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Tesla M2090 | Tesla M2075 | Tesla M2070-Q |
| Product brief
Download (412 KB PDF) |
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| GPGPU Performance | Highest Performance | Mid-Range Performance | Mid-Range Performance |
| GPU Computing Applications | Seismic processing, CFD, CAE, Financial computing, Computational chemistry and Physics, Data analytics, Satellite imaging, Weather modeling | ||
| Visualization Applications | N/A | N/A | CAD, CAM, CAE pre/post processing Remote desktop |
| Peak double precision floating point performance | 665 Gigaflops | 515 Gigaflops | 515 Gigaflops |
| Peak single precision floating point performance | 1331 Gigaflops | 1030 Gigaflops | 1030 Gigaflops |
| Memory bandwidth (ECC off) | 177 GBytes/sec | 150 GBytes/sec | 150 GBytes/sec |
| Memory size (GDDR5) | 6 GigaBytes | 6 GigaBytes | 6 GigaBytes |
| CUDA cores | 512 | 448 | 448 |
* Note: With ECC on, 12.5% of the GPU memory is used for ECC bits. For example, 3 GB total memory yields 2.625 GB of user available memory with ECC on.
NVIDIA recommends getting drivers for M-class products from system OEMs. Please visit the NVIDIA Driver Downloads page for the latest Tesla M-class drivers.
Tesla M-class products are supported underClick here to learn more about drivers and cluster management software tools for Tesla data center products.
Click here to learn more about C, C++, Fortran, and OpenCL software development tools for Tesla GPUs.