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Run your most demanding scientific models on NVIDIA® Tesla® GPU Accelerators. Based on the NVIDIA Kepler™ Architecture, Tesla GPUs are designed to deliver faster, more efficient compute performance.

With the introduction of Tesla K40 GPU Accelerators, you can run big scientific models on its 12GB of GPU accelerator memory, capable of processing 2x larger datasets and ideal for big data analytics. It also outperforms CPUs by up to 10x with its GPU Boost feature, converting power headroom into user-controlled performance boost. Try a Tesla K40 GPU today for free.

Tesla K40Where to Buy


Select the Right Tesla GPU

Features Tesla K40 Tesla K20X Tesla K20 Tesla K10
Number and Type of GPU 1 Kepler GK110B 1 Kepler GK110 2 Kepler GK104s
Peak double precision floating
point performance
1.43 Tflops 1.31 Tflops 1.17 Tflops 0.19 Tflops
Peak single precision floating
point performance
4.29 Tflops 3.95 Tflops 3.52 Tflops 4.58 Tflops
Memory bandwidth (ECC off) 288 GB/sec 250 GB/sec 208 GB/sec 320 GB/sec
Memory size (GDDR5) 12 GB 6 GB 5 GB 8 GB
CUDA cores 2880 2688 2496 2 x 1536

* Note: Tesla K10 specifications are shown as aggregate of two GPUs. With ECC on, 6.25% of the GPU memory is used for ECC bits. For example, 6 GB total memory yields 5.25 GB of user available memory with ECC on.



A complete list of supported operating systems is available at:


Tesla 20-series GPUs
> Tesla M-Class GPU modules  PDF


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Discuss Tesla products, talk about CUDA development, and share interesting issues, tips and solutions with your fellow NVIDIA Tesla users on the GPU computing forums.

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