Will It Run AI

Can Qwen 2.5 Math 72B run on H100 NVL 188GB?

YES — Runs Great

B63Good
Estimated from fit model

Qwen 2.5 Math 72B needs ~68.5 GB VRAM. H100 NVL 188GB has 188.0 GB. With Q4_K_M quantization, expect ~156 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) 68.5 GB, 156.4 tok/s, Runs well
68.5 GB required188.0 GB available
36% VRAM used

Fit status

Runs well

Decode

156.4 tok/s

TTFT

1238 ms

Safe context

4K

Memory

68.5 GB / 188.0 GB

Memory breakdown

Weights43.9 GB
KV Cache4.9 GB
Runtime0.9 GB
Headroom18.8 GB

See how fast it feels

See how fast it feelsQwen 2.5 Math 72B on H100 NVL 188GB
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: 156.4 tok/s decode · 1.2s TTFT (warm) · 391 tok/s prefill

What limits this setup

This setup is broadly balanced for this model.

No major red flags

This recommendation has enough memory headroom and acceptable estimated speed for the selected workload.

Best improvement path

Performance by workload

WorkloadGradeFitDecodeTTFTContext
ChatBRuns well156.4 tok/s675 ms4K
CodingBRuns well156.4 tok/s1238 ms4K
Agentic CodingBRuns well143.9 tok/s1958 ms4K
ReasoningBRuns well156.4 tok/s1463 ms4K
RAGBRuns well156.4 tok/s2250 ms4K

Quantization options

How Qwen 2.5 Math 72B (72B params) fits at each quantization level on H100 NVL 188GB (188.0 GB usable).

QuantBitsVRAMQualityFit
Q2_K
2
28.1 GB
LowC52
Q3_K_S
3
35.3 GB
LowC53
NVFP4
4
40.3 GB
MediumC53
Q4_K_M
4
43.9 GB
MediumC54
Q5_K_M
5
51.8 GB
HighC55
Q6_K
6
59.0 GB
HighB56
Q8_0
8
77.0 GB
Very HighB58
F16Best for your GPU
16
147.6 GB
MaximumB61

Get started

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

Run

docker run --rm -it ghcr.io/ggerganov/llama.cpp:full \ --hf-repo "Qwen/Qwen2.5-Math-72B-Instruct" \ --hf-file "Qwen2.5-Math-72B-Instruct-Q4_K_M.gguf" \ -c 4096 -ngl 99

Frequently asked questions

Can H100 NVL 188GB run Qwen 2.5 Math 72B?

Yes, H100 NVL 188GB can run Qwen 2.5 Math 72B with a B grade (Runs well). Expected decode speed: 156.4 tok/s.

How much VRAM does Qwen 2.5 Math 72B need?

Qwen 2.5 Math 72B (72B parameters) requires approximately 68.5 GB of memory with Q4_K_M quantization.

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

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

What speed will Qwen 2.5 Math 72B run at on H100 NVL 188GB?

On H100 NVL 188GB, Qwen 2.5 Math 72B achieves approximately 156.4 tokens per second decode speed with a time-to-first-token of 1238ms using Q4_K_M quantization.

Can H100 NVL 188GB run Qwen 2.5 Math 72B for coding?

For coding workloads, Qwen 2.5 Math 72B on H100 NVL 188GB receives a B grade with 156.4 tok/s and 4K context.

What context window can Qwen 2.5 Math 72B use on H100 NVL 188GB?

On H100 NVL 188GB, Qwen 2.5 Math 72B can safely use up to 4K tokens of context. The model's official context limit is 4K, but available memory constrains the safe maximum.

See all results for H100 NVL 188GBSee all hardware for Qwen 2.5 Math 72B
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