AMD Instinct MI455X vs NVIDIA H100 CNX Comparison

Head-to-Head Benchmarks

The recorded database contains no benchmark scores for either the AMD Instinct MI455X or the NVIDIA H100 CNX. Both entries show an average benchmark score of zero and an empty benchmark array. The percentile versus all GPUs is identical for both at 50. Consequently, no direct head-to-head performance delta can be computed from the measurements. The absence of empirical data means the database cannot establish a winner in any workload category.

The only quantifiable performance indicators come from the theoretical specification sheet. In raw FP32 compute, the AMD Instinct MI455X delivers 157.3 TFLOPS, while the NVIDIA H100 CNX delivers 53.84 TFLOPS. That places the AMD part at approximately 2.9 times the FP32 throughput of the NVIDIA accelerator. For FP16, the situation inverts on paper: the MI455X lists 157.3 TFLOPS (1:1 ratio), while the H100 CNX lists 215.4 TFLOPS (4:1 ratio). The NVIDIA part holds a 37% advantage in that metric.

Texture rate also favors AMD, with the MI455X recording 2,457.6 GTexel/s versus 841.3 GTexel/s for the H100 CNX, a factor of 2.9. Pixel rate is a different story. The MI455X shows 0 MPixel/s, while the H100 CNX shows 44.28 GPixel/s. The AMD accelerator has no raster output pipeline, which explains the zero pixel rate. The NVIDIA part has 24 ROPs.

Memory bandwidth heavily favors AMD. The MI455X lists 23.3 TB/s, the H100 CNX lists 2.04 TB/s. That is an 11.4 times advantage for the AMD part. Memory capacity also differs drastically: 432 GB versus 80 GB, a 5.4 times difference. These gaps in theoretical throughput and capacity are the only measurable differences available in the database, as no application-level benchmark results exist for either card.

Where Each One Wins

Based on the recorded specifications, the AMD Instinct MI455X wins in scenarios that depend on raw FP32 compute, texture throughput, and memory bandwidth. Workloads such as dense linear algebra, scientific simulation, and data-parallel compute that do not rely heavily on FP16 tensor operations would favor the MI455X on paper. The 432 GB HBM4 memory pool and 23.3 TB/s bandwidth suggest a design aimed at massive in-memory datasets, possibly for large language model inference or high-fidelity simulations that require keeping entire models or datasets resident on the accelerator.

The NVIDIA H100 CNX wins in theoretical FP16 throughput, delivering 215.4 TFLOPS versus 157.3 TFLOPS for the MI455X. This advantage comes from the 4:1 FP16 ratio, meaning the H100 CNX can double-pump its FP16 execution relative to FP32. The 456 tensor cores on the H100 CNX also provide a hardware path for mixed-precision neural network training and inference. The H100 CNX additionally has a functional pixel rate of 44.28 GPixel/s, which the MI455X lacks entirely, so any workload requiring rasterization output would go to the NVIDIA part. The H100 CNX also runs at a far lower TDP of 350 W versus 2300 W for the MI455X, making it the only one of the two that fits in a standard dual-slot chassis with an 8-pin EPS connector.

The database shows no benchmark wins for either accelerator, so the use-case split rests entirely on architectural capabilities rather than measured performance.

Architecture Differences

The AMD Instinct MI455X uses the MI450 256CU chip built on CDNA 5.0 architecture. The NVIDIA H100 CNX uses the GH100 chip built on Hopper architecture. These are fundamentally different design philosophies. AMD employs a 2 nm process node from TSMC, while NVIDIA uses a 5 nm process node from the same foundry. The transistor counts diverge sharply: 320,000 million transistors on the MI455X versus 80,000 million on the H100 CNX. Die size also differs, with the MI455X at 2990 mm² and the H100 CNX at 814 mm². Transistor density is slightly higher on the AMD part at 107.0M per mm² versus 98.3M per mm² on the NVIDIA part.

The MI455X has 32,768 shading units and 1,024 texture mapping units, with zero ROPs. The H100 CNX has 14,592 shading units, 456 TMUs, and 24 ROPs. The NVIDIA part includes 456 tensor cores, while the MI455X lists no tensor cores. The AMD architecture does not expose a separate tensor core count in the database, relying instead on its unified compute units delivering FP16 at a 1:1 ratio with FP32. The H100 CNX achieves its FP16 advantage through the 4:1 ratio and dedicated tensor hardware.

Memory architecture differs at every level. The MI455X uses HBM4 with a 24576-bit bus and 23.3 TB/s bandwidth. The H100 CNX uses HBM2e with a 5120-bit bus and 2.04 TB/s bandwidth. The AMD part has 432 GB of memory, the NVIDIA part has 80 GB. Clock speeds also vary: the MI455X has a 1000 MHz base and 2400 MHz boost, while the H100 CNX has a 690 MHz base and 1845 MHz boost. The boost clock on the MI455X is 30% higher than the NVIDIA part.

The MI455X is an EAM Module with no power connectors and no display outputs. The H100 CNX is a dual-slot card measuring 267 mm in length and 111 mm in height, with an 8-pin EPS power connector and no display outputs. The MI455X lists no API support for DirectX, OpenGL, or Vulkan, all marked N/A. The H100 CNX lists no API data at all.

Specification Differences

The two accelerators differ in nearly every measurable specification. Process node: 2 nm for the MI455X, 5 nm for the H100 CNX. Transistors: 320,000 million versus 80,000 million. Die size: 2990 mm² versus 814 mm². Base clock: 1000 MHz versus 690 MHz. Boost clock: 2400 MHz versus 1845 MHz. Memory clock: 1900 MHz (7.6 Gbps effective) versus 1593 MHz (3.2 Gbps effective). Memory size: 432 GB versus 80 GB. Memory type: HBM4 versus HBM2e. Bus width: 24576 bit versus 5120 bit. Bandwidth: 23.3 TB/s versus 2.04 TB/s.

Shading units: 32,768 versus 14,592. TMUs: 1,024 versus 456. ROPs: 0 versus 24. Tensor cores: none listed versus 456. Pixel rate: 0 MPixel/s versus 44.28 GPixel/s. Texture rate: 2,457.6 GTexel/s versus 841.3 GTexel/s. FP32: 157.3 TFLOPS versus 53.84 TFLOPS. FP16: 157.3 TFLOPS (1:1) versus 215.4 TFLOPS (4:1). TDP: 2300 W versus 350 W. Slot width: EAM Module versus dual-slot. Power connectors: none versus 8-pin EPS. Suggested PSU: 2700 W versus 750 W. Bus interface: PCIe 6.0 x16 versus PCIe 5.0 x16.

Release dates also differ: the MI455X is dated 2026-07-22, while the H100 CNX is dated 2023-03-20. The H100 CNX has an active production status, while the MI455X has no production status listed. The H100 CNX has a predecessor (Server Ada) and successor (Server Blackwell) listed, while the MI455X lists Radeon Instinct as its predecessor and no successor. Neither part has a launch MSRP in the database.

FAQ

Q: Which accelerator has higher FP32 compute?

A: The AMD Instinct MI455X delivers 157.3 TFLOPS FP32, which is 2.9 times the 53.84 TFLOPS of the NVIDIA H100 CNX.

Q: Does the NVIDIA H100 CNX support tensor operations?

A: Yes, the H100 CNX lists 456 tensor cores. The AMD MI455X does not list any tensor cores in the database.

Q: What is the memory bandwidth difference?

A: The MI455X has 23.3 TB/s bandwidth from HBM4 on a 24576-bit bus, while the H100 CNX has 2.04 TB/s from HBM2e on a 5120-bit bus. The AMD part has 11.4 times the bandwidth.

Q: Which card uses more power?

A: The MI455X has a TDP of 2300 W and suggests a 2700 W PSU. The H100 CNX has a TDP of 350 W and suggests a 750 W PSU.

Q: Are there any benchmark results available for these two GPUs?

A: No. The database shows zero benchmark scores and zero average benchmark scores for both accelerators, with both at the 50th percentile versus all GPUs.

Q: Which accelerator has more memory capacity?

A: The MI455X has 432 GB of HBM4, while the H100 CNX has 80 GB of HBM2e. The AMD part provides 5.4 times the capacity.

Q: What process nodes do these chips use?

A: The MI455X uses a 2 nm TSMC process. The H100 CNX uses a 5 nm TSMC process. Both are fabricated by TSMC.