NVIDIA Tesla PG500-216

The NVIDIA Tesla PG500-216 is a data-center oriented accelerator built on the Volta architecture, featuring the GV100 chip on a 12 nm TSMC process. It packages 21,100 million transistors on an 815 mm² die, yielding a transistor density of 25.9M per mm², and it was released on 2019-11-25 as part of the Tesla Volta generation. This card is now end-of-life, with no display outputs and a PCIe 3.0 x16 interface, targeting compute workloads rather than consumer gaming.

How It Compares

The benchmark database currently lists no nearest rivals for the Tesla PG500-216, and its average benchmark score is recorded as 0. This places it at the 50th percentile of all GPUs, meaning it sits exactly at the midpoint of the performance distribution when compared against every other GPU in the database. Without rival scores or deltaPct values, direct positional comparisons cannot be made, but the percentile indicates that half of all tracked GPUs score higher and half score lower.

Since no nearestRivals data exists, the Tesla PG500-216 cannot be positioned against specific competing models in terms of percentage deltas. Its percentile of 50 suggests it is not an outlier in either direction, but rather a middle-of-the-pack performer when viewed across the entire GPU landscape. The absence of benchmark scores reinforces that this is a specialized compute product, not a typical consumer graphics card.

The production status of end-of-life means the card is no longer actively manufactured, and its predecessor is listed as Tesla Pascal while its successor is Tesla Turing. This places it in the Volta generation, which bridges the Pascal and Turing eras in NVIDIA’s data-center lineup, and the architecture name Volta confirms this mid-generation positioning.

Who Should Consider It

Given the Tesla PG500-216 has no benchmark scores and no display outputs, it is not suited for traditional gaming or interactive rendering workloads. The card offers 32 GB of HBM2 memory with a 4096-bit bus and 1.13 TB/s of bandwidth, which points toward high-capacity, bandwidth-intensive compute tasks such as large-scale data processing, scientific simulations, or machine learning inference. The 640 tensor cores and fp16 performance of 28.26 TFLOPS (2:1) suggest it can handle mixed-precision workloads that benefit from tensor operations.

For resolutions, the lack of display outputs means no direct rasterization at any resolution is possible. However, if used for off-screen compute or rendering tasks, the 32 GB frame buffer and 1.13 TB/s bandwidth would theoretically support very high-resolution textures or large datasets without memory pressure. The 5120 shading units and 128 ROPs provide a pixel rate of 176.6 GPixel/s, which could handle high-resolution off-screen rendering, but the card is not designed for interactive use.

The card’s 250 W TDP and dual-slot design make it suitable for server environments where power density is managed. Users with compute-heavy pipelines that require large memory capacity and high bandwidth, but who do not need display output, would find this card appropriate. The absence of a suggested PSU rating beyond 600 W means typical workstation power supplies can accommodate it, but it is not a consumer gaming card.

Benchmark Performance

The Tesla PG500-216 has an average benchmark score of 0 and no recorded benchmarks in the database, which prevents any quantitative performance analysis against rivals. The percentile of 50 indicates that, if it were scored, it would rank exactly at the median of all GPUs, but without actual scores, this is only a positional reference. The fp32 compute of 14.13 TFLOPS and fp16 of 28.26 TFLOPS (2:1) are the only performance metrics available, and they describe raw compute throughput rather than game or application scores.

The texture rate of 441.6 GTexel/s and pixel rate of 176.6 GPixel/s are derived from the 320 TMUs and 128 ROPs, respectively, at the boost clock of 1380 MHz. These rates are relevant for fill-rate-bound tasks but do not translate directly into benchmark scores. The 50th percentile suggests that the hardware’s raw specifications align with a mid-tier GPU in the overall database, but the lack of comparative data means no percentage deltas can be cited.

Because no nearestRivals are provided, there are no deltaPct values to reference for multi-core or single-core comparisons. The absence of benchmark scores also means the card’s real-world performance in popular suites is unknown from this data. The 14.13 TFLOPS fp32 figure is the only concrete compute number, and it indicates a capable but not exceptional compute throughput for its era.

FAQ

Q: Does the Tesla PG500-216 support DirectX?

A: Yes, it supports DirectX 12 (12_1), along with OpenGL 4.6 and Vulkan 1.4.

Q: What is the memory configuration of this card?

A: It has 32 GB of HBM2 memory with a 4096-bit bus width and a bandwidth of 1.13 TB/s.

Q: How many tensor cores does it have?

A: It has 640 tensor cores, which contribute to its fp16 performance of 28.26 TFLOPS (2:1).

Q: What power connector does it require?

A: It has no power connectors, meaning it draws power solely from the PCIe slot, and the suggested PSU is 600 W.

Q: Is this card still in production?

A: No, it is end-of-life, with a release date of 2019-11-25 and a successor in the Tesla Turing generation.

Q: What is the process node and die size?

A: The chip is fabricated on a 12 nm TSMC process with a die size of 815 mm² and 21,100 million transistors.

Memory Subsystem

The Tesla PG500-216 is equipped with 32 GB of HBM2 memory, which is a high-bandwidth memory type designed for compute workloads. The bus width is 4096 bits, which is exceptionally wide, and this combines with a memory clock of 1106 MHz (2.2 Gbps effective) to produce a total bandwidth of 1.13 TB/s. This bandwidth figure is critical for memory-bound tasks, as it allows large data sets to be fed to the compute units without stalling.

For high-resolution work, the 32 GB capacity is substantial, enabling large frame buffers or massive datasets to reside entirely on the card. The 1.13 TB/s bandwidth ensures that data movement across the 4096-bit bus does not become a bottleneck, which is particularly important for fp16 workloads that rely on tensor cores. The memory type HBM2 is physically stacked on the die, which reduces the footprint and allows the dual-slot design to remain compact.

The combination of 32 GB capacity and 1.13 TB/s bandwidth places this card well above typical consumer GPUs in memory throughput, but it lacks display outputs so this memory cannot be used for direct rendering output. In off-screen compute contexts, the memory subsystem would support extremely high-resolution render targets or large neural network models. The 4096-bit bus is unusual outside of data-center parts, and it directly contributes to the bandwidth figure that defines the card’s compute character.

Power and Cooling

The Tesla PG500-216 has a TDP of 250 W, which is moderate for a compute accelerator of this class, and it is designed as a dual-slot card. The power connectors are listed as none, meaning the card draws all power through the PCIe 3.0 x16 slot, which is unusual for a 250 W part but consistent with server-oriented designs that rely on board power delivery. The suggested PSU is 600 W, which is a conservative recommendation that accounts for the rest of the system’s components.

Cooling is handled by the dual-slot form factor, which allows for a substantial heatsink and fan assembly to dissipate the 250 W of heat. The absence of power connectors simplifies installation in servers where cable management is critical, but it also means the motherboard must provide adequate power through the PCIe slot. The 12 nm process node and 21,100 million transistors generate heat across the 815 mm² die, and the dual-slot cooler is designed to manage this within a standard chassis.

For system builders, the 600 W suggested PSU is a baseline, and the lack of external power connectors means no specialized cables are required. The card’s end-of-life status may affect availability, but its power and cooling requirements are straightforward: a dual-slot PCIe slot and a PSU with at least 600 W capacity. The TDP of 250 W is the only power figure provided, and it indicates the card is not overly power-hungry relative to its compute capabilities.