Can Qwen 3 8B run on Intel Arc A580 8GB?
BARELY — Tight on Memory
Qwen 3 8B needs ~8.8 GB VRAM. Intel Arc A580 8GB has 8.0 GB. With Q4_K_M quantization, expect ~34 tok/s.
Operating mode
Choose the run profile you care about
Interactive favors responsiveness, while light API and scale-out lean harder on serving readiness. The fit stays the same, but the recommendation lens changes.
Current mode
Balanced
Balanced for general local use. Keeps the ranking neutral across personal and serving workflows.
Select quantization to explore
0.8 GB over capacity — needs offload or smaller quantization
Fit status
Very compromised (needs ~0.4 GB host RAM)
Decode
34.1 tok/s
TTFT
5677 ms
Safe context
10K
Memory
8.8 GB / 8.0 GB
Offload
10%
Memory breakdown
See how fast it feels
What limits this setup
It fits through host-memory offload, and offload is the main reason performance drops.
CPU or host-memory offload is active
About 10% of the working set spills out of accelerator memory, which usually hurts latency and sustained decode throughput.
Very little memory headroom
You can run the model, but there is not much room left for longer context, bigger batches, extra apps, or future model updates.
Runtime ecosystem is narrower than CUDA
Intel GPUs can look attractive on memory per dollar, but local AI tooling, kernels, and model coverage are still broader and easier on CUDA today.
Best improvement path
Remove offload with more accelerator memory
Prioritize a GPU or unified-memory tier that fits the whole model natively. Removing offload usually helps more than small compute gains.
Prefer CUDA if you want the path of least resistance
If your goal is maximum runtime coverage, easier troubleshooting, and better support for new local AI releases, CUDA is usually still the safer upgrade path.
Buy headroom, not only minimum fit
A slightly larger memory tier gives you safer context growth and makes the recommendation more future-proof.
Performance by workload
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Chat | S | Runs with offload | 51.4 tok/s | 2054 ms | 10K |
| Coding | A | Very compromised (needs ~0.4 GB host RAM) | 34.1 tok/s | 5677 ms | 10K |
| Agentic Coding | F | Too heavy | 21.3 tok/s | 13217 ms | 10K |
| Reasoning | A | Very compromised (needs ~0.4 GB host RAM) | 34.1 tok/s | 6710 ms | 10K |
| RAG | F | Too heavy | 21.3 tok/s | 16521 ms |
Quantization options
How Qwen 3 8B (8B params) fits at each quantization level on Intel Arc A580 8GB (8.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 3.1 GB | Low | S94 |
Q3_K_S | 3 | 3.9 GB | Low | S93 |
NVFP4 | 4 |
Get started
Copy-paste commands to run Qwen 3 8B on your machine.
Run
ollama run qwen3:8bYour hardware
More models your Intel Arc A580 8GB can run
| Model | Params | Grade | Decode | Capabilities |
|---|---|---|---|---|
| 👁 Alibaba Qwen 3.5 9B | 9B | A | 26.3 tok/s |
