GPUs/Intel Arc A750/Qwen 2.5 14B

Can Intel Arc A750 run Qwen 2.5 14B?

14B parameter LLM model on 8GB GDDR6

Barely — requires CPU/RAM offloading
~1-3 tok/s (offload)
SpeedVery slow — expect 1-3 tokens/sec
QualityQuality is fine but the speed makes it impractical for interactive use
Intel GPUs lack CUDA. While Qwen 2.5 14B can technically run via llama.cpp/GGUF, the setup is more complex and less optimized than on NVIDIA hardware.

VRAM Requirements

Qwen 2.5 14B is a 14B parameter model. At full precision (FP16), it requires 28GB of VRAM. Your Intel Arc A750 only has 8GB — not enough even at maximum compression.

FP16 (Full Precision)28GB (need 20GB more)

Maximum quality, no quantization

Q8 (8-bit)14GB (need 6GB more)

Near-lossless, ~50% size reduction

Q4 (4-bit)9GB (need 1GB more)

Good quality, ~75% size reduction

Your GPU VRAM: 8GB GDDR6 at 512 GB/s bandwidth
Recommended system RAM: 32GB DDR5 (2x GPU VRAM minimum for model overflow)

How to Set It Up

Step 1: Install Ollama

curl -fsSL https://ollama.com/install.sh | sh

Ollama is the easiest way to run local LLMs. Works on Linux, macOS, and Windows.

Step 2: Download and run Qwen 2.5 14B

ollama run qwen2.5:14b:q4_K_M

This downloads the model (~14GB). First run takes a few minutes.

Step 3: Verify GPU is being used

rocm-smi

Check that VRAM usage increases when the model loads. You should see ~9GB used.

Intel Arc A750 Specs

VRAM8GB GDDR6
Memory Bandwidth512 GB/s
TDP225W
CUDA CoresN/A
Street Price~$160
AI Rating1/10

About Qwen 2.5 14B

Good balance of quality and speed. Fits on 12–16GB GPUs at Q4-Q8.

Category: LLM · Parameters: 14B · CUDA required: No (runs via llama.cpp/GGUF)