NVIDIA H100 SXM5 64 GB

The NVIDIA H100 SXM5 64 GB is a server-class accelerator built on the Hopper architecture, using the GH100 chip fabricated on TSMC's 5 nm process. The die contains 80,000 million transistors across an 814 mm² area, giving a transistor density of 98.3 million per square millimeter. In the benchmark database, this part currently holds the 50th percentile position among all GPUs, though no benchmark scores have been recorded for it — the average benchmark score sits at zero. This is a compute-first product with no display outputs, no recorded graphics API support, and a power envelope that assumes a server chassis rather than a desktop tower.

How It Compares

The nearestRivals list is empty in the database, which means there are no direct competitor entries to anchor a comparison. This is typical for a server accelerator that shares the database with consumer GPUs — the H100's specifications place it in a different category entirely. Its 50th percentile rank among all GPUs reflects the absence of recorded benchmark scores rather than a measured performance level; a zero average score drags the percentile down despite the hardware's theoretical capabilities.

Against its own lineage, the H100 SXM5 sits between the Server Ada generation that preceded it and the Server Blackwell generation that follows. The production status is listed as Active, and it was released on 2023-03-20. The SXM5 form factor is a module, not a PCIe card, which separates it from slot-based accelerators in the same server ecosystem.

Since no rival deltas are available, the comparison must rely on the compute figures in the fact pack. The FP32 throughput of 66.91 TFLOPS and FP16 throughput of 267.6 TFLOPS (4:1 ratio) define a device aimed at dense numerical workloads rather than rasterized graphics. The 24 ROPs and 528 TMUs are modest by gaming GPU standards, but the 16,896 shading units and 528 tensor cores tell the real story — this is a tensor-throughput machine.

Ray Tracing and Feature Set

The fact pack does not list a ray tracing core count — the RT cores field is null. That absence is meaningful: the H100 SXM5 is not marketed as a real-time ray tracing part, and with no display outputs and no recorded DirectX, OpenGL, or Vulkan support, it is not designed to drive a monitor or run a conventional graphics API workload. The 528 tensor cores are the headline feature, paired with FP16 throughput of 267.6 TFLOPS at a 4:1 ratio — that ratio indicates tensor-accelerated compute paths are prioritized over general-purpose FP32 work.

The Hopper architecture's focus is server-scale compute. The PCIe 5.0 x16 bus interface provides host connectivity, but the SXM module form factor implies direct board integration in a server node rather than user-upgradeable expansion. The lack of display outputs reinforces the compute-only design; there is no video encoder or decoder listed, no output ports, and no graphics API support recorded. Buyers evaluating this part should treat it as an accelerator for training and inference workloads, not as a graphics card.

Benchmark Performance

The database contains no benchmark entries for the H100 SXM5 — the benchmarks array is empty and the average benchmark score is zero. This makes a direct performance comparison impossible from the recorded data. However, the theoretical compute figures provide a basis for expectation. The FP32 rate of 66.91 TFLOPS is the peak single-precision throughput, while the FP16 rate of 267.6 TFLOPS at a 4:1 ratio represents the tensor-heavy path. Pixel fill rate is 47.52 GPixel/s and texture fill rate is 1,045.4 GTexel/s — figures that matter less for a compute accelerator but are recorded nonetheless.

The 50th percentile rank against all GPUs in the database is a statistical artifact of the missing benchmark data. A zero score places the H100 in the middle of the distribution, but that does not reflect real-world performance — it reflects the absence of recorded runs. In practice, the 2.02 TB/s memory bandwidth and 64 GB HBM3 capacity position this part for workloads that saturate memory, such as large language model training or scientific simulation. Without recorded scores, the practical advice is to rely on the compute and memory specifications rather than database rankings.

FAQ

Q: What architecture and chip does the H100 SXM5 use?

A: It uses the Hopper architecture with the GH100 chip, fabricated on TSMC's 5 nm process. The die measures 814 mm² and contains 80,000 million transistors.

Q: How much memory does it have and what type?

A: It has 64 GB of HBM3 memory on a 3072-bit bus, delivering 2.02 TB/s of bandwidth. The memory clock is 1313 MHz with a 5.3 Gbps effective data rate.

Q: What power supply is recommended?

A: The TDP is 700 W and the suggested PSU is 1100 W. Power is delivered through an 8-pin EPS connector, and the card uses an SXM Module slot width.

Q: Does it support DirectX, Vulkan, or display outputs?

A: No. The DirectX, OpenGL, and Vulkan API fields are all null, and the card has no display outputs. It is a compute-only accelerator.

Q: What is the FP16 and FP32 performance?

A: FP32 peak is 66.91 TFLOPS, and FP16 peak is 267.6 TFLOPS at a 4:1 ratio. It has 528 tensor cores to drive those workloads.

Q: When was it released and what is its production status?

A: It was released on 2023-03-20 and its production status is listed as Active. Its predecessor is Server Ada and its successor is Server Blackwell.

Memory Subsystem

The memory configuration is one of the defining characteristics of the H100 SXM5. It carries 64 GB of HBM3 on a 3072-bit bus, with bandwidth rated at 2.02 TB/s. The effective memory clock is 5.3 Gbps, with a base memory clock of 1313 MHz. These numbers place it firmly in the territory of high-bandwidth server accelerators — the 3072-bit bus width is several times wider than what consumer GPUs use, and the 2.02 TB/s bandwidth is the kind of figure that matters when loading large models or datasets into VRAM.

For high-resolution or large-batch workloads, the memory subsystem determines how quickly data can be fed to the compute units. The 64 GB capacity is substantial — enough to hold large model weights or high-resolution simulation data without spilling to host memory. The HBM3 type and the 5.3 Gbps effective rate indicate a design optimized for sustained throughput rather than low latency. The bus width of 3072 bit is the key enabler: at this width, even moderate clock speeds produce massive aggregate bandwidth.

The practical implication is that memory-bound workloads — training runs, inference batches, scientific computing — will scale well on this part as long as the software can utilize the full 2.02 TB/s. The 64 GB capacity also reduces the need for memory pooling or distributed sharding in smaller clusters. For users considering this for high-resolution rendering or simulation, the bandwidth is the number to watch; the 3072-bit bus is the mechanism that delivers it.

Power and Cooling

The H100 SXM5 is a 700 W part. That TDP requires serious power delivery infrastructure: the suggested PSU is 1100 W, and the module uses an 8-pin EPS connector rather than the standard PCIe power connectors found on consumer cards. The slot width is listed as SXM Module, meaning this is not a card that fits into a standard PCIe slot — it mounts directly to a server board designed for SXM modules. Cooling is likewise a server-grade concern; a 700 W module in an SXM form factor typically relies on chassis-level cooling or liquid solutions, though the fact pack does not specify the cooling solution.

The 8-pin EPS connector is worth noting — EPS is a CPU power standard, not a GPU one, which signals that the H100 SXM5 draws power through the server board's CPU power rails rather than a dedicated GPU power path. The 1100 W PSU recommendation covers the module's 700 W draw plus headroom for the host system. Builders integrating this part into a server should verify their chassis power distribution and cooling capacity before installation; the data sheet's 700 W TDP is the number to plan around, and the 1100 W PSU suggestion is the safe minimum for the full node.

The absence of dimensions in the fact pack (length, height, width all null) reinforces that this is a board-integrated module, not a standalone card. Physical clearance and airflow are dictated by the server chassis design, not by the card itself. For anyone evaluating this part, the power and cooling requirements are as important as the compute specifications — a 700 W module with an 8-pin EPS connection and a 1100 W PSU recommendation is not a drop-in upgrade for a standard workstation.