AMD Instinct MI355X vs NVIDIA H800 SXM5 Comparison

FAQ

Q: What is the process node difference between the AMD Instinct MI355X and the NVIDIA H800 SXM5?

A: The AMD Instinct MI355X is built on a 3 nm process at TSMC, while the NVIDIA H800 SXM5 uses a 5 nm process, also at TSMC.

Q: How much memory does each accelerator offer?

A: The AMD Instinct MI355X has 288 GB of HBM3e memory, whereas the NVIDIA H800 SXM5 has 80 GB of HBM3 memory.

Q: What is the memory bandwidth of each product?

A: The AMD Instinct MI355X delivers 8.19 TB/s of bandwidth, compared to 3.36 TB/s for the NVIDIA H800 SXM5.

Q: Which accelerator has a higher FP32 (single-precision) throughput?

A: The AMD Instinct MI355X reaches 78.64 TFLOPS FP32, while the NVIDIA H800 SXM5 reaches 59.30 TFLOPS FP32.

Q: What is the thermal design power (TDP) for each module?

A: The AMD Instinct MI355X has a TDP of 1400 W, and the NVIDIA H800 SXM5 has a TDP of 700 W.

Q: What are the release dates for the two accelerators?

A: The AMD Instinct MI355X was released on June 11, 2025, and the NVIDIA H800 SXM5 was released on March 20, 2023.

Architecture Differences

The AMD Instinct MI355X is built on the CDNA 4.0 architecture, a compute-focused design from AMD. It uses the MI350 256CU chip, which contains 185,000 million transistors on a 2380 mm² die. The manufacturing process is 3 nm at TSMC. The NVIDIA H800 SXM5 is built on the Hopper architecture, using the GH100 chip. This chip contains 80,000 million transistors on an 814 mm² die, produced on a 5 nm process at TSMC. The transistor density figures tell an interesting story: the NVIDIA chip packs 98.3M transistors per mm², while the AMD chip has 77.7M per mm². Even though the AMD chip is much larger, the NVIDIA design achieves higher density on a mature process.

The memory subsystems differ significantly. The AMD Instinct MI355X uses 288 GB of HBM3e across an 8192-bit bus, yielding 8.19 TB/s of bandwidth. The NVIDIA H800 SXM5 has 80 GB of HBM3 on a 5120-bit bus, providing 3.36 TB/s. The AMD part also runs its memory at 2000 MHz (8 Gbps effective), while the NVIDIA memory runs at 1313 MHz (5.3 Gbps effective). These are major differences in capacity and bandwidth, which directly affect large model workloads.

The compute configurations are also distinct. The AMD Instinct MI355X has 16384 shading units and 1024 TMUs, with no ROPs listed. The NVIDIA H800 SXM5 has 16896 shading units, 528 TMUs, 24 ROPs, and 528 tensor cores. The AMD part reports a pixel rate of 0 MPixel/s and a texture rate of 2457.6 GTexel/s. The NVIDIA part has a pixel rate of 42.12 GPixel/s and a texture rate of 926.6 GTexel/s. The AMD design is clearly optimized for raw compute throughput rather than traditional graphics rasterization.

The AMD Instinct MI355X has no display outputs and no API support for DirectX, OpenGL, or Vulkan. The NVIDIA H800 SXM5 also has no display outputs, but its API fields are null, meaning no data is recorded. Both are server modules, the former an OAM Module and the latter an SXM Module. The AMD part uses no power connectors, while the NVIDIA part uses an 8-pin EPS connector. The suggested PSU is 1800 W for AMD and 1100 W for NVIDIA. The AMD module measures 102 mm in length and 165 mm in width, while the NVIDIA dimensions are not recorded in the database.

Head-to-Head Benchmarks

The recorded data shows no direct benchmark scores for either accelerator, since both have an average benchmark score of 0 and no entries in their head-to-head benchmark lists. However, the specification data provides a basis for comparison, and the differences are substantial.

The most obvious gap is memory capacity. The AMD Instinct MI355X offers 288 GB, which is 3.6 times the capacity of the NVIDIA H800 SXM5 at 80 GB. This is a decisive advantage for workloads that require large model weights or massive datasets to reside on the accelerator itself. Memory bandwidth follows a similar pattern: the AMD part delivers 8.19 TB/s, which is 2.4 times the bandwidth of the NVIDIA part at 3.36 TB/s. The AMD part also uses a wider bus (8192 bit versus 5120 bit) and faster memory (HBM3e versus HBM3).

FP32 compute throughput favors AMD. The MI355X reaches 78.64 TFLOPS, while the H800 SXM5 reaches 59.30 TFLOPS. That is a 32.6% advantage for AMD in single-precision compute. Texture rate also favors AMD: 2457.6 GTexel/s versus 926.6 GTexel/s, a 2.65 times difference. However, the NVIDIA part has a non-zero pixel rate (42.12 GPixel/s) while the AMD part reports 0 MPixel/s, indicating that the AMD design has no raster output stage.

The FP16 comparison is more nuanced. The AMD Instinct MI355X reports FP16 at 78.64 TFLOPS with a 1:1 ratio, meaning it does not double throughput for half-precision. The NVIDIA H800 SXM5 reports FP16 at 237.2 TFLOPS with a 4:1 ratio. This means the NVIDIA part achieves 3 times the FP16 throughput of the AMD part when using its specialized ratio. This is a significant advantage for training or inference workloads that rely on mixed-precision arithmetic.

Clock speeds differ as well. The AMD part has a base clock of 1000 MHz and a boost clock of 2400 MHz. The NVIDIA part has a base clock of 1095 MHz and a boost clock of 1755 MHz. The AMD part boosts much higher, but the NVIDIA part has a higher base clock. This contributes to the compute differences noted above.

The transistor counts and die sizes are also worth comparing. The AMD chip has 185,000 million transistors, which is 2.3 times the transistor count of the NVIDIA chip at 80,000 million. The AMD die is 2380 mm², which is 2.9 times the size of the NVIDIA die at 814 mm². Despite the larger die, the AMD part achieves lower transistor density (77.7M / mm² versus 98.3M / mm²), reflecting the different design priorities and process nodes.

Specification Differences

The following fields differ between the AMD Instinct MI355X and the NVIDIA H800 SXM5:

• Architecture: CDNA 4.0 versus Hopper.
• Process node: 3 nm versus 5 nm.
• Transistors: 185,000 million versus 80,000 million.
• Die size: 2380 mm² versus 814 mm².
• Transistor density: 77.7M / mm² versus 98.3M / mm².
• Base clock: 1000 MHz versus 1095 MHz.
• Boost clock: 2400 MHz versus 1755 MHz.
• Memory clock: 2000 MHz (8 Gbps effective) versus 1313 MHz (5.3 Gbps effective).
• Memory size: 288 GB versus 80 GB.
• Memory type: HBM3e versus HBM3.
• Memory bus width: 8192 bit versus 5120 bit.
• Memory bandwidth: 8.19 TB/s versus 3.36 TB/s.
• Shading units: 16384 versus 16896.
• TMUs: 1024 versus 528.
• ROPs: 0 versus 24.
• Tensor cores: null versus 528.
• Pixel rate: 0 MPixel/s versus 42.12 GPixel/s.
• Texture rate: 2457.6 GTexel/s versus 926.6 GTexel/s.
• FP32: 78.64 TFLOPS versus 59.30 TFLOPS.
• FP16: 78.64 TFLOPS (1:1) versus 237.2 TFLOPS (4:1).
• TDP: 1400 W versus 700 W.
• Slot width: OAM Module versus SXM Module.
• Power connectors: None versus 8-pin EPS.
• Suggested PSU: 1800 W versus 1100 W.
• Dimensions: 102 mm length, 165 mm width versus not recorded.
• Release date: June 11, 2025 versus March 20, 2023.
• Predecessor: Radeon Instinct versus Server Ada.
• Successor: null versus Server Blackwell.
• Production status: null versus Active.

The shading unit count is close, with NVIDIA having 512 more, but the AMD part compensates with more TMUs (1024 versus 528) and a much higher boost clock. The AMD part also has no tensor cores listed, while NVIDIA lists 528. This suggests different compute strategies: AMD relies on general-purpose shader units, while NVIDIA has dedicated tensor hardware.

The Verdict

The data shows two accelerators with different strengths. The AMD Instinct MI355X leads in memory capacity (288 GB versus 80 GB), memory bandwidth (8.19 TB/s versus 3.36 TB/s), FP32 compute (78.64 TFLOPS versus 59.30 TFLOPS), and texture rate (2457.6 GTexel/s versus 926.6 GTexel/s). It also uses a newer process node (3 nm versus 5 nm) and a larger die (2380 mm² versus 814 mm²). The NVIDIA H800 SXM5 leads in FP16 throughput (237.2 TFLOPS versus 78.64 TFLOPS), has tensor cores (528 versus none), and operates at a lower TDP (700 W versus 1400 W). The NVIDIA part also has a higher base clock (1095 MHz versus 1000 MHz) and a higher transistor density (98.3M / mm² versus 77.7M / mm²).

The AMD accelerator is the choice for workloads that need maximum memory capacity and bandwidth, such as large-scale inference or training with massive model footprints. Its 288 GB of HBM3e and 8.19 TB/s bandwidth provide a clear advantage for holding large datasets or model parameters entirely on the accelerator. The NVIDIA accelerator, with its 3 times higher FP16 throughput and dedicated tensor cores, is better suited for mixed-precision training and inference pipelines that rely on tensor operations and half-precision arithmetic.

The power requirements are also a factor. The AMD part requires 1400 W and a suggested PSU of 1800 W, while the NVIDIA part requires 700 W and a suggested PSU of 1100 W. Systems designed for lower power envelopes would favor the NVIDIA part. However, the AMD part delivers 2.4 times the memory bandwidth and 2.5 times the FP32 throughput per watt, based on the recorded figures. The NVIDIA part delivers 3 times the FP16 throughput per watt, at 237.2 TFLOPS versus 78.64 TFLOPS.

The release dates indicate the AMD part is newer by over two years, which explains its use of HBM3e and a 3 nm process. The NVIDIA part, released in March 2023, uses HBM3 and a 5 nm process. The production status for the NVIDIA part is listed as Active, while the AMD part has no recorded production status. The NVIDIA part also has a named successor (Server Blackwell), while the AMD part does not.

Both parts are server modules with no display outputs and no graphics API support. The AMD part is an OAM Module, and the NVIDIA part is an SXM Module. Neither has a launch MSRP recorded in the database. The AMD part has no tensor cores listed, and the NVIDIA part has 528, which is the most significant architectural distinction for AI workloads. The AMD part compensates with more shading units and TMUs, but the absence of tensor cores means its FP16 performance is limited to a 1:1 ratio.

In summary, the AMD Instinct MI355X is the memory-capacity leader with higher FP32 and texture throughput. The NVIDIA H800 SXM5 is the mixed-precision leader with tensor cores and higher FP16 throughput. The choice depends on whether the workload prioritizes memory size and bandwidth or tensor-based half-precision compute, and whether the system can accommodate the higher power draw of the AMD module.