AMD Instinct MI100 vs NVIDIA B200 Comparison

The NVIDIA B200 and AMD Instinct MI100 represent two distinct eras of accelerated computing, with the data showing a generational chasm in raw performance. The B200, based on the Blackwell architecture, is an active, flagship server solution, while the MI100, built on CDNA 1.0, is an end-of-life product from a previous cycle. Benchmark results from Geekbench OpenCL illustrate