Can I run it?

Can I run Swift Qwen3.8 27B on GeForce RTX 4060 Ti 8GB?

Partial offload

Partial offload on your GeForce RTX 4060 Ti 8GB: Q4_K_M at 4K context, 24 of 64 layers on the GPU and 10.4 GB in system RAM. Expect about 3.7–5.0 tok/s.

Swift Qwen3.8 27B details · GeForce RTX 4060 Ti 8GB page · How this estimate is made

Run commands

llama-server -hf ukisai/Swift-Qwen3.8-27B-GGUF:Q4_K_M -c 4096 -ngl 24

lms get ukisai/Swift-Qwen3.8-27B-GGUF
# Then load quant Q4_K_M

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%.
• Q4_K_M 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.
• About 24 of 64 layers stay on the GPU. 10.4 GB is read from system RAM.

Models that fit this machine more comfortably

• Can I run Qwen3.8 27B on GeForce RTX 4060 Ti 8GB? — Tight fit, UD-IQ1_M, 23–31 tok/s
• Can I run gemma 3 27b it on GeForce RTX 4060 Ti 8GB? — Tight fit, UD-IQ1_S, 23–31 tok/s
• Can I run medgemma 27b text it on GeForce RTX 4060 Ti 8GB? — Tight fit, UD-IQ1_S, 21–29 tok/s

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