GPU Comparison

The AMD Instinct MI300X and NVIDIA PG506-232 are both professional compute accelerators, but they serve entirely different performance tiers. The benchmark data shows a decisive overall victory for the AMD part, yet the PG506-232 remains relevant in specific legacy or power-constrained roles. This analysis breaks down the measured performance, architectural philosophies, and practical implications of each card.

Head-to-Head Benchmarks

The single available benchmark result, Geekbench OpenCL, provides a clear picture of the performance gap. The AMD Instinct MI300X scores 317,994 points, while the NVIDIA PG506-232 scores 225,124 points. This translates to a 41.3% advantage for the MI300X, making it the outright winner of the head-to-head comparison. The MI300X also claims the sole win in the wins tally, 1 to 0.

Looking at the broader competitive landscape reinforces this dominance. The MI300X sits at the 100th percentile of all GPUs, meaning it outperforms every other GPU in the database. Its nearest rival, the NVIDIA H200 NVL, scores 334,891 points, which is 5% higher than the MI300X. However, the MI300X is 7.5% ahead of the NVIDIA L40S (295,763 points) and 10.7% ahead of the NVIDIA RTX 6000 Ada Generation (287,237 points). Even the mighty NVIDIA B200 (345,482 points) is only 8% faster than the MI300X, which shows how close the AMD part is to the absolute top of the performance stack.

The PG506-232, by contrast, occupies the 99th percentile. Its closest rival is the NVIDIA L20, which scores 251,147 points and is 10.4% faster. The PG506-232 does beat the AMD Radeon PRO W7900D (219,827 points) by 2.4%, the NVIDIA A100 PCIe 80 GB (207,124 points) by 8.7%, and the NVIDIA RTX 6000D (195,964 points) by 14.9%. While the PG506-232 is a strong performer in its own right, the 41.3% gap to the MI300X is a chasm that no amount of architectural efficiency can bridge in raw compute throughput.

The Verdict

The data is unequivocal: the AMD Instinct MI300X is the superior compute accelerator. It delivers a 41.3% higher OpenCL score than the PG506-232, placing it in the top percentile of all GPUs. For any workload where raw compute throughput is the primary bottleneck, the MI300X is the only rational choice. Its 317,994-point score is not just a win; it is a categorical statement of performance class.

The NVIDIA PG506-232, however, is not without merit. It is an end-of-life product, but its 225,124-point score still places it in the 99th percentile of all GPUs. It outperforms several current workstation cards, including the RTX 6000D by 14.9%. If a system requires a dual-slot, 165 W card with an 8-pin EPS connector and a 450 W suggested PSU, the PG506-232 is a viable option. But the MI300X, with its 750 W TDP and OAM module form factor, is a completely different class of hardware designed for maximum throughput, not ease of integration.

The verdict is simple: pick the MI300X for performance, pick the PG506-232 for a specific, power-efficient, legacy slot. There is no scenario in the data where the PG506-232 wins on speed.

Where Each One Wins

The MI300X wins in every measured compute scenario. Its 81.72 TFLOPS FP32 performance dwarfs the PG506-232's 10.32 TFLOPS. This is an 8x difference in raw floating-point throughput. The MI300X also has a massive memory advantage with 192 GB of HBM3 at 5.32 TB/s bandwidth, compared to the PG506-232's 24 GB of HBM2 at 933.1 GB/s. The 5.32 TB/s bandwidth is over 5.7 times faster than the PG506-232's 933.1 GB/s. This makes the MI300X ideal for large language models, scientific simulations, or any workload that requires holding and rapidly processing huge datasets.

The PG506-232 wins in power efficiency and physical integration. Its 165 W TDP is a fraction of the MI300X's 750 W. It is a dual-slot card, 267 mm long and 112 mm tall, that fits into standard PCIe 4.0 x16 slots with an 8-pin EPS power connector. The MI300X, in contrast, is an OAM module with no display outputs and no power connectors, requiring a specific server chassis. The PG506-232's 24 GB of HBM2 is also more than sufficient for many inference tasks or smaller training jobs, making it a practical choice for a workstation that cannot accommodate the MI300X's infrastructure requirements.

FAQ

Q: Which GPU has the higher Geekbench OpenCL score?

A: The AMD Instinct MI300X scores 317,994 points, which is 41.3% higher than the NVIDIA PG506-232's score of 225,124 points.

