Yi 1.5 9B needs ~10.6 GB VRAM. RTX A5000 24GB has 24.0 GB. With Q4_K_M quantization, expect ~107 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
106.5 tok/s
TTFT
1818 ms
Safe context
4K
Memory
10.6 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 | B | Runs well | 106.5 tok/s | 992 ms | 4K |
| Coding | B | Runs well | 106.5 tok/s | 1818 ms | 4K |
| Agentic Coding | B | Runs well | 106.5 tok/s | 2644 ms | 4K |
| Reasoning | B | Runs well | 106.5 tok/s | 2149 ms | 4K |
| RAG | B | Runs well | 106.5 tok/s | 3305 ms | 4K |
How Yi 1.5 9B (9B params) fits at each quantization level on RTX A5000 24GB (24.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 3.5 GB | Low | C49 |
Q3_K_S | 3 | 4.4 GB | Low | C50 |
NVFP4 | 4 | 5.0 GB | Medium | C50 |
Q4_K_M | 4 | 5.5 GB | Medium | C50 |
Q5_K_M | 5 | 6.5 GB | High | C51 |
Q6_K | 6 | 7.4 GB | High | C51 |
Q8_0 | 8 | 9.6 GB | Very High | C53 |
F16Best for your GPU | 16 | 18.5 GB | Maximum | C54 |
Copy-paste commands to run Yi 1.5 9B on your machine.
Run
lms load Yi-1.5-9B-Chat && lms server startYes, RTX A5000 24GB can run Yi 1.5 9B with a B grade (Runs well). Expected decode speed: 106.5 tok/s.
Yi 1.5 9B (9B parameters) requires approximately 10.6 GB of memory with Q4_K_M quantization.
The recommended quantization for Yi 1.5 9B is Q4_K_M, which balances quality and memory efficiency.
On RTX A5000 24GB, Yi 1.5 9B achieves approximately 106.5 tokens per second decode speed with a time-to-first-token of 1818ms using Q4_K_M quantization.
For coding workloads, Yi 1.5 9B on RTX A5000 24GB receives a B grade with 106.5 tok/s and 4K context.
On RTX A5000 24GB, Yi 1.5 9B 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/yi-1.5-9b-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>
Preview: