Qwen 2.5 Math 72B needs ~67.7 GB VRAM. NVIDIA B200 180GB has 180.0 GB. With Q4_K_M quantization, expect ~166 tok/s.
Operating mode
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.
Select quantization to explore
Fit status
Runs well
Decode
166.4 tok/s
TTFT
1164 ms
Safe context
4K
Memory
67.7 GB / 180.0 GB
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.
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Chat | B | Runs well | 166.4 tok/s | 635 ms | 4K |
| Coding | B | Runs well | 166.4 tok/s | 1164 ms | 4K |
| Agentic Coding | B | Runs well | 166.4 tok/s | 1692 ms | 4K |
| Reasoning | B | Runs well | 166.4 tok/s | 1375 ms | 4K |
| RAG | B | Runs well | 166.4 tok/s | 2115 ms | 4K |
How Qwen 2.5 Math 72B (72B params) fits at each quantization level on NVIDIA B200 180GB (180.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 28.1 GB | Low | C52 |
Q3_K_S | 3 | 35.3 GB | Low | C53 |
NVFP4 | 4 | 40.3 GB | Medium | C54 |
Q4_K_M | 4 | 43.9 GB | Medium | C54 |
Q5_K_M | 5 | 51.8 GB | High | B55 |
Q6_K | 6 | 59.0 GB | High | B56 |
Q8_0 | 8 | 77.0 GB | Very High | B58 |
F16Best for your GPU | 16 | 147.6 GB | Maximum | B61 |
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 99Yes, NVIDIA B200 180GB can run Qwen 2.5 Math 72B with a B grade (Runs well). Expected decode speed: 166.4 tok/s.
Qwen 2.5 Math 72B (72B parameters) requires approximately 67.7 GB of memory with Q4_K_M quantization.
The recommended quantization for Qwen 2.5 Math 72B is Q4_K_M, which balances quality and memory efficiency.
On NVIDIA B200 180GB, Qwen 2.5 Math 72B achieves approximately 166.4 tokens per second decode speed with a time-to-first-token of 1164ms using Q4_K_M quantization.
For coding workloads, Qwen 2.5 Math 72B on NVIDIA B200 180GB receives a B grade with 166.4 tok/s and 4K context.
On NVIDIA B200 180GB, 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.
Paste this snippet into any page to show a live fit card.
<iframe src="https://willitrunai.com/embed/qwen-2.5-math-72b-on-b200-180gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
Preview: