Vicuna 7B needs ~15.7 GB VRAM. RTX A5000 24GB has 24.0 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
15.7 GB / 24.0 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 | C | Runs well | 98.0 tok/s | 1078 ms | 4K |
| Coding | B | Runs well | 98.0 tok/s | 1976 ms | 4K |
| Agentic Coding | C | Runs with offload | 98.0 tok/s | 2873 ms | 4K |
| Reasoning | B | Runs well | 98.0 tok/s | 2335 ms | 4K |
| RAG | C | Runs with offload | 98.0 tok/s | 3592 ms | 4K |
How Vicuna 7B (7B params) fits at each quantization level on RTX A5000 24GB (24.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 2.7 GB | Low | C45 |
Q3_K_S | 3 | 3.4 GB | Low | C45 |
NVFP4 | 4 | 3.9 GB | Medium | C45 |
Q4_K_M | 4 | 4.3 GB | Medium | C46 |
Q5_K_M | 5 | 5.0 GB | High | C46 |
Q6_K | 6 | 5.7 GB | High | C46 |
Q8_0 | 8 | 7.5 GB | Very High | C47 |
F16Best for your GPU | 16 | 14.3 GB | Maximum | C51 |
Copy-paste commands to run Vicuna 7B on your machine.
Run
ollama run vicunaYes, RTX A5000 24GB can run Vicuna 7B with a B grade (Runs well). Expected decode speed: 98.0 tok/s.
Vicuna 7B (7B parameters) requires approximately 15.7 GB of memory with Q4_K_M quantization.
The recommended quantization for Vicuna 7B is Q4_K_M, which balances quality and memory efficiency.
On RTX A5000 24GB, Vicuna 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, Vicuna 7B on RTX A5000 24GB receives a B grade with 98.0 tok/s and 4K context.
On RTX A5000 24GB, Vicuna 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/vicuna-7b-on-a5000-24gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
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