Tesla P100 16GB Review: The Fast Budget GPU Nobody Talks About
Everyone talks about the Tesla P40 as the budget AI GPU king, and for good reason - 24GB of VRAM at dirt cheap prices is hard to beat. But the Tesla P100 16GB deserves more attention. Its HBM2 memory gives it significantly more bandwidth than the P40, making it faster for LLM inference per-token generation despite having less VRAM.
| GPU Architecture | Pascal (GP100) |
|---|---|
| CUDA Cores | 3,584 |
| VRAM | 16GB HBM2 |
| Memory Bandwidth | 732 GB/s |
| FP32 Performance | 9.3 TFLOPS |
| FP16 Performance | 18.7 TFLOPS (native) |
| TDP | 250W |
| Cooling | Passive (requires server airflow) |
| Typical Used Price | $150-200 (PCIe), $100-150 (SXM2) |
The Bandwidth Advantage
The P100's defining feature is its HBM2 memory. While the P40 uses GDDR5X at 347 GB/s, the P100 delivers 732 GB/s - more than double. Since LLM token generation is memory-bandwidth-bound (see our speed estimation methodology), this translates directly to faster inference.
| GPU | Memory Type | Bandwidth | Est. tok/s (8B Q4) | Typical Price |
|---|---|---|---|---|
| Tesla M40 24GB | GDDR5 | 288 GB/s | ~35 | $80 |
| Tesla P40 24GB | GDDR5X | 347 GB/s | ~45 | $150 |
| Tesla P100 16GB | HBM2 | 732 GB/s | ~80 | $170 |
| RTX 3090 24GB | GDDR6X | 936 GB/s | ~130 | $700 |
The P100 delivers nearly double the generation speed of the P40 for models that fit in 16GB. That's a meaningful difference in interactive use - the difference between 45 tok/s (readable but slow) and 80 tok/s (fast, fluid reading speed).
P100 vs P40: Which Should You Buy?
| Factor | P100 16GB | P40 24GB | Winner |
|---|---|---|---|
| VRAM | 16GB | 24GB | P40 - 50% more VRAM |
| Bandwidth | 732 GB/s | 347 GB/s | P100 - 2x faster |
| FP16 Support | Native (18.7 TFLOPS) | None (INT8 only) | P100 - full FP16 |
| NVLink | Yes (SXM2 version) | No | P100 |
| Price | $150-200 | $130-170 | P40 - slightly cheaper |
| Max model (Q4) | ~14B comfortably | ~24B comfortably | P40 - bigger models |
| Cooling | Passive | Passive | Tie - both need aftermarket |
Choose the P100 if: You primarily run 7B-14B models and want the fastest possible generation speed. Also if you need FP16 for training or fine-tuning.
Choose the P40 if: You want to run larger models (up to ~24B at Q4) and VRAM capacity matters more than speed.
What Can You Run on 16GB?
- Llama 3 8B (Q4) - ~4GB, fits easily. This is the sweet spot. Fast inference at ~80 tok/s.
- Llama 3 8B (Q8) - ~8GB, fits well with room for context.
- Mistral 7B / Qwen 7B - Same class as above, excellent performance.
- Llama 3 14B (Q4) - ~7.5GB, fits with decent context window.
- Deepseek Coder 33B (Q2/Q3) - Tight fit, heavy quantization reduces quality.
- Llama 3 70B - Does NOT fit. Need 40GB+ for Q4.
The PCIe vs SXM2 Question
Important: Two P100 Form Factors
The P100 comes in two versions:
- PCIe version ($150-200) - Standard PCIe card, drops into any system. This is what most people want.
- SXM2 version ($100-150) - Cheaper, but requires a special SXM2 socket found only in specific server motherboards (like the DGX-1). Has NVLink support. Not recommended unless you already have the right server.
Make sure you buy the PCIe version unless you have a server with SXM2 sockets.
Cooling
Like the P40 and M40, the P100 is a passively-cooled data center card. It has no fans and relies on server chassis airflow. In a desktop PC, you must add aftermarket cooling:
- 3D-printed fan shroud with a 92mm fan (search "P100 fan shroud" on Thingiverse/Printables)
- Zip-tied fan - Crude but effective. A 92mm Noctua fan zip-tied to the heatsink works
- Keep temps below 85C under sustained load
Verdict
Buy It If Speed Matters More Than VRAM
The Tesla P100 16GB is an overlooked gem. At $150-200, you get 2x the memory bandwidth of a P40, native FP16 support, and genuinely fast LLM inference for models up to 14B parameters. If your use case fits within 16GB of VRAM, the P100 delivers a better experience than the P40 at a similar price.
However, if you need the flexibility to run larger models or want to experiment with 20B+ parameter models at various quantizations, the P40's 24GB of VRAM is more versatile. For most beginners, we still recommend starting with the P40 for its flexibility.
Pros
- 732 GB/s HBM2 bandwidth - fastest in its price range
- Native FP16 support (18.7 TFLOPS)
- Excellent for 7B-14B models
- NVLink support on SXM2 variant
- Often cheaper than a P40
Cons
- Only 16GB VRAM (vs P40's 24GB)
- Can't fit 20B+ models at Q4
- Passive cooling needs aftermarket solution
- No display output
- SXM2 version is a trap for desktop users