Can Qwen 3 8B run on Intel Arc A770 16GB?
YES — Runs Great
Qwen 3 8B needs ~9.6 GB VRAM. Intel Arc A770 16GB has 16.0 GB. With Q4_K_M quantization, expect ~56 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
Fit status
Runs well
Decode
55.5 tok/s
TTFT
3488 ms
Safe context
63K
Memory
9.6 GB / 16.0 GB
Memory breakdown
See how fast it feels
What limits this setup
The raw memory story may look fine, but the software ecosystem is still a constraint here.
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
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.
Performance by workload
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Chat | S | Runs well | 55.5 tok/s | 1902 ms | 63K |
| Coding | S | Runs well | 55.5 tok/s | 3488 ms | 63K |
| Agentic Coding | S | Runs well | 55.5 tok/s | 5073 ms | 63K |
| Reasoning | S | Runs well | 55.5 tok/s | 4122 ms | 63K |
| RAG | S | Runs well | 55.5 tok/s | 6341 ms | 63K |
Quantization options
How Qwen 3 8B (8B params) fits at each quantization level on Intel Arc A770 16GB (16.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 3.1 GB | Low | S87 |
Q3_K_S | 3 | 3.9 GB | Low | S88 |
NVFP4 | 4 | 4.5 GB | Medium | S88 |
Q4_K_M | 4 | 4.9 GB | Medium | S89 |
Q5_K_M | 5 | 5.8 GB | High | S89 |
Q6_K | 6 | 6.6 GB | High | S90 |
Q8_0Best for your GPU | 8 | 8.6 GB | Very High | S91 |
F16 | 16 | 16.4 GB | Maximum | F0 |
Get started
Copy-paste commands to run Qwen 3 8B on your machine.
Run
ollama run qwen3:8bYour hardware
More models your Intel Arc A770 16GB can run
| Model | Params | Grade | Decode | Capabilities |
|---|---|---|---|---|
| 9B | S | 49.3 tok/s | ||
| 14B | S | 31.9 tok/s |
Frequently asked questions
Can Intel Arc A770 16GB run Qwen 3 8B?
Yes, Intel Arc A770 16GB can run Qwen 3 8B with a S grade (Runs well). Expected decode speed: 55.5 tok/s.
How much VRAM does Qwen 3 8B need?
Qwen 3 8B (8B parameters) requires approximately 9.6 GB of memory with Q4_K_M quantization.
What is the best quantization for Qwen 3 8B?
The recommended quantization for Qwen 3 8B is Q4_K_M, which balances quality and memory efficiency.
What speed will Qwen 3 8B run at on Intel Arc A770 16GB?
On Intel Arc A770 16GB, Qwen 3 8B achieves approximately 55.5 tokens per second decode speed with a time-to-first-token of 3488ms using Q4_K_M quantization.
Can Intel Arc A770 16GB run Qwen 3 8B for coding?
For coding workloads, Qwen 3 8B on Intel Arc A770 16GB receives a S grade with 55.5 tok/s and 63K context.
What context window can Qwen 3 8B use on Intel Arc A770 16GB?
On Intel Arc A770 16GB, Qwen 3 8B can safely use up to 63K tokens of context. The model's official context limit is 131K, but available memory constrains the safe maximum.
What should I upgrade first if Qwen 3 8B feels slow on Intel Arc A770 16GB?
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.
Would CUDA be a better path than Intel Arc A770 16GB for Qwen 3 8B?
Often yes, if your goal is the easiest setup and the widest runtime support. Intel can offer attractive memory capacity, but CUDA still tends to win on tooling maturity, guides, kernels, and model coverage for local AI.
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<iframe src="https://willitrunai.com/embed/qwen-3-8b-on-arc-a770-16gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
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