NVIDIA P40 24GB Used GPU: Best Budget LLM Card in 2026?

The NVIDIA Tesla P40 is a 2016 data center GPU with 24GB GDDR5 memory. In 2026, used P40s are available for $150-$250 — making them the best VRAM-per-dollar option for running large language models locally. Here is everything you need to know before buying one.

P40 Specs for LLM Inference

SpecP40RTX 3090RTX 4090
VRAM24 GB GDDR524 GB GDDR6X24 GB GDDR6X
Memory BW347 GB/s936 GB/s1,008 GB/s
TDP250W (passive)350W450W
Street Price (2026)$150-$250$400-$500$950-$1,100
LLM Token Speed~35 tok/s (8B)~88 tok/s (8B)~120 tok/s (8B)

The Catch: Passive Cooling

P40 is a data-center card with passive cooling only — no fans, no display outputs. You need to:

  • Mount it in a well-ventilated case with strong airflow
  • Add an aftermarket active cooling solution ($20-$50 fan brackets available)
  • Use a PCIe riser if your case has clearance issues
  • No display output — needs a separate GPU for desktop (or use headless)

Linux Setup

# P40 is Pascal architecture (SM 6.1) — fully supported in CUDA 11+
nvidia-smi  # verify detection
# Expected output: Tesla P40 | 24MiB | 250W

# Build llama.cpp with P40 support
cmake -B build -DGGML_CUDA=ON -DCMAKE_CUDA_ARCHITECTURES=61
cmake --build build -j12

./build/bin/llama-server   -m ./models/qwen3.6-32b-q4_k_m.gguf   --n-gpu-layers 999   --ctx-size 16384   --host 0.0.0.0 --port 8080

Is the P40 Worth It?

At $200, the P40 gives you 24GB VRAM — the same as an RTX 4090 — for 1/5th the price. Token generation speed is 3x slower due to GDDR5 bandwidth, but you can run 32B models fully on GPU. It is the best entry point for 32B-class models on a strict budget. For full price/performance comparisons, LLMHardware.io's budget GPU guide has detailed analysis.

Best use case: Run P40 alongside an RTX 4060/4070 — use the gaming card for display and the P40 as a pure inference card. Combined for under $600, you get 24GB dedicated LLM VRAM plus display capability.

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