AMD Radeon Pro WX 8200 vs NVIDIA Tesla P40 Comparison

The AMD Radeon Pro WX 8200 and NVIDIA Tesla P40 are both end-of-life professional accelerators, but the benchmark data clearly separates them. In the two head-to-head tests available, the AMD card wins both, with a decisive 12.5% advantage in OpenCL and a narrower 1.3% edge in Vulkan. However, the Tesla P40 counters with a massive 24 GB memory capacity versus 8 GB, a higher 11.76 TFLOPS FP32 peak, and a superior 147.0 GPixel/s pixel rate, making the choice highly workload-dependent.

Head-to-Head Benchmarks

The most significant performance gap appears in the Geekbench OpenCL test. The AMD Radeon Pro WX 8200 scores 69,774, while the NVIDIA Tesla P40 scores 62,017, giving AMD a 12.5% lead. This is a substantial margin, indicating that the GCN 5.0 architecture handles general-purpose compute tasks more efficiently in this benchmark scenario. The result aligns with the AMD card’s higher FP16 throughput of 21.50 TFLOPS, though the OpenCL test primarily measures FP32 and integer workloads.

In Vulkan, the race is much closer. The AMD card scores 69,076 against the Tesla P40’s 68,172, a delta of just 1.3%. While still an AMD victory, this near-parity suggests that graphics-oriented workloads narrow the gap. The Tesla P40’s higher texture rate (367.4 GTexel/s vs 336.0 GTexel/s) and pixel rate (147.0 GPixel/s vs 96.0 GPixel/s) likely help it stay competitive in rasterization tasks, even if it cannot overcome AMD’s compute advantage in this test.

Notably, the Tesla P40 lacks a Geekbench Metal score in the data, while the WX 8200 posts 70,759 in that test. This absence is predictable given the P40’s lack of display outputs, making it unsuitable for Metal-based rendering workflows. The WX 8200’s average benchmark score of 69,870 places it in the 90th percentile of all GPUs, whereas the Tesla P40’s average of 65,095 sits at the 89th percentile, a small but consistent overall gap.

Where Each One Wins

The AMD Radeon Pro WX 8200 wins decisively in compute-heavy, OpenCL-accelerated tasks. Its 12.5% OpenCL advantage suggests superior performance in scientific simulation, financial modeling, and other GPGPU workloads that leverage this API. The card also holds a slight edge in Vulkan, making it the better choice for cross-platform graphics and compute applications that use this modern API. With 4x mini-DisplayPort 1.4a outputs, the WX 8200 is also the only option here for driving multiple displays or VR headsets directly.

The NVIDIA Tesla P40, despite losing both benchmarks, wins in capacity and raw throughput metrics. Its 24 GB of GDDR5 memory is triple the WX 8200’s 8 GB, making it the clear choice for large dataset inference, deep learning model training, or in-memory databases where capacity trumps bandwidth. The P40 also edges out the AMD card in peak FP32 performance at 11.76 TFLOPS versus 10.75 TFLOPS, and its 367.4 GTexel/s texture fill rate is 9.3% higher. For workloads that saturate FP32 cores or texture units—such as certain rendering pipelines—the P40 may complete tasks faster despite losing synthetic benchmarks.

Neither card supports ray tracing or tensor cores, so those features are absent from consideration. The P40’s FP16 performance is a paltry 183.7 GFLOPS (1:64 ratio), making it unsuitable for mixed-precision AI training, while the WX 8200’s 21.50 TFLOPS FP16 (2:1 ratio) provides a 117x advantage in that specific metric, though the test data does not directly measure this.

Architecture Differences

The fundamental split is GCN 5.0 versus Pascal. AMD’s Vega 10 chip uses a 14 nm process from GlobalFoundries, while NVIDIA’s GP102 uses TSMC’s 16 nm node. Transistor counts are close—12,500 million for AMD and 11,800 million for NVIDIA—but the die sizes differ slightly at 495 mm² versus 471 mm², yielding nearly identical transistor densities of 25.3M/mm² and 25.1M/mm² respectively.

Memory architecture diverges sharply. The WX 8200 employs HBM2 with a 2048-bit bus, achieving 512.0 GB/s bandwidth. The Tesla P40 uses GDDR5 on a 384-bit bus, delivering 347.1 GB/s. This means the AMD card has 47.5% more memory bandwidth, crucial for bandwidth-bound compute kernels. However, the P40’s 24 GB capacity provides 200% more storage, a tradeoff between speed and size.

Shading unit counts are similar—3584 for AMD versus 3840 for NVIDIA—but the P40 has more texture mapping units (240 vs 224) and more ROPs (96 vs 64). These differences explain the P40’s higher pixel and texture fill rates. Clock speeds also favor NVIDIA: the P40 boosts to 1531 MHz versus 1500 MHz for the WX 8200, with base clocks of 1303 MHz and 1200 MHz respectively.

API support is largely equivalent for DirectX 12 (12_1) and OpenGL 4.6, but Vulkan differs: the P40 supports Vulkan 1.4 while the WX 8200 is limited to 1.3. This may matter for future software compatibility, though the current benchmark shows the AMD card ahead in Vulkan performance anyway.

Specification Differences

| Specification | AMD Radeon Pro WX 8200 | NVIDIA Tesla P40 |

|---|---|---|

| Process node | 14 nm | 16 nm |

| Foundry | GlobalFoundries | TSMC |

| Transistors | 12,500 million | 11,800 million |

| Die size | 495 mm² | 471 mm² |

| Base clock | 1200 MHz | 1303 MHz |

| Boost clock | 1500 MHz | 1531 MHz |

| Memory size | 8 GB | 24 GB |

| Memory type | HBM2 | GDDR5 |

| Memory bus | 2048 bit | 384 bit |

| Memory bandwidth | 512.0 GB/s | 347.1 GB/s |

| Shading units | 3584 | 3840 |

| TMUs | 224 | 240 |

| ROPs | 64 | 96 |

| Pixel rate | 96.00 GPixel/s | 147.0 GPixel/s |

| Texture rate | 336.0 GTexel/s | 367.4 GTexel/s |

| FP32 | 10.75 TFLOPS | 11.76 TFLOPS |

| FP16 | 21.50 TFLOPS (2:1) | 183.7 GFLOPS (1:64) |

| TDP | 230 W | 250 W |

| Power connectors | 1x 6-pin + 1x 8-pin | 8-pin EPS |

| Suggested PSU | 550 W | 600 W |

| Display outputs | 4x mini-DisplayPort 1.4a | No outputs |

| Vulkan version | 1.3 | 1.4 |

The table highlights that the P40 wins on raw compute peaks (FP32, pixel rate, texture rate) and memory capacity, while the WX 8200 wins on memory bandwidth, FP16 throughput, display connectivity, and lower power draw. The P40’s 250 W TDP versus 230 W for AMD is minor, but its 8-pin EPS connector differs from AMD’s dual connectors, requiring different power supply cabling.

FAQ

Q: Which card has better OpenCL performance?

A: The AMD Radeon Pro WX 8200 scores 69,774 in Geekbench OpenCL, beating the NVIDIA Tesla P40’s 62,017 by 12.5%.

Q: Does the NVIDIA Tesla P40 support display outputs?

A: No, the Tesla P40 has no display outputs, while the AMD Radeon Pro WX 8200 offers 4x mini-DisplayPort 1.4a.

Q: What is the memory capacity difference?

A: The Tesla P40 has 24 GB of GDDR5 memory, which is three times the 8 GB of HBM2 found on the Radeon Pro WX 8200.

Q: Which card has higher memory bandwidth?

A: The AMD Radeon Pro WX 8200 achieves 512.0 GB/s over a 2048-bit HBM2 bus, compared to the Tesla P40’s 347.1 GB/s over a 384-bit GDDR5 bus.

Q: How do their FP32 performances compare?

A: The Tesla P40 reaches 11.76 TFLOPS FP32, slightly ahead of the WX 8200’s 10.75 TFLOPS.

Q: Which card is better for Vulkan workloads?

A: The AMD card wins Geekbench Vulkan with 69,076 versus 68,172 (1.3% lead), but the Tesla P40 supports Vulkan 1.4 while the WX 8200 only supports 1.3.

The Verdict

Choose the AMD Radeon Pro WX 8200 if your priority is compute performance in OpenCL or Vulkan, memory bandwidth, or FP16 throughput. The data shows it wins both head-to-head benchmarks, and its HBM2 memory provides 512.0 GB/s bandwidth that is 47.5% higher than the Tesla P40’s. It also has display outputs for visualization work and a lower 230 W TDP. This card suits scientific computing, machine learning inference that benefits from FP16, and any workstation role requiring monitor connectivity.

Choose the NVIDIA Tesla P40 if you need maximum memory capacity or peak FP32, pixel, or texture rates. Its 24 GB GDDR5 is essential for models or datasets that exceed 8 GB, and its 11.76 TFLOPS FP32, 147.0 GPixel/s pixel rate, and 367.4 GTexel/s texture rate all exceed the AMD card’s figures. The P40 is a server-oriented accelerator for deep learning inference with large batch sizes or rendering tasks where memory size prevents out-of-core failures. It also supports Vulkan 1.4, offering slightly newer API compliance.

The verdict hinges on workload profile. For interactive workstations and bandwidth-hungry compute, the WX 8200 wins. For massive-memory, headless server deployments, the P40 is the logical pick despite losing the two benchmark tests.