Tesla V100 PCIe 16 GB vs GeForce GT 640M LE
Primary details
GPU architecture, market segment, value for money and other general parameters compared.
| Place in the ranking | 918 | not rated |
| Place by popularity | not in top-100 | not in top-100 |
| Cost-effectiveness evaluation | 0.06 | no data |
| Power efficiency | 3.94 | no data |
| Architecture | Fermi (2010−2014) | Volta (2017−2020) |
| GPU code name | GF108 | GV100 |
| Market segment | Laptop | Workstation |
| Release date | 4 May 2012 (12 years ago) | 21 June 2017 (7 years ago) |
| Launch price (MSRP) | $849.99 | no data |
Cost-effectiveness evaluation
Performance to price ratio. The higher, the better.
Detailed specifications
General parameters such as number of shaders, GPU core base clock and boost clock speeds, manufacturing process, texturing and calculation speed. Note that power consumption of some graphics cards can well exceed their nominal TDP, especially when overclocked.
| Pipelines / CUDA cores | Up to 384 | 5120 |
| Core clock speed | Up to 500 MHz | 1246 MHz |
| Boost clock speed | no data | 1380 MHz |
| Number of transistors | 585 million | 21,100 million |
| Manufacturing process technology | 40 nm | 12 nm |
| Power consumption (TDP) | 20 Watt | 300 Watt |
| Texture fill rate | 12.05 | 441.6 |
| Floating-point processing power | 0.289 TFLOPS | 14.13 TFLOPS |
| ROPs | 4 | 128 |
| TMUs | 16 | 320 |
| Tensor Cores | no data | 640 |
Form factor & compatibility
Information on compatibility with other computer components. Useful when choosing a future computer configuration or upgrading an existing one. For desktop graphics cards it's interface and bus (motherboard compatibility), additional power connectors (power supply compatibility).
| Laptop size | medium sized | no data |
| Bus support | PCI Express 2.0, PCI Express 3.0 | no data |
| Interface | PCIe 2.0 x16 | PCIe 3.0 x16 |
| Width | no data | 2-slot |
| Supplementary power connectors | no data | 2x 8-pin |
VRAM capacity and type
Parameters of VRAM installed: its type, size, bus, clock and resulting bandwidth. Integrated GPUs have no dedicated video RAM and use a shared part of system RAM.
| Memory type | DDR3\DDR5 | HBM2 |
| Maximum RAM amount | 2 GB | 16 GB |
| Memory bus width | 128bit | 4096 Bit |
| Memory clock speed | 785 MHz | 876 MHz |
| Memory bandwidth | Up to 28.8 GB/s | 897.0 GB/s |
| Shared memory | - | - |
Connectivity and outputs
Types and number of video connectors present on the reviewed GPUs. As a rule, data in this section is precise only for desktop reference ones (so-called Founders Edition for NVIDIA chips). OEM manufacturers may change the number and type of output ports, while for notebook cards availability of certain video outputs ports depends on the laptop model rather than on the card itself.
| Display Connectors | No outputs | No outputs |
| HDMI | + | - |
| HDCP | + | - |
| Maximum VGA resolution | Up to 2048x1536 | no data |
Supported technologies
Supported technological solutions. This information will prove useful if you need some particular technology for your purposes.
| 3D Blu-Ray | + | - |
| Optimus | + | - |
API compatibility
List of supported 3D and general-purpose computing APIs, including their specific versions.
| DirectX | 12 API | 12 (12_1) |
| Shader Model | 5.1 | 6.4 |
| OpenGL | 4.5 | 4.6 |
| OpenCL | 1.1 | 1.2 |
| Vulkan | N/A | 1.2.131 |
| CUDA | + | 7.0 |
Pros & cons summary
| Recency | 4 May 2012 | 21 June 2017 |
| Maximum RAM amount | 2 GB | 16 GB |
| Chip lithography | 40 nm | 12 nm |
| Power consumption (TDP) | 20 Watt | 300 Watt |
GT 640M LE has 1400% lower power consumption.
Tesla V100 PCIe 16 GB, on the other hand, has an age advantage of 5 years, a 700% higher maximum VRAM amount, and a 233.3% more advanced lithography process.
We couldn't decide between GeForce GT 640M LE and Tesla V100 PCIe 16 GB. We've got no test results to judge.
Be aware that GeForce GT 640M LE is a notebook card while Tesla V100 PCIe 16 GB is a workstation one.
Should you still have questions concerning choice between the reviewed GPUs, ask them in Comments section, and we shall answer.
Comparisons with similar GPUs
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