Explore the complete details of Tesla K8, including specs, performance benchmarks
The Tesla K8 GPU by NVIDIA. features a Kepler (2012−2018) architecture. with 1536 CUDA cores. and a boost clock of 811 MHz MHz. It offers GDDR5 memory with 8 GB GB capacity and a 256 Bit-bit interface. delivering a bandwidth of 160.0 GB/s GB/s. With a power consumption (TDP) of 100W. it supports DirectX 12 (11_0), Vulkan 1.1.126 for enhanced performance.
Basic details about the Tesla K8, including manufacturer, ranking, and release date.
Title | Tesla K8 |
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Manufacturer | NVIDIA |
Ranking | 497 |
Popularity Rank | not in top-100 |
Architecture | Kepler (2012−2018) |
GPU code name | GK104 |
Market Segmente | Workstation |
Length - Width | 241 mm - 1-slot |
Release Date | 16 September 2014 |
Launch Price | $N/A |
Details on clock speeds, cores, and floating-point processing power of Tesla K8.
Core Clock Speed | 693 MHz |
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Boost Clock Speed | 811 MHz |
Floating Point Processing Power | 2.491 TFLOPS |
No of Transistors | 3,540 million |
CUDA Cores | 1536 |
Ray Tracing Cores | N/A |
Tensor Cores | N/A |
Texture Fill Rate | 103.8 |
ROPs | 32 |
Available display connectors and API compatibility for enhanced performance.
Interface | PCIe 2.0 x16 |
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Display Connectors | No outputs |
HDMI | N/A |
DirectX | 12 (11_0) |
Shader Model | 5.1 |
OpenGL | 4.6 |
OpenCL | 1.2 |
Vulkan | 1.1.126 |
CUDA | 3.0 |
DLSS | N/A |
TMUs | 128 |
Information on memory type, capacity, and bandwidth to evaluate data processing power.
Memory Type | GDDR5 |
---|---|
Maximum RAM | 8 GB |
Memory Bus Width | 256 Bit |
Memory Clock Speed | 1250 MHz |
Memory Bandwidth | 160.0 GB/s GB/s |
Resizable BAR | N/A |
Power consumption, efficiency, and additional power requirements.
Power Consumption (TDP) | 100 W |
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Power Efficiency | 6.67 |
Manufacturing Process | 28 nm |
Supplementary Power Connectors | 1x 6-pin |
Here are some of the closest competitors to this GPU. Compare their power consumption, efficiency, and additional power requirements.
Here are some of the closest competitors to this GPU. Compare their power consumption, efficiency, and additional power requirements.