Qwen3-Coder 480B A35B Instruct needs ~309.4 GB but Intel Data Center GPU Max 1550 128GB only has 128.0 GB. Try a smaller quantization or lighter model.
Operating mode
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
181.4 GB over capacity — needs offload or smaller quantization
Fit status
Too heavy
Decode
3.2 tok/s
TTFT
61413 ms
Safe context
4K
Memory
309.4 GB / 128.0 GB
Offload
60%
Usable VRAM is the main blocker for this model.
Not enough usable memory
The model needs 309.4 GB, but this setup only exposes 128.0 GB of usable VRAM.
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.
Add more VRAM headroom
The first useful upgrade is more dedicated VRAM so you can fit the model without shrinking context or dropping to a much lower quant.
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.
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Chat | F | Too heavy | 3.2 tok/s | 33498 ms | 4K |
| Coding | F | Too heavy | 2.9 tok/s | 67171 ms | 4K |
| Agentic Coding | F | Too heavy | 3.2 tok/s | 89329 ms | 4K |
| Reasoning | F | Too heavy | 3.2 tok/s | 72580 ms | 4K |
| RAG | F | Too heavy | 3.2 tok/s | 111661 ms | 4K |
How Qwen3-Coder 480B A35B Instruct (480B params) fits at each quantization level on Intel Data Center GPU Max 1550 128GB (128.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 187.2 GB | Low | F0 |
Q3_K_S | 3 | 235.2 GB | Low | F0 |
NVFP4 | 4 |
Upgrade options
No, Qwen3-Coder 480B A35B Instruct requires more memory than Intel Data Center GPU Max 1550 128GB provides.
Qwen3-Coder 480B A35B Instruct (480B parameters) requires approximately 309.4 GB of memory with Q4_K_M quantization.
The recommended quantization for Qwen3-Coder 480B A35B Instruct is Q4_K_M, which balances quality and memory efficiency.
On Intel Data Center GPU Max 1550 128GB, Qwen3-Coder 480B A35B Instruct achieves approximately 2.9 tokens per second decode speed with a time-to-first-token of 67171ms using Q4_K_M quantization.
For coding workloads, Qwen3-Coder 480B A35B Instruct on Intel Data Center GPU Max 1550 128GB receives a F grade with 2.9 tok/s and 4K context.
On Intel Data Center GPU Max 1550 128GB, Qwen3-Coder 480B A35B Instruct can safely use up to 4K tokens of context. The model's official context limit is 256K, but available memory constrains the safe maximum.
Paste this snippet into any page to show a live fit card.
<iframe src="https://willitrunai.com/embed/qwen-3-coder-480b-a35b-on-max-1550-128gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
Preview:
268.8 GB |
| Medium |
| F0 |
Q4_K_M | 4 | 292.8 GB | Medium | F0 |
Q5_K_M | 5 | 345.6 GB | High | F0 |
Q6_K | 6 | 393.6 GB | High | F0 |
Q8_0 | 8 | 513.6 GB | Very High | F0 |
F16 | 16 | 984.0 GB | Maximum | F0 |
Add more VRAM headroom. The first useful upgrade is more dedicated VRAM so you can fit the model without shrinking context or dropping to a much lower quant.
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.
