Qwen 3 32B needs ~37.1 GB VRAM. Intel Data Center GPU Max 1550 128GB has 128.0 GB. With Q4_K_M quantization, expect ~112 tok/s.
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
Fit status
Runs well
Decode
112.3 tok/s
TTFT
1724 ms
Safe context
131K
Memory
37.1 GB / 128.0 GB
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.
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 | S | Runs well | 112.3 tok/s | 940 ms | 131K |
| Coding | S | Runs well | 112.3 tok/s | 1724 ms | 131K |
| Agentic Coding | S | Runs well | 112.3 tok/s | 2507 ms | 131K |
| Reasoning | S | Runs well | 112.3 tok/s | 2037 ms | 131K |
| RAG | S | Runs well | 112.3 tok/s | 3134 ms | 131K |
How Qwen 3 32B (32B 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 | 12.5 GB | Low | A80 |
Q3_K_S | 3 | 15.7 GB | Low | A80 |
NVFP4 | 4 |
Copy-paste commands to run Qwen 3 32B on your machine.
Run
ollama run qwen3:32bYour hardware
| Model | Params | Grade | Decode | Capabilities |
|---|---|---|---|---|
 Devstral 2 123B Instruct | 123B | S | 29.2 tok/s | |
 Qwen 3.5 122B A10B | 122B | S |
Yes, Intel Data Center GPU Max 1550 128GB can run Qwen 3 32B with a S grade (Runs well). Expected decode speed: 112.3 tok/s.
Qwen 3 32B (32B parameters) requires approximately 37.1 GB of memory with Q4_K_M quantization.
The recommended quantization for Qwen 3 32B is Q4_K_M, which balances quality and memory efficiency.
On Intel Data Center GPU Max 1550 128GB, Qwen 3 32B achieves approximately 112.3 tokens per second decode speed with a time-to-first-token of 1724ms using Q4_K_M quantization.
For coding workloads, Qwen 3 32B on Intel Data Center GPU Max 1550 128GB receives a S grade with 112.3 tok/s and 131K context.
On Intel Data Center GPU Max 1550 128GB, Qwen 3 32B can safely use up to 131K tokens of context. The model's official context limit is 131K, 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-3-32b-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:
17.9 GB |
| Medium |
| A80 |
Q4_K_M | 4 | 19.5 GB | Medium | A80 |
Q5_K_M | 5 | 23.0 GB | High | A80 |
Q6_K | 6 | 26.2 GB | High | A81 |
Q8_0 | 8 | 34.2 GB | Very High | A82 |
F16Best for your GPU | 16 | 65.6 GB | Maximum | S87 |
| 81 tok/s |
| Qwen 3.6 35B A3B | 35B | S | 256.2 tok/s |
| Qwen 3.5 35B A3B | 35B | S | 278.6 tok/s |
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.
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.