text model · Qwen2.5-Coder · Windows
Can I run Qwen2.5 Coder 0.5B on 8GB RAM Laptop (CPU/iGPU only)?
Yes. Qwen2.5 Coder 0.5B runs on 8GB RAM Laptop (CPU/iGPU only) at Q4_K_M (~1.4 GB of ~5 GB usable).
Runs at Q4_K_M using ~1.4 GB of ~5 GB usable. You have room for FP16 for higher quality.
- Q4_K_M needed
- ~1.4 GB
- Usable on device
- ~5 GB
- Device memory
- 8 GB
- Best quant
- Q4_K_M
Run it
Pick your tool. All three load the same Q4_K_M weights.
ollama run qwen2.5-coder:0.5b llama-cli -hf bartowski/Qwen2.5-Coder-0.5B-Instruct-GGUF:Q4_K_M lms get bartowski/Qwen2.5-Coder-0.5B-Instruct-GGUF AMD GPUs run via Vulkan/ROCm at roughly half CUDA throughput. NVIDIA is the smooth path on Windows.
- Parameters
- 0.494B
- Q4_K_M size
- 0.37 GB
- Q8_0 size
- 0.49 GB
- Context
- 32k
- Ollama tag
- qwen2.5-coder:0.5b
- Memory
- 8 GB ram
- Usable for weights
- ~5 GB
- Best runtime
- Ollama (llama.cpp backend)
You could also run
Run Qwen2.5 Coder 0.5B on other hardware
FAQ
Can 8GB RAM Laptop (CPU/iGPU only) run Qwen2.5 Coder 0.5B?
Yes. Qwen2.5 Coder 0.5B runs on 8GB RAM Laptop (CPU/iGPU only) at Q4_K_M (~1.4 GB of ~5 GB usable).
How much memory does Qwen2.5 Coder 0.5B need?
8GB RAM Laptop (CPU/iGPU only) has room to spare. At Q4_K_M the weights are ~0.37 GB; with KV cache and runtime overhead, budget ~1.4 GB at a 4k context.
What is the best tool to run Qwen2.5 Coder 0.5B on Windows?
LM Studio for a simple setup; Ollama (CUDA) for the most speed. AMD GPUs run via Vulkan/ROCm at roughly half CUDA throughput. NVIDIA is the smooth path on Windows.
Sources
Memory figures are estimates. See methodology.