Can WizardMath 7B run on RTX A4000 16GB?
YES — Runs Great
WizardMath 7B needs ~9.0 GB VRAM. RTX A4000 16GB has 16.0 GB. With Q4_K_M quantization, expect ~73 tok/s.
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.
Select quantization to explore
Fit status
Runs well
Decode
79.0 tok/s
TTFT
2452 ms
Safe context
4K
Memory
9.0 GB / 16.0 GB
Memory breakdown
See how fast it feels
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 | A | Runs well | 79.0 tok/s | 1338 ms | 4K |
| Coding | A | Runs well | 73.4 tok/s | 2636 ms | 4K |
| Agentic Coding | A | Runs well | 79.0 tok/s | 3567 ms | 4K |
| Reasoning | A | Runs well | 79.0 tok/s | 2898 ms | 4K |
| RAG | A | Runs well | 79.0 tok/s | 4458 ms | 4K |
Quantization options
How WizardMath 7B (7B params) fits at each quantization level on RTX A4000 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 | 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 |
Get started
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
More models your RTX A4000 16GB can run
| Model | Params | Grade | Decode | Capabilities |
|---|---|---|---|---|
| 9B | S | 61.4 tok/s | ||
| 14B | S | 39.7 tok/s | ||
| 8B | S | 69.1 tok/s | ||
| 14.7B | S | 37.6 tok/s | ||
| 21B | A | 35 tok/s |
Frequently asked questions
Can RTX A4000 16GB run WizardMath 7B?
Yes, RTX A4000 16GB can run WizardMath 7B with a A grade (Runs well). Expected decode speed: 73.4 tok/s.
How much VRAM does WizardMath 7B need?
WizardMath 7B (7B parameters) requires approximately 9.0 GB of memory with Q4_K_M quantization.
What is the best quantization for WizardMath 7B?
The recommended quantization for WizardMath 7B is Q4_K_M, which balances quality and memory efficiency.
What speed will WizardMath 7B run at on RTX A4000 16GB?
On RTX A4000 16GB, WizardMath 7B achieves approximately 73.4 tokens per second decode speed with a time-to-first-token of 2636ms using Q4_K_M quantization.
Can RTX A4000 16GB run WizardMath 7B for coding?
For coding workloads, WizardMath 7B on RTX A4000 16GB receives a A grade with 73.4 tok/s and 4K context.
What context window can WizardMath 7B use on RTX A4000 16GB?
On RTX A4000 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.
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