NVIDIA Tesla P40

The Tesla P40 is a vintage datacenter GPU from 2016 that has found new life in the local AI community. With 24 GB of GDDR5 memory and used prices around $150, it's the absolute cheapest way to get 24 GB VRAM. The caveats are significant: no display outputs (passive server card), Pascal architecture (no FP16/BF16), and requires active cooling mods.

Quick verdict

The Tesla P40 is the ultimate budget local AI experimenter's card. 24 GB for $150 is unmatched VRAM-per-dollar. But it's slow (~5-8 tok/s on 30B models), doesn't support modern precision formats, and needs cooling mods. Perfect for learning or batch inference where speed isn't critical.

Spec breakdown

• VRAM: 24 GB GDDR5
• Memory bandwidth: 347 GB/s
• TDP: 250 W (passive - needs active cooling)
• PCIe: 3.0 ×16
• Architecture: Pascal GP102
• CUDA cores: 3,840
• Tensor cores: None (no TensorRT optimization)

Real-world AI inference

Model	Tokens/sec	Source
Qwen3-30B Q4_K_M	~5 tok/s	r/LocalLLaMA
Mistral Small 3 Q4_K_M	~10 tok/s	Community
Llama 3.1 8B Q4_K_M	~20 tok/s	Community
Dual P40 - 70B Q3_K_M	~4 tok/s	Community

Where to buy

• eBay: ~$150-200
• Requires: Active cooling fan mod (3D printed shroud)

Honest alternatives

• Used RTX 3060 12GB (~$200): Faster, easier to use, less VRAM
• Used RTX 3090 (~$700): Much faster, same VRAM, higher cost
• Intel Arc A770 16GB (~$200): Modern, easier setup

What the community says

"Bought two P40s for $120 each. Slapped 3D-printed fans on them. 48 GB total for $240. Runs 70B at Q3_K_M at 4 tok/s. It's janky but it works!"

• u/jank-ai on r/LocalLLaMA, 278 upvotes