Q: How does the MI300X compare to the NVIDIA H200 NVL?

A: The H200 NVL scores 334,891 points, which is 5% higher than the MI300X's 317,994 points. The MI300X is the second-place performer among its nearest rivals.

Q: Is the PG506-232 faster than the NVIDIA A100 PCIe 80 GB?

A: Yes. The PG506-232 scores 225,124 points, which is 8.7% higher than the A100 PCIe 80 GB's 207,124 points.

Q: What are the memory capacities of these two cards?

A: The MI300X has 192 GB of HBM3 memory with a 5.32 TB/s bandwidth. The PG506-232 has 24 GB of HBM2 memory with a 933.1 GB/s bandwidth.

Q: What is the power consumption difference?

A: The MI300X has a 750 W TDP and requires a suggested 1150 W PSU. The PG506-232 has a 165 W TDP and requires a suggested 450 W PSU.

Q: Are these cards similar in physical size?

A: No. The PG506-232 is a dual-slot card measuring 267 mm in length and 112 mm in height. The MI300X is an OAM module with no specified dimensions, requiring a different mounting system.

Architecture Differences

The two GPUs come from different architectural generations and design philosophies. The AMD Instinct MI300X is built on the CDNA 3.0 architecture, using the Aqua Vanjaram chip, and is fabricated on a 5 nm process at TSMC. It packs 153,000 million transistors onto a 1017 mm² die, achieving a transistor density of 150.4M / mm². The NVIDIA PG506-232 is based on the older Ampere architecture, using the GA100 chip, and is fabricated on a 7 nm process at TSMC. It has 54,200 million transistors on an 826 mm² die, for a density of 65.6M / mm². This means the MI300X has nearly three times the transistor count and more than double the transistor density.

The memory subsystems are also fundamentally different. The MI300X uses 192 GB of HBM3 on an 8192-bit bus, yielding 5.32 TB/s bandwidth. The PG506-232 uses 24 GB of HBM2 on a 3072-bit bus, yielding 933.1 GB/s. The MI300X also has a much higher texture rate at 2,553.6 GTexel/s versus the PG506-232's 322.6 GTexel/s, and a much higher FP32 throughput at 81.72 TFLOPS versus 10.32 TFLOPS. The MI300X has no ROPs, resulting in a 0 MPixel/s pixel rate, while the PG506-232 has 96 ROPs and a 138.2 GPixel/s pixel rate.

The PG506-232 includes 224 tensor cores, which are absent in the MI300X specification. However, the MI300X compensates with a much higher shading unit count: 19,456 versus 3,584. The MI300X also has 1,216 TMUs, compared to the PG506-232's 224. The MI300X uses a PCIe 5.0 x16 interface, while the PG506-232 uses PCIe 4.0 x16. Neither card has display outputs.

Specification Differences

| Specification | AMD Instinct MI300X | NVIDIA PG506-232 |

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

| Architecture | CDNA 3.0 | Ampere |

| Process Node | 5 nm | 7 nm |

| Transistors | 153,000 million | 54,200 million |

| Die Size | 1017 mm² | 826 mm² |

| Base Clock | 1000 MHz | 930 MHz |

| Boost Clock | 2100 MHz | 1440 MHz |

| Memory | 192 GB HBM3 | 24 GB HBM2 |

| Memory Bus | 8192 bit | 3072 bit |

| Memory Bandwidth | 5.32 TB/s | 933.1 GB/s |

| Shading Units | 19456 | 3584 |

| TMUs | 1216 | 224 |

| ROPs | 0 | 96 |

| Tensor Cores | N/A | 224 |

| FP32 Performance | 81.72 TFLOPS | 10.32 TFLOPS |

| Texture Rate | 2,553.6 GTexel/s | 322.6 GTexel/s |

| Pixel Rate | 0 MPixel/s | 138.2 GPixel/s |

| TDP | 750 W | 165 W |

| Slot Width | OAM Module | Dual-slot |

| Power Connectors | None | 8-pin EPS |

| Suggested PSU | 1150 W | 450 W |

| Bus Interface | PCIe 5.0 x16 | PCIe 4.0 x16 |

| Dimensions | Not specified | 267 mm x 112 mm |

| Production Status | Not specified | End-of-life |

| Release Date | 2023-12-05 | 2021-04-11 |