s. Weights 27.1 GB plus 0.57 GB of KV cache — 28.3 GB of 45.1 GB usable. Up to 256K context still fits.
Best quantQ8_0
Working context8K
Max that fits256K
Speed18–24 tok/s
Weights27.1 GB
KV cache0.57 GB
Total28.3 GB
Usable45.1 GB
Swift Qwen3.8 27B details · RTX 6000 Ada page · How this estimate is made
Run commands
llama.cpp
llama-server -hf ukisai/Swift-Qwen3.8-27B-GGUF:Q8_0 -c 8192 -ngl 64
No matching name in the Ollama library snapshot.
LM Studio
lms get ukisai/Swift-Qwen3.8-27B-GGUF # Then load quant Q8_0
Assumptions
- Estimate, not a benchmark. Decode speed uses a memory-bandwidth model at 55–75% of peak.
- 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%.
- Q8_0 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
- Can I run Qwen3.6 35B A3B on RTX 6000 Ada? — Runs, UD-Q8_K_XL, 151–206 tok/s
- Can I run Qwen3.8 35B A3B Distill on RTX 6000 Ada? — Runs, Q8_0, 157–214 tok/s
Updated 2026-10-24. Profile on this page is the device default plus 32 GB of DDR5-5600 system RAM.