Can I run it?
Can I run Qwen2.5 VL 7B Instruct on Intel Arc A770 16GB?
Runs
Runs fully on your Intel Arc A770 16GB at UD-Q8_K_XL, 8K context, about 29–39 tok/s. Weights 9.49 GB plus 0.44 GB of KV cache — 10.3 GB of 14.7 GB usable. Up to 64K context still fits.
Best quantUD-Q8_K_XL
Working context8K
Max that fits64K
Speed29–39 tok/s
Weights9.49 GB
KV cache0.44 GB
Total10.3 GB
Usable14.7 GB
Qwen2.5 VL 7B Instruct details · Intel Arc A770 16GB page · How this estimate is made
Run commands
llama.cpp
llama-server -hf unsloth/Qwen2.5-VL-7B-Instruct-GGUF:UD-Q8_K_XL -c 8192 -ngl 28
Ollama
ollama run qwen2.5
LM Studio
lms get unsloth/Qwen2.5-VL-7B-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 Intel Arc A770 16GB? — Tight fit, UD-IQ4_XS, 21–28 tok/s
- Can I run gemma 4 12b it on Intel Arc A770 16GB? — Tight fit, UD-Q8_K_XL, 18–25 tok/s
- Can I run Qwen3.5 9B on Intel Arc A770 16GB? — Tight fit, UD-Q8_K_XL, 23–32 tok/s
Updated 2026-10-24. Profile on this page is the device default plus 32 GB of DDR5-5600 system RAM.