Can I run it?
Can I run Qwen3 VL 4B Instruct on GeForce RTX 5060 Ti 8GB?
Tight fit
Tight fit fully on your GeForce RTX 5060 Ti 8GB at UD-Q8_K_XL, 8K context, about 39–54 tok/s. Weights 4.71 GB plus 1.13 GB of KV cache — 6.18 GB of 7.13 GB usable.
Best quantUD-Q8_K_XL
Working context8K
Max that fits8K
Speed39–54 tok/s
Weights4.71 GB
KV cache1.13 GB
Total6.18 GB
Usable7.13 GB
Qwen3 VL 4B Instruct details · GeForce RTX 5060 Ti 8GB page · How this estimate is made
Run commands
llama.cpp
llama-server -hf unsloth/Qwen3-VL-4B-Instruct-GGUF:UD-Q8_K_XL -c 8192 -ngl 36
Ollama
ollama run qwen3
LM Studio
lms get unsloth/Qwen3-VL-4B-Instruct-GGUF # Then load quant UD-Q8_K_XL
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%.
- UD-Q8_K_XL 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 5060 Ti 8GB? — Tight fit, UD-IQ1_M, 35–48 tok/s
- Can I run gemma 4 12b it on GeForce RTX 5060 Ti 8GB? — Tight fit, IQ4_XS, 31–42 tok/s
- Can I run Qwen3.5 9B on GeForce RTX 5060 Ti 8GB? — Tight fit, UD-Q5_K_XL, 35–48 tok/s
Updated 2026-10-24. Profile on this page is the device default plus 32 GB of DDR5-5600 system RAM.