WizardMath 7B needs ~8.6 GB VRAM. RTX 3060 12GB has 12.0 GB. With Q4_K_M quantization, expect ~60 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
59.8 tok/s
TTFT
3237 ms
Safe context
4K
Memory
8.6 GB / 12.0 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 | A | Runs well | 59.8 tok/s | 1765 ms | 4K |
| Coding | A | Runs well | 59.8 tok/s | 3237 ms | 4K |
| Agentic Coding | A | Tight fit | 59.8 tok/s | 4708 ms | 4K |
| Reasoning | A | Runs well | 59.8 tok/s | 3825 ms | 4K |
| RAG | A | Tight fit | 59.8 tok/s | 5885 ms | 4K |
How WizardMath 7B (7B params) fits at each quantization level on RTX 3060 12GB (12.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 2.7 GB | Low | B70 |
Q3_K_S | 3 | 3.4 GB | Low | A70 |
NVFP4 | 4 | 3.9 GB | Medium | A71 |
Q4_K_M | 4 | 4.3 GB | Medium | A72 |
Q5_K_M | 5 | 5.0 GB | High | A73 |
Q6_K | 6 | 5.7 GB | High | A73 |
Q8_0Best for your GPU | 8 | 7.5 GB | Very High | A72 |
F16 | 16 | 14.3 GB | Maximum | F0 |
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 |
|---|---|---|---|---|
 Qwen 3.5 9B | 9B | S | 46.5 tok/s | |
| Qwen 3 14B | 14B | A | 17.9 tok/s | |
| Qwen 3 8B | 8B | S | 52.3 tok/s | |
 Nemotron Nano 8B | 8B | S | 52.3 tok/s | |
 Ministral 3 14B | 14B | A | 17.8 tok/s |
Yes, RTX 3060 12GB can run WizardMath 7B with a A grade (Runs well). Expected decode speed: 59.8 tok/s.
WizardMath 7B (7B parameters) requires approximately 8.6 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 RTX 3060 12GB, WizardMath 7B achieves approximately 59.8 tokens per second decode speed with a time-to-first-token of 3237ms using Q4_K_M quantization.
For coding workloads, WizardMath 7B on RTX 3060 12GB receives a A grade with 59.8 tok/s and 4K context.
On RTX 3060 12GB, 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-rtx-3060-12gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
Preview: