Will It Run AI

Can Qwen 2.5 VL 72B run on Intel Data Center GPU Max 1550 128GB?

YES — Runs Great

S91Excellent
Estimated from fit model

Qwen 2.5 VL 72B needs ~62.5 GB VRAM. Intel Data Center GPU Max 1550 128GB has 128.0 GB. With Q4_K_M quantization, expect ~46 tok/s.

Runtime: llama.cppCapacity: 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) — 62.5 GB, 49.9 tok/s, Runs well
62.5 GB required128.0 GB available
49% VRAM used

Fit status

Runs well

Decode

49.9 tok/s

TTFT

3878 ms

Safe context

33K

Memory

62.5 GB / 128.0 GB

Memory breakdown

Weights43.9 GB
KV Cache4.9 GB
Runtime0.9 GB
Headroom12.8 GB

See how fast it feels

See how fast it feelsQwen 2.5 VL 72B 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: 49.9 tok/s decode · 3.9s TTFT (warm) · 125 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 well49.9 tok/s2115 ms33K
CodingSRuns well45.9 tok/s4218 ms33K
Agentic CodingSRuns well49.9 tok/s5641 ms33K
ReasoningSRuns well49.9 tok/s4584 ms33K
RAGSRuns well49.9 tok/s7052 ms33K

Quantization options

How Qwen 2.5 VL 72B (72B params) fits at each quantization level on Intel Data Center GPU Max 1550 128GB (128.0 GB usable).

QuantBitsVRAMQualityFit
Q2_K
2
28.1 GB
LowA81
Q3_K_S
3
35.3 GB
LowA82
NVFP4
4
40.3 GB
MediumA83
Q4_K_M
4
43.9 GB
MediumA84
Q5_K_M
5
51.8 GB
HighA85
Q6_K
6
59.0 GB
HighS86
Q8_0Best for your GPU
8
77.0 GB
Very HighS88
F16
16
147.6 GB
MaximumF0

Get started

Copy-paste commands to run Qwen 2.5 VL 72B on your machine.

Run

lms load Qwen2.5-VL-72B-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
AlibabaQwen 3.5 122B A10B122BS81 tok/s
MistralMistral Small 4 119B119BS87.9 tok/s
OpenAIGPT-OSS 120B117BS30.7 tok/s
CohereCommand A 111B111BS32.5 tok/s

Frequently asked questions

Can Intel Data Center GPU Max 1550 128GB run Qwen 2.5 VL 72B?

Yes, Intel Data Center GPU Max 1550 128GB can run Qwen 2.5 VL 72B with a S grade (Runs well). Expected decode speed: 45.9 tok/s.

How much VRAM does Qwen 2.5 VL 72B need?

Qwen 2.5 VL 72B (72B parameters) requires approximately 62.5 GB of memory with Q4_K_M quantization.

What is the best quantization for Qwen 2.5 VL 72B?

The recommended quantization for Qwen 2.5 VL 72B is Q4_K_M, which balances quality and memory efficiency.

What speed will Qwen 2.5 VL 72B run at on Intel Data Center GPU Max 1550 128GB?

On Intel Data Center GPU Max 1550 128GB, Qwen 2.5 VL 72B achieves approximately 45.9 tokens per second decode speed with a time-to-first-token of 4218ms using Q4_K_M quantization.

Can Intel Data Center GPU Max 1550 128GB run Qwen 2.5 VL 72B for coding?

For coding workloads, Qwen 2.5 VL 72B on Intel Data Center GPU Max 1550 128GB receives a S grade with 45.9 tok/s and 33K context.

What context window can Qwen 2.5 VL 72B use on Intel Data Center GPU Max 1550 128GB?

On Intel Data Center GPU Max 1550 128GB, Qwen 2.5 VL 72B can safely use up to 33K tokens of context. The model's official context limit is 33K, but available memory constrains the safe maximum.

What should I upgrade first if Qwen 2.5 VL 72B 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 Qwen 2.5 VL 72B?

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 Qwen 2.5 VL 72B
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