Will It Run AI

Can Qwen3-VL 30B A3B Instruct run on Intel Data Center GPU Max 1550 128GB?

YES — Runs Great

S90Excellent
Estimated from fit model

Qwen3-VL 30B A3B Instruct needs ~34.4 GB VRAM. Intel Data Center GPU Max 1550 128GB has 128.0 GB. With Q4_K_M quantization, expect ~315 tok/s.

Runtime: TransformersCapacity: RoomyBandwidth: HighStack: StandardBottleneck: Balanced
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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.

Capabilities:

Select quantization to explore

Q4_K_M (Medium quality) — 34.4 GB, 315.3 tok/s, Runs well
34.4 GB required128.0 GB available
27% VRAM used

Fit status

Runs well

Decode

315.3 tok/s

TTFT

614 ms

Safe context

256K

Memory

34.4 GB / 128.0 GB

Memory breakdown

Weights18.3 GB
KV Cache1.5 GB
Runtime1.8 GB
Headroom12.8 GB

See how fast it feels

See how fast it feelsQwen3-VL 30B A3B Instruct on Intel Data Center GPU Max 1550 128GB
1st promptCold start — includes initialization
>Solve: If a train travels at 60 mph for 2.5 hours, how far does it go?
Let me work through this step by step. Given information: - Speed = 60 mph (miles per hour) - Time = 2.5 hours Formula: Distance = Speed x Time Calculation: Distance = 60 mph x 2.5 h = 150 miles The train travels 150 miles. Double-check: at 60 mph the train covers 60 miles each hour. In half an hour it covers 30 miles. So in 2.5 hours: 60 + 60 + 30 = 150 miles. Confirmed.
2nd promptWarm — model ready, no init overhead
>What if the train stops for 20 minutes halfway?
The stop doesn't change the total distance covered while moving, but it affects total trip time. Breakdown: - First half: 1.25 hours at 60 mph = 75 miles - Stop: 20 minutes (no distance) - Second half: 1.25 hours at 60 mph = 75 miles Total distance: 150 miles (same) Total time: 2.5 h + 0.33 h = 2.83 hours Average speed: 150 / 2.83 = 53 mph The distance stays the same but average speed drops to 53 mph because of the stop.
Estimated: 315.3 tok/s decode · 614ms TTFT (warm) · 788 tok/s prefill

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

WorkloadGradeFitDecodeTTFTContext
ChatSRuns well315.3 tok/s350 ms256K
CodingSRuns well315.3 tok/s614 ms256K
Agentic CodingSRuns well315.3 tok/s893 ms256K
ReasoningSRuns well315.3 tok/s726 ms256K
RAGSRuns well315.3 tok/s1116 ms256K

Quantization options

How Qwen3-VL 30B A3B Instruct (30B params) fits at each quantization level on Intel Data Center GPU Max 1550 128GB (128.0 GB usable).

QuantBitsVRAMQualityFit
Q2_K
2
11.7 GB
LowA81
Q3_K_S
3
14.7 GB
LowA81
NVFP4
4
16.8 GB
MediumA81
Q4_K_M
4
18.3 GB
MediumA81
Q5_K_M
5
21.6 GB
HighA81
Q6_K
6
24.6 GB
HighA82
Q8_0
8
32.1 GB
Very HighA83
F16Best for your GPU
16
61.5 GB
MaximumS88

Get started

Copy-paste commands to run Qwen3-VL 30B A3B Instruct on your machine.

Run

lms load Qwen3-VL-30B-A3B-Instruct && lms server start

Your hardware

More models your Intel Data Center GPU Max 1550 128GB can run

ModelParamsGradeDecodeCapabilities
MistralDevstral 2 123B Instruct123BS29.2 tok/s
AlibabaQwen3-Coder 30B A3B Instruct30.5BS304.8 tok/s
AlibabaQwen 3.5 122B A10B122BS81 tok/s
AlibabaQwen 3.6 35B A3B35BS256.2 tok/s

Frequently asked questions

Can Intel Data Center GPU Max 1550 128GB run Qwen3-VL 30B A3B Instruct?

Yes, Intel Data Center GPU Max 1550 128GB can run Qwen3-VL 30B A3B Instruct with a S grade (Runs well). Expected decode speed: 315.3 tok/s.

How much VRAM does Qwen3-VL 30B A3B Instruct need?

Qwen3-VL 30B A3B Instruct (30B parameters) requires approximately 34.4 GB of memory with Q4_K_M quantization.

What is the best quantization for Qwen3-VL 30B A3B Instruct?

The recommended quantization for Qwen3-VL 30B A3B Instruct is Q4_K_M, which balances quality and memory efficiency.

What speed will Qwen3-VL 30B A3B Instruct run at on Intel Data Center GPU Max 1550 128GB?

On Intel Data Center GPU Max 1550 128GB, Qwen3-VL 30B A3B Instruct achieves approximately 315.3 tokens per second decode speed with a time-to-first-token of 614ms using Q4_K_M quantization.

Can Intel Data Center GPU Max 1550 128GB run Qwen3-VL 30B A3B Instruct for coding?

For coding workloads, Qwen3-VL 30B A3B Instruct on Intel Data Center GPU Max 1550 128GB receives a S grade with 315.3 tok/s and 256K context.

What context window can Qwen3-VL 30B A3B Instruct use on Intel Data Center GPU Max 1550 128GB?

On Intel Data Center GPU Max 1550 128GB, Qwen3-VL 30B A3B Instruct can safely use up to 256K tokens of context. The model's official context limit is 256K, but available memory constrains the safe maximum.

What should I upgrade first if Qwen3-VL 30B A3B Instruct feels slow on Intel Data Center GPU Max 1550 128GB?

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 Data Center GPU Max 1550 128GB for Qwen3-VL 30B A3B Instruct?

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.

See all results for Intel Data Center GPU Max 1550 128GBSee all hardware for Qwen3-VL 30B A3B Instruct
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