Tesla P100 16GB: The Fast Budget GPU Nobody Talks About
Last updated: February 2026
732 GB/s bandwidth for ~$60. The Tesla P100 has over 2x the memory bandwidth of a P40 and costs less than half the price. For models that fit in 16GB, nothing this cheap is this fast.
Why the P100 Is Interesting
Everyone in the budget AI space talks about the Tesla P40. 24GB, great $/GB, solid choice. But the P100 is the card's overlooked sibling with a very different set of strengths.
The P100 uses HBM2 memory instead of GDDR5X. That's the same memory technology used in the A100 and H100. The result is massive bandwidth — 732 GB/s vs the P40's 346 GB/s. For LLM inference, where token generation speed is almost entirely bandwidth-limited, that's a big deal.
The tradeoff: 16GB instead of 24GB. That means smaller models or heavier quantization. But if your model fits, the P100 will generate tokens significantly faster than a P40.
The Specs
| VRAM | 16GB HBM2 |
|---|---|
| Architecture | Pascal (GP100) |
| CUDA Cores | 3584 |
| Memory Bandwidth | 732 GB/s |
| TDP | 250W |
| Compute | 9.3 TFLOPS FP32, 18.7 TFLOPS FP16 |
| Display Output | None |
| Cooling | Passive (requires airflow) |
| Form Factor | SXM2 or PCIe (get PCIe) |
| Release | 2016 |
SXM2 vs PCIe — Read This Before Buying
The P100 comes in two versions:
- PCIe — Standard slot, works in any desktop. This is what you want.
- SXM2 — Server-only form factor. Requires a DGX-1 or HGX baseboard. Useless in a desktop PC. These are often cheaper on eBay — that's why.
If the listing says "SXM2" or shows a card without a PCIe bracket, skip it.
The Bandwidth Advantage
LLM token generation is memory-bandwidth bound. Every token requires reading the full model weights from VRAM. More bandwidth = faster tokens. It's that simple.
| GPU | Bandwidth | VRAM | Price |
|---|---|---|---|
| Tesla M40 | 288 GB/s | 24GB | $80 |
| Tesla P40 | 346 GB/s | 24GB | $170 |
| Tesla P100 | 732 GB/s | 16GB | $60 |
| RTX 3060 12GB | 360 GB/s | 12GB | $200 |
| RTX 3090 | 936 GB/s | 24GB | $800 |
The P100 has bandwidth in the same league as cards costing 5-10x more. Per dollar of bandwidth, nothing touches it.
What You Can Run
16GB is the constraint. Here's what fits:
- Llama 3.1 8B — Q8_0 with full context, very fast
- Qwen 2.5 14B — Q4_K_M with 8K context, good quality
- Mistral 7B / Mistral Nemo 12B — Q6 or Q8, quick inference
- DeepSeek-R1 14B — Q4_K_M, solid reasoning model
- Phi-3 Medium 14B — Q4_K_M, fits nicely
- CodeLlama 13B — Q5 or Q6 for code generation
What won't fit (without extreme quantization):
- Qwen 2.5 32B — needs ~20GB at Q4_K_M
- Llama 3.1 70B — needs 40GB+ even at Q4
- Mixtral 8x7B — needs ~24GB at Q4
This is where the P40 wins. If you need 32B models, the P100's 16GB isn't enough.
Real-World Performance
For models that fit in 16GB, the P100 is noticeably faster than a P40 thanks to that HBM2 bandwidth:
| Model | Quant | P100 Speed | P40 Speed |
|---|---|---|---|
| Llama 3.1 8B | Q4_K_M | ~40-50 t/s | ~25-30 t/s |
| Qwen 2.5 14B | Q4_K_M | ~25-30 t/s | ~15-18 t/s |
| Mistral 7B | Q6_K | ~50-60 t/s | ~30-35 t/s |
Roughly 1.5-2x faster on the same models. That's the HBM2 advantage — and it's real.
Why Buy a P100
- Insane bandwidth per dollar — 732 GB/s for ~$60 is unmatched
- Fast for its price — 1.5-2x faster than P40 for models that fit
- HBM2 memory — Same tech as modern datacenter GPUs
- Native FP16 — Proper half-precision support, unlike M40
- Dirt cheap — $60 is throwaway money for GPU experimentation
- Great for 7B-14B models — Sweet spot for small fast models
The Tradeoffs
- Only 16GB — Can't run 32B+ models that the P40 handles
- No display output — Need a separate GPU for video
- Passive cooling — Same cooling mods as P40 required
- SXM2 trap — Make sure you buy the PCIe version
- No tensor cores — Pascal doesn't have Flash Attention
- 250W TDP — Same power draw as the P40
P100 vs P40: Which One?
This is the real question. Same generation, same cooling needs, same power draw. But very different strengths:
| P100 16GB | P40 24GB | |
|---|---|---|
| Price | ~$60 | ~$170 |
| VRAM | 16GB | 24GB |
| Bandwidth | 732 GB/s | 346 GB/s |
| Token Speed (14B Q4) | ~25-30 t/s | ~15-18 t/s |
| Max Model (Q4) | ~14B | ~32B |
| $/GB | ~$3.75 | ~$7.08 |
Get the P100 if: You mostly run 7B-14B models and want the fastest possible inference on a budget. Also great as a first/experimental AI GPU since it's so cheap.
Get the P40 if: You need to run 32B models, want Mixtral, or plan to use the full 24GB. The P40 is slower per token but fits much larger models.
Get both: They're so cheap you could buy a P100 and a P40 for under $250 and use whichever fits the model. Use the P100 for fast 7B-14B inference and the P40 when you need the VRAM headroom.
The Cooling Situation
Same story as every datacenter GPU — passive heatsink, needs active cooling in a desktop. The P100's cooler is similar to the P40's.
Your options:
- 3D-printed fan shroud with a 92mm blower (~$20-30)
- Zip-tie fans — Strap 2x 120mm fans to the heatsink
- Open-air frame with good case airflow
Budget $20-30 for cooling on top of the card price. At ~$90 all-in, still far cheaper than anything comparable.
Power Connector
Like the P40, the P100 PCIe uses an 8-pin EPS connector (not standard PCIe power). You'll likely need a dual 6-pin PCIe to 8-pin EPS adapter (~$10).
Who Should Buy a P100?
Yes, buy a P100 if:
- You want the fastest possible budget AI card for 7B-14B models
- You're experimenting with local AI and want to spend as little as possible
- You value speed over model size
- You want a second card alongside a P40 for versatility
- You're building a dedicated inference server for smaller models
Consider something else if:
- You need 24GB+ for large models — get a P40
- You want a display output for daily driving
- You need 32B+ model support
- 16GB isn't enough for your use case
Bottom Line
The Tesla P100 is the best-kept secret in budget AI hardware. For ~$60, you get datacenter-class HBM2 bandwidth that makes 7B-14B models fly. It's faster than the P40 for models that fit, and costs a third of the price.
The 16GB limit means it can't touch the P40 for larger models. But for anyone running small-to-medium models, or anyone who just wants the cheapest possible entry into local AI, the P100 is hard to beat.
Current P100 Prices
We track Tesla P100 listings from eBay daily. At ~$60, these are some of the cheapest AI-capable GPUs available.
Related
- Tesla P40 Review — 24GB for $170, the VRAM king
- Tesla M40 Review — 24GB for $80, even cheaper but slower
- Tesla K80 Review — $50 but too old, skip it
- Best GPU for 70B Under $500
- How we estimate inference speed