NVIDIA Tesla P100 — 16GB
Budget datacenter card with 16GB. Older architecture but still handles 14B models.
Specifications
| Brand | NVIDIA |
|---|---|
| Model | Tesla P100 |
| VRAM | 16GB |
| Architecture | Pascal |
| CUDA / Stream Processors | 3,584 |
| Memory Bandwidth | 732 GB/s |
| TDP | 250W |
| FP32 TFLOPS | 9.3 |
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For AI / LLM Use
Good for 14B models. 30B requires aggressive quantisation. Older architecture may have limited software support (check CUDA compatibility). Datacenter card — no display output, may need aftermarket cooling.
What Models Can It Run?
- 14B Q6_K, 30B Q3_K (tight)
- 14B Q4_K_M, 7B full precision
- 7B Q6_K, 14B Q3_K (tight)
- 7B Q4_K_M only
Estimated Performance
Generation: ~55 tokens/sec
Prefill: ~166 tokens/sec
Recommended Quantisations
- Q4_K_M for 14B models
- Q6_K for 7B-8B models
- Q8 for 7B if VRAM allows
Pros & Cons
Pros
Cons
- Older architecture — check CUDA/ROCm compatibility
- No display output — headless only
- May need aftermarket cooling solution
Community Verdict
- r/LocalLLaMA
16GB HBM2 on a budget. Pascal architecture limits software support but handles 14B Q4 models.
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