Adds memory headroom for longer context windows and future model growth.
~$2,499 MSRP
WizardMath 7B needs ~12.2 GB VRAM. Quadro RTX 8000 48GB has 48.0 GB. With Q4_K_M quantization, expect ~98 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
98.0 tok/s
TTFT
1976 ms
Safe context
4K
Memory
12.2 GB / 48.0 GB
This setup is broadly balanced for this model.
Older PCIe generation
PCIe 3.0 is workable, but it compounds the penalty when you offload heavily or try to scale across multiple cards.
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Chat | B | Runs well | 98.0 tok/s | 1078 ms | 4K |
| Coding | B | Runs well | 98.0 tok/s | 1976 ms | 4K |
| Agentic Coding | B | Runs well | 98.0 tok/s | 2873 ms | 4K |
| Reasoning | B | Runs well | 98.0 tok/s | 2335 ms | 4K |
| RAG | B | Runs well | 98.0 tok/s | 3592 ms | 4K |
How WizardMath 7B (7B params) fits at each quantization level on Quadro RTX 8000 48GB (48.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 2.7 GB | Low | B62 |
Q3_K_S | 3 | 3.4 GB | Low | B62 |
NVFP4 | 4 |
Copy-paste commands to run WizardMath 7B on your machine.
Run
docker run --rm -it ghcr.io/ggerganov/llama.cpp:full \
--hf-repo "WizardLMTeam/WizardMath-7B-V1.1" \
--hf-file "WizardMath-7B-V1.1-Q4_K_M.gguf" \
-c 4096 -ngl 99Upgrade options
Adds memory headroom for longer context windows and future model growth.
~$2,499 MSRP
Adds memory headroom for longer context windows and future model growth.
~$3,999 MSRP
Yes, Quadro RTX 8000 48GB can run WizardMath 7B with a B grade (Runs well). Expected decode speed: 98.0 tok/s.
WizardMath 7B (7B parameters) requires approximately 12.2 GB of memory with Q4_K_M quantization.
The recommended quantization for WizardMath 7B is Q4_K_M, which balances quality and memory efficiency.
On Quadro RTX 8000 48GB, WizardMath 7B achieves approximately 98.0 tokens per second decode speed with a time-to-first-token of 1976ms using Q4_K_M quantization.
For coding workloads, WizardMath 7B on Quadro RTX 8000 48GB receives a B grade with 98.0 tok/s and 4K context.
On Quadro RTX 8000 48GB, WizardMath 7B 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/wizard-math-7b-on-quadro-rtx-8000-48gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
Preview:
3.9 GB |
| Medium |
| B62 |
Q4_K_M | 4 | 4.3 GB | Medium | B62 |
Q5_K_M | 5 | 5.0 GB | High | B62 |
Q6_K | 6 | 5.7 GB | High | B62 |
Q8_0 | 8 | 7.5 GB | Very High | B63 |
F16Best for your GPU | 16 | 14.3 GB | Maximum | B65 |