Can WizardMath 7B run on RTX 4000 Ada 20GB?
YES — Runs Great
WizardMath 7B needs ~9.4 GB VRAM. RTX 4000 Ada 20GB has 20.0 GB. With Q4_K_M quantization, expect ~71 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
70.7 tok/s
TTFT
2739 ms
Safe context
4K
Memory
9.4 GB / 20.0 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 | 70.7 tok/s | 1494 ms | 4K |
| Coding | A | Runs well | 70.7 tok/s | 2739 ms | 4K |
| Agentic Coding | A | Runs well | 65.8 tok/s | 4282 ms | 4K |
| Reasoning | A | Runs well | 70.7 tok/s | 3237 ms | 4K |
| RAG | A | Runs well | 70.7 tok/s | 4979 ms | 4K |
Quantization options
How WizardMath 7B (7B params) fits at each quantization level on RTX 4000 Ada 20GB (20.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 2.7 GB | Low | B66 |
Q3_K_S | 3 | 3.4 GB | Low | B66 |
NVFP4 | 4 | 3.9 GB | Medium | B67 |
Q4_K_M | 4 | 4.3 GB | Medium | B67 |
Q5_K_M | 5 | 5.0 GB | High | B67 |
Q6_K | 6 | 5.7 GB | High | B68 |
Q8_0 | 8 | 7.5 GB | Very High | B69 |
F16Best for your GPU | 16 | 14.3 GB | Maximum | A71 |
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 4000 Ada 20GB can run
| Model | Params | Grade | Decode | Capabilities |
|---|---|---|---|---|
| 30.5B | A | 23.2 tok/s | ||
| 27B | A | 10.4 tok/s | ||
| 27B | S | 13 tok/s | ||
| 30B | A | 24.6 tok/s | ||
| 9B | S | 55 tok/s |
Frequently asked questions
Can RTX 4000 Ada 20GB run WizardMath 7B?
Yes, RTX 4000 Ada 20GB can run WizardMath 7B with a A grade (Runs well). Expected decode speed: 70.7 tok/s.
How much VRAM does WizardMath 7B need?
WizardMath 7B (7B parameters) requires approximately 9.4 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 4000 Ada 20GB?
On RTX 4000 Ada 20GB, WizardMath 7B achieves approximately 70.7 tokens per second decode speed with a time-to-first-token of 2739ms using Q4_K_M quantization.
Can RTX 4000 Ada 20GB run WizardMath 7B for coding?
For coding workloads, WizardMath 7B on RTX 4000 Ada 20GB receives a A grade with 70.7 tok/s and 4K context.
What context window can WizardMath 7B use on RTX 4000 Ada 20GB?
On RTX 4000 Ada 20GB, 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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