Yi 1.5 9B needs ~9.8 GB VRAM. Tesla P100 16GB has 16.0 GB. With Q4_K_M quantization, expect ~86 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
85.5 tok/s
TTFT
2263 ms
Safe context
4K
Memory
9.8 GB / 16.0 GB
This setup is broadly balanced for this model.
Older PCIe generation
PCIe 3.0 is workable, but it compounds the penalty when you offload heavily or try to scale across multiple cards.
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Chat | B | Runs well | 85.5 tok/s | 1234 ms | 4K |
| Coding | B | Runs well | 85.5 tok/s | 2263 ms | 4K |
| Agentic Coding | B | Runs well | 85.5 tok/s | 3292 ms | 4K |
| Reasoning | B | Runs well | 85.5 tok/s | 2674 ms | 4K |
| RAG | B | Runs well | 85.5 tok/s | 4115 ms | 4K |
How Yi 1.5 9B (9B params) fits at each quantization level on Tesla P100 16GB (16.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 3.5 GB | Low | C52 |
Q3_K_S | 3 | 4.4 GB | Low | C53 |
NVFP4 | 4 | 5.0 GB | Medium | C53 |
Q4_K_M | 4 | 5.5 GB | Medium | C54 |
Q5_K_M | 5 | 6.5 GB | High | C55 |
Q6_K | 6 | 7.4 GB | High | B56 |
Q8_0Best for your GPU | 8 | 9.6 GB | Very High | B56 |
F16 | 16 | 18.5 GB | Maximum | F0 |
Copy-paste commands to run Yi 1.5 9B on your machine.
Run
lms load Yi-1.5-9B-Chat && lms server startYes, Tesla P100 16GB can run Yi 1.5 9B with a B grade (Runs well). Expected decode speed: 85.5 tok/s.
Yi 1.5 9B (9B parameters) requires approximately 9.8 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 Tesla P100 16GB, Yi 1.5 9B achieves approximately 85.5 tokens per second decode speed with a time-to-first-token of 2263ms using Q4_K_M quantization.
For coding workloads, Yi 1.5 9B on Tesla P100 16GB receives a B grade with 85.5 tok/s and 4K context.
On Tesla P100 16GB, 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-tesla-p100-16gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
Preview: