WizardMath 7B needs ~9.0 GB VRAM. NVIDIA T4 16GB has 16.0 GB. With Q4_K_M quantization, expect ~49 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
52.4 tok/s
TTFT
3697 ms
Safe context
4K
Memory
9.0 GB / 16.0 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 | A | Runs well | 48.7 tok/s | 2168 ms | 4K |
| Coding | A | Runs well | 48.7 tok/s | 3974 ms | 4K |
| Agentic Coding | A | Runs well | 48.7 tok/s | 5781 ms | 4K |
| Reasoning | A | Runs well | 48.7 tok/s | 4697 ms | 4K |
| RAG | A | Runs well | 48.7 tok/s | 7226 ms | 4K |
How WizardMath 7B (7B params) fits at each quantization level on NVIDIA T4 16GB (16.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 2.7 GB | Low | B67 |
Q3_K_S | 3 | 3.4 GB | Low | B68 |
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 99Your hardware
| Model | Params | Grade | Decode | Capabilities |
|---|---|---|---|---|
| 9B | S | 40.7 tok/s | ||
| 14B | S | 26.3 tok/s |
Yes, NVIDIA T4 16GB can run WizardMath 7B with a A grade (Runs well). Expected decode speed: 48.7 tok/s.
WizardMath 7B (7B parameters) requires approximately 9.0 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 NVIDIA T4 16GB, WizardMath 7B achieves approximately 48.7 tokens per second decode speed with a time-to-first-token of 3974ms using Q4_K_M quantization.
For coding workloads, WizardMath 7B on NVIDIA T4 16GB receives a A grade with 48.7 tok/s and 4K context.
On NVIDIA T4 16GB, 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-t4-16gb" 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 |
| B68 |
Q4_K_M | 4 | 4.3 GB | Medium | B69 |
Q5_K_M | 5 | 5.0 GB | High | B69 |
Q6_K | 6 | 5.7 GB | High | A70 |
Q8_0Best for your GPU | 8 | 7.5 GB | Very High | A72 |
F16 | 16 | 14.3 GB | Maximum | F0 |
| 8B | S | 45.8 tok/s |
| 14.7B | S | 24.9 tok/s |
| 21B | A | 22.3 tok/s |