Can I run it?
Can I run Qwen2.5 14B Instruct on GeForce RTX 4060 Ti 8GB?
Tight fit
Tight fit fully on your GeForce RTX 4060 Ti 8GB at Q3_K_S, 2K context, about 22–31 tok/s. Weights 6.20 GB plus 0.38 GB of KV cache — 6.94 GB of 7.13 GB usable.
Best quantQ3_K_S
Working context2K
Max that fits2K
Speed22–31 tok/s
Weights6.20 GB
KV cache0.38 GB
Total6.94 GB
Usable7.13 GB
Qwen2.5 14B Instruct details · GeForce RTX 4060 Ti 8GB page · How this estimate is made
Run commands
llama.cpp
llama-server -hf bartowski/Qwen2.5-14B-Instruct-GGUF:Q3_K_S -c 2048 -ngl 48
Ollama
ollama run qwen2.5
LM Studio
lms get bartowski/Qwen2.5-14B-Instruct-GGUF # Then load quant Q3_K_S
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%.
- Q3_K_S 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 2K context, not at the maximum context that still fits.
Larger models that also fit
- Can I run Qwen3.8 27B on GeForce RTX 4060 Ti 8GB? — Tight fit, UD-IQ1_M, 23–31 tok/s
- Can I run Mistral Small 3.2 24B Instruct 2506 on GeForce RTX 4060 Ti 8GB? — Tight fit, UD-IQ1_M, 24–32 tok/s
- Can I run gemma 3 27b it on GeForce RTX 4060 Ti 8GB? — Tight fit, UD-IQ1_S, 23–31 tok/s
Updated 2026-10-17. Profile on this page is the device default plus 32 GB of DDR5-5600 system RAM.