Will It Run AI

Can Qwen 2.5 Math 72B run on NVIDIA H800 80GB?

YES — Runs Great

B69Good
Estimated from fit model

Qwen 2.5 Math 72B needs ~57.7 GB VRAM. NVIDIA H800 80GB has 80.0 GB. With Q4_K_M quantization, expect ~60 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) 57.7 GB, 60.2 tok/s, Runs well
57.7 GB required80.0 GB available
72% VRAM used

Fit status

Runs well

Decode

60.2 tok/s

TTFT

3218 ms

Safe context

4K

Memory

57.7 GB / 80.0 GB

Memory breakdown

Weights43.9 GB
KV Cache4.9 GB
Runtime0.9 GB
Headroom8.0 GB

See how fast it feels

See how fast it feelsQwen 2.5 Math 72B on NVIDIA H800 80GB
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: 60.2 tok/s decode · 3.2s TTFT (warm) · 150 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 well60.2 tok/s1755 ms4K
CodingBRuns well60.2 tok/s3218 ms4K
Agentic CodingBRuns well60.2 tok/s4680 ms4K
ReasoningBRuns well60.2 tok/s3803 ms4K
RAGBRuns well60.2 tok/s5850 ms4K

Quantization options

How Qwen 2.5 Math 72B (72B params) fits at each quantization level on NVIDIA H800 80GB (80.0 GB usable).

QuantBitsVRAMQualityFit
Q2_K
2
28.1 GB
LowB57
Q3_K_S
3
35.3 GB
LowB59
NVFP4
4
40.3 GB
MediumB61
Q4_K_M
4
43.9 GB
MediumB61
Q5_K_M
5
51.8 GB
HighB61
Q6_KBest for your GPU
6
59.0 GB
HighB61
Q8_0
8
77.0 GB
Very HighF0
F16
16
147.6 GB
MaximumF0

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 NVIDIA H800 80GB run Qwen 2.5 Math 72B?

Yes, NVIDIA H800 80GB can run Qwen 2.5 Math 72B with a B grade (Runs well). Expected decode speed: 60.2 tok/s.

How much VRAM does Qwen 2.5 Math 72B need?

Qwen 2.5 Math 72B (72B parameters) requires approximately 57.7 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 NVIDIA H800 80GB?

On NVIDIA H800 80GB, Qwen 2.5 Math 72B achieves approximately 60.2 tokens per second decode speed with a time-to-first-token of 3218ms using Q4_K_M quantization.

Can NVIDIA H800 80GB run Qwen 2.5 Math 72B for coding?

For coding workloads, Qwen 2.5 Math 72B on NVIDIA H800 80GB receives a B grade with 60.2 tok/s and 4K context.

What context window can Qwen 2.5 Math 72B use on NVIDIA H800 80GB?

On NVIDIA H800 80GB, 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 NVIDIA H800 80GBSee all hardware for Qwen 2.5 Math 72B
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