Explore the complete details of Quadro K500M, including specs, performance benchmarks
The Quadro K500M GPU by Unknown. features a Kepler (2012−2018) architecture. with 192 CUDA cores. It offers DDR3 memory with 1 GB GB capacity and a 64 Bit-bit interface. delivering a bandwidth of 12.8 GB/s GB/s. With a power consumption (TDP) of 35W.
Basic details about the Quadro K500M, including manufacturer, ranking, and release date.
| Title | Quadro K500M |
|---|---|
| Manufacturer | Unknown |
| Ranking | 1086 |
| Popularity Rank | not in top-100 |
| Architecture | Kepler (2012−2018) |
| GPU code name | GK107 |
| Market Segmente | Mobile workstation |
| Length - Width | N/A - N/A |
| Release Date | 1 June 2012 |
| Launch Price | $N/A |
Details on clock speeds, cores, and floating-point processing power of Quadro K500M.
| Core Clock Speed | 850 MHz |
|---|---|
| Boost Clock Speed | N/A |
| Floating Point Processing Power | 0.3264 TFLOPS |
| No of Transistors | 1,270 million |
| CUDA Cores | 192 |
| Ray Tracing Cores | N/A |
| Tensor Cores | N/A |
| Texture Fill Rate | 13.60 |
| ROPs | 8 |
Available display connectors and API compatibility for enhanced performance.
| Interface | MXM-A (3.0) |
|---|---|
| Display Connectors | No outputs |
| HDMI | N/A |
| DirectX | N/A |
| Shader Model | N/A |
| OpenGL | N/A |
| OpenCL | N/A |
| Vulkan | N/A |
| CUDA | N/A |
| DLSS | N/A |
| TMUs | 16 |
Information on memory type, capacity, and bandwidth to evaluate data processing power.
| Memory Type | DDR3 |
|---|---|
| Maximum RAM | 1 GB |
| Memory Bus Width | 64 Bit |
| Memory Clock Speed | 800 MHz |
| Memory Bandwidth | 12.8 GB/s GB/s |
| Resizable BAR | N/A |
Power consumption, efficiency, and additional power requirements.
| Power Consumption (TDP) | 35 W |
|---|---|
| Power Efficiency | 2.46 |
| Manufacturing Process | 28 nm |
| Supplementary Power Connectors | N/A |
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.
