Can Qwen 3 14B run on Tesla P100 16GB?
YES — Tight Fit
Qwen 3 14B needs ~13.8 GB VRAM. Tesla P100 16GB has 16.0 GB. With Q4_K_M quantization, expect ~55 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
Tight fit
Decode
54.6 tok/s
TTFT
3545 ms
Safe context
31K
Memory
13.8 GB / 16.0 GB
Memory breakdown
See how fast it feels
What limits this setup
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.
Best improvement path
Performance by workload
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Chat | S | Runs well | 54.6 tok/s | 1933 ms | 31K |
| Coding | S | Tight fit | 54.6 tok/s | 3545 ms | 31K |
| Agentic Coding | S | Runs with offload (needs ~0.1 GB host RAM) | 38.6 tok/s | 7287 ms | 31K |
| Reasoning | S | Tight fit | 54.6 tok/s | 4189 ms | 31K |
| RAG | S | Runs with offload (needs ~0.1 GB host RAM) | 38.6 tok/s | 9108 ms |
Quantization options
How Qwen 3 14B (14B params) fits at each quantization level on Tesla P100 16GB (16.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 5.5 GB | Low | S90 |
Q3_K_S | 3 | 6.9 GB | Low | S91 |
NVFP4 | 4 |
Get started
Copy-paste commands to run Qwen 3 14B on your machine.
Run
ollama run qwen3