Can Qwen 2.5 Math 72B run on RTX PRO 6000 Blackwell Workstation Edition 96GB?

YES — Runs Great

B65Good

Estimated from fit model

Qwen 2.5 Math 72B needs ~59.3 GB VRAM. RTX PRO 6000 Blackwell Workstation Edition 96GB has 96.0 GB. With Q4_K_M quantization, expect ~34 tok/s.

Runtime: llama.cppCapacity: RoomyBandwidth: HighStack: StandardBottleneck: Balanced

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) — 59.3 GB, 37.3 tok/s, Runs well

59.3 GB required96.0 GB available

62% VRAM used

Fit status

Runs well

Decode

37.3 tok/s

TTFT

5194 ms

Safe context

Memory

59.3 GB / 96.0 GB

Memory breakdown

Weights43.9 GB

KV Cache4.9 GB

Runtime0.9 GB

Headroom9.6 GB

See how fast it feels

See how fast it feelsQwen 2.5 Math 72B on RTX PRO 6000 Blackwell Workstation Edition 96GB
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: 37.3 tok/s decode · 5.2s TTFT (warm) · 93 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

Workload	Grade	Fit	Decode	TTFT	Context
Chat	B	Runs well	37.3 tok/s	2833 ms	4K
Coding	B	Runs well	34.3 tok/s	5649 ms	4K
Agentic Coding	B	Runs well	37.3 tok/s	7555 ms	4K
Reasoning	B	Runs well	37.3 tok/s	6139 ms	4K
RAG	B	Runs well	37.3 tok/s	9444 ms	4K

Quantization options

How Qwen 2.5 Math 72B (72B params) fits at each quantization level on RTX PRO 6000 Blackwell Workstation Edition 96GB (96.0 GB usable).

Quant	Bits	VRAM	Quality	Fit
Q2_K	2	28.1 GB	Low	B56
Q3_K_S	3	35.3 GB	Low	B57
NVFP4	4

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

Upgrade options

Hardware that runs Qwen 2.5 Math 72B well

AMD Instinct MI300A 128GBBudget pick

128 GB VRAM (+32)5300 GB/s (+3508)

Raises estimated decode speed by about 146%.91.9 tok/s decode

Raises estimated decode speed by about 146%.

Adds memory headroom for longer context windows and future model growth.

~$12,000 MSRP

Frequently asked questions

Can RTX PRO 6000 Blackwell Workstation Edition 96GB run Qwen 2.5 Math 72B?

Yes, RTX PRO 6000 Blackwell Workstation Edition 96GB can run Qwen 2.5 Math 72B with a B grade (Runs well). Expected decode speed: 34.3 tok/s.

How much VRAM does Qwen 2.5 Math 72B need?

Qwen 2.5 Math 72B (72B parameters) requires approximately 59.3 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 RTX PRO 6000 Blackwell Workstation Edition 96GB?

On RTX PRO 6000 Blackwell Workstation Edition 96GB, Qwen 2.5 Math 72B achieves approximately 34.3 tokens per second decode speed with a time-to-first-token of 5649ms using Q4_K_M quantization.

Can RTX PRO 6000 Blackwell Workstation Edition 96GB run Qwen 2.5 Math 72B for coding?

For coding workloads, Qwen 2.5 Math 72B on RTX PRO 6000 Blackwell Workstation Edition 96GB receives a B grade with 34.3 tok/s and 4K context.

What context window can Qwen 2.5 Math 72B use on RTX PRO 6000 Blackwell Workstation Edition 96GB?

On RTX PRO 6000 Blackwell Workstation Edition 96GB, 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 RTX PRO 6000 Blackwell Workstation Edition 96GB See all hardware for Qwen 2.5 Math 72B

Embed this result▼

Paste this snippet into any page to show a live fit card.

<iframe src="https://willitrunai.com/embed/qwen-2.5-math-72b-on-rtx-pro-6000-blackwell-96gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>

Preview: