AMD Instinct MI300A vs NVIDIA H100 PCIe 96 GB Comparison

Head-to-Head Benchmarks

The recorded data shows no direct head-to-head benchmark results between the AMD Instinct MI300A and the NVIDIA H100 PCIe 96 GB. Both accelerators hold a 50th percentile ranking against all GPUs in the database, with an average benchmark score of 0 for each. The absence of measured wins for either part means the comparison must rely entirely on architectural specifications and derived performance metrics rather than empirical test results.

The closest point of comparison in raw compute throughput is FP32 performance. The NVIDIA H100 PCIe 96 GB delivers 62.08 TFLOPS, while the AMD Instinct MI300A produces 61.29 TFLOPS. The difference is 0.79 TFLOPS, placing the H100 approximately 1.3% ahead in single-precision floating-point work. This is a narrow margin, effectively a statistical tie in theoretical peak performance, though the H100 edges ahead in the raw specification.

Texture processing tells a different story. The AMD Instinct MI300A reaches 1,915.2 GTexel/s, compared to 969.9 GTexel/s for the NVIDIA H100 PCIe 96 GB. That represents a 97.5% advantage for the MI300A, nearly double the texturing throughput. The MI300A also carries 912 texture mapping units against 528 on the H100, and the higher boost clock of 2100 MHz versus 1837 MHz contributes to this substantial lead.

Memory bandwidth heavily favors the AMD part. The MI300A provides 5.32 TB/s of bandwidth across an 8192-bit bus, while the H100 PCIe 96 GB delivers 3.36 TB/s over a 5120-bit bus. This is a 58.3% bandwidth advantage for the MI300A. The H100 compensates partially with a larger memory pool in a different configuration, but the raw bandwidth differential is one of the largest gaps between the two accelerators.

Pixel processing is effectively absent on the AMD side. The MI300A records 0 MPixel/s with zero ROPs, while the H100 manages 44.09 GPixel/s from its 24 ROPs. This makes the H100 the only one of the two capable of any rasterization-style output, a meaningful distinction for any workload that requires pixel generation.

FP16 throughput is where the NVIDIA part demonstrates its clearest measured superiority. The H100 PCIe 96 GB lists 248.3 TFLOPS (4:1), a figure the AMD MI300A does not specify in the database. For mixed-precision training and inference workloads that rely on FP16 tensor operations, the H100 has a documented advantage, while the MI300A data is silent on this metric.

Where Each One Wins

The AMD Instinct MI300A wins decisively in memory bandwidth, texture throughput, and memory capacity. Its 5.32 TB/s bandwidth and 128 GB of HBM3 memory make it the stronger choice for workloads that stream large datasets through the accelerator, such as large language model inference with substantial batch sizes, scientific simulations with dense memory access patterns, and graph analytics that require rapid traversal of massive adjacency structures. The 1,915.2 GTexel/s texture rate and 912 TMUs suggest the MI300A is also better suited to compute tasks that exhibit texture-like access patterns, including certain convolution operations and image processing pipelines.

The NVIDIA H100 PCIe 96 GB wins in FP32 peak throughput, FP16 throughput, and pixel processing. Its 62.08 TFLOPS FP32 rating edges past the MI300A, making it marginally better for workloads that are heavily dependent on single-precision compute. The 248.3 TFLOPS FP16 (4:1) figure gives it a documented advantage in mixed-precision machine learning training, where FP16 tensor core operations dominate. The 44.09 GPixel/s pixel rate and 24 ROPs mean the H100 is the only one of the two with any rasterization capability, relevant for rendering or visualization tasks that require pixel output.

The H100 also wins on physical integration flexibility. It uses a dual-slot PCIe form factor with an 8-pin EPS power connector, allowing installation in standard server chassis without custom power delivery. The MI300A is an OAM module with no power connectors, requiring a baseboard designed specifically for OAM accelerators. The H100's 268 mm length and 111 mm height fit conventional server layouts, whereas the MI300A's dimensions are not recorded in the database.

Architecture Differences

The two accelerators come from different architectural families. The AMD Instinct MI300A uses the CDNA 3.0 architecture on the Aqua Vanjaram chip, part of the Instinct (MIx) generation. The NVIDIA H100 PCIe 96 GB uses the Hopper architecture on the GH100 chip, part of the Server Hopper (Hxx) generation. Both are manufactured at TSMC on a 5 nm process node, but the similarities end there.

Transistor counts differ substantially. The MI300A packs 153,000 million transistors on a 1017 mm² die, yielding a transistor density of 150.4M per mm². The H100 contains 80,000 million transistors on an 814 mm² die, with a density of 98.3M per mm². The MI300A therefore has 91.25% more transistors in 24.9% more die area, reflecting a significantly denser design.

Clock behavior diverges sharply. The MI300A runs at a 1000 MHz base clock and boosts to 2100 MHz, a 110% boost range. The H100 starts at 1665 MHz base and boosts to 1837 MHz, only a 10.3% boost window. The H100's higher base clock means it sustains more performance under continuous load without relying on boost headroom, while the MI300A's aggressive boost curve suggests it can reach higher peak frequencies when thermal and power conditions allow.

Memory architecture differs in both capacity and bus width. The MI300A uses 128 GB of HBM3 across an 8192-bit bus, while the H100 uses 96 GB of HBM3 across a 5120-bit bus. The MI300A's memory clock is 1300 MHz (5.2 Gbps effective), and the H100's is 1313 MHz (5.3 Gbps effective). Despite the H100's marginally higher memory clock, the MI300A's wider bus produces the overall bandwidth advantage.

Shader and fixed-function hardware counts do not correlate with the transistor difference. The MI300A has 14,592 shading units and 912 TMUs but zero ROPs. The H100 has 16,896 shading units, 528 TMUs, and 24 ROPs. The H100 actually has 15.8% more shading units despite having fewer total transistors, while the MI300A has 72.7% more TMUs. The H100 also carries 528 tensor cores, a feature class the MI300A does not list.

Power and cooling requirements are close but not identical. The MI300A draws 750 W with a suggested PSU of 1150 W, while the H100 draws 700 W with a suggested PSU of 1100 W. The MI300A consumes 7.1% more power, consistent with its larger transistor count and higher bandwidth. Neither card has display outputs, and both use a PCIe 5.0 x16 bus interface.

Release timing also differs. The H100 PCIe 96 GB launched on 2023-03-20, and the MI300A launched on 2023-12-05. The H100 precedes the MI300A by roughly nine months. The H100 lists a predecessor (Server Ada) and successor (Server Blackwell), while the MI300A lists only a predecessor (Radeon Instinct).

FAQ

Q: Which accelerator has higher memory bandwidth?

A: The AMD Instinct MI300A, with 5.32 TB/s across an 8192-bit HBM3 bus. The NVIDIA H100 PCIe 96 GB provides 3.36 TB/s over a 5120-bit bus.

Q: How do the two compare in FP32 compute?

A: The NVIDIA H100 PCIe 96 GB is slightly ahead at 62.08 TFLOPS versus 61.29 TFLOPS for the AMD Instinct MI300A, a margin of about 1.3%.

Q: Which card can perform rasterization?

A: Only the NVIDIA H100 PCIe 96 GB, which has 24 ROPs and a 44.09 GPixel/s pixel rate. The AMD Instinct MI300A has zero ROPs and records 0 MPixel/s.

Q: What are the form factor differences?

A: The AMD Instinct MI300A is an OAM module with no power connectors, requiring a dedicated OAM baseboard. The NVIDIA H100 PCIe 96 GB is a dual-slot PCIe card with an 8-pin EPS connector, measuring 268 mm in length and 111 mm in height.

Q: Does either card support FP16 operations?

A: The NVIDIA H100 PCIe 96 GB lists 248.3 TFLOPS FP16 (4:1). The AMD Instinct MI300A does not have an FP16 figure recorded in the database.

Q: Which accelerator has more transistors?

A: The AMD Instinct MI300A, with 153,000 million transistors on a 1017 mm² die, compared to 80,000 million transistors on an 814 mm² die for the NVIDIA H100 PCIe 96 GB.

Specification Differences

| Specification | AMD Instinct MI300A | NVIDIA H100 PCIe 96 GB |

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

| Architecture | CDNA 3.0 | Hopper |

| Chip | Aqua Vanjaram | GH100 |

| Generation | Instinct (MIx) | Server Hopper (Hxx) |

| Transistors | 153,000 million | 80,000 million |

| Die Size | 1017 mm² | 814 mm² |

| Transistor Density | 150.4M / mm² | 98.3M / mm² |

| Base Clock | 1000 MHz | 1665 MHz |

| Boost Clock | 2100 MHz | 1837 MHz |

| Memory Clock | 1300 MHz, 5.2 Gbps effective | 1313 MHz, 5.3 Gbps effective |

| Memory Size | 128 GB | 96 GB |

| Memory Type | HBM3 | HBM3 |

| Memory Bus Width | 8192 bit | 5120 bit |

| Memory Bandwidth | 5.32 TB/s | 3.36 TB/s |

| Shading Units | 14,592 | 16,896 |

| TMUs | 912 | 528 |

| ROPs | 0 | 24 |

| Tensor Cores | Not listed | 528 |

| Pixel Rate | 0 MPixel/s | 44.09 GPixel/s |

| Texture Rate | 1,915.2 GTexel/s | 969.9 GTexel/s |

| FP32 | 61.29 TFLOPS | 62.08 TFLOPS |

| FP16 | Not listed | 248.3 TFLOPS (4:1) |

| TDP | 750 W | 700 W |

| Slot Width | OAM Module | Dual-slot |

| Power Connectors | None | 8-pin EPS |

| Suggested PSU | 1150 W | 1100 W |

| Dimensions | Not recorded | 268 mm length, 111 mm height |

| Release Date | 2023-12-05 | 2023-03-20 |

| Production Status | Not recorded | Active |

| Predecessor | Radeon Instinct | Server Ada |

| Successor | Not recorded | Server Blackwell |

Shared specifications include the 5 nm TSMC process node, PCIe 5.0 x16 bus interface, no display outputs, and no recorded launch MSRP.

The Verdict

The data defines two distinct profiles. The AMD Instinct MI300A is the memory-centric accelerator: 5.32 TB/s bandwidth, 128 GB capacity, and a 1,915.2 GTexel/s texture rate that more than doubles the H100's 969.9 GTexel/s. Its 750 W power draw and OAM form factor indicate a design aimed at dense compute nodes where memory bandwidth is the binding constraint.

The NVIDIA H100 PCIe 96 GB is the compute-centric accelerator with broader documented capabilities. It leads in FP32 at 62.08 TFLOPS, offers FP16 at 248.3 TFLOPS (4:1), and is the only one of the two with pixel rendering capability at 44.09 GPixel/s. Its 700 W TDP and dual-slot PCIe form factor with an 8-pin EPS connector make it the more conventional integration choice for standard servers.

For workloads that stress memory bandwidth and texture-like access patterns, the MI300A's 58.3% bandwidth advantage and 97.5% texture rate lead point clearly to AMD. For mixed-precision machine learning, single-precision compute, and any task requiring pixel output, the H100's documented FP16 and FP32 figures plus its ROP support make it the better fit.

The MI300A's 153,000 million transistors and 1017 mm² die represent a more ambitious physical design, but the H100 achieves comparable FP32 performance with 80,000 million transistors and 814 mm². The H100's higher base clock of 1665 MHz versus 1000 MHz explains how it reaches near-parity FP32 with fewer resources. The production status of the H100 is recorded as Active, while the MI300A's status is not recorded, which may indicate differences in availability.

The absence of direct benchmark scores and the 50th percentile ranking for both parts mean the selection depends on which architectural strengths match the target workload. The MI300A suits memory-bound large-scale compute. The H100 suits mixed-precision AI training and any workflow requiring rasterization or a standard PCIe installation path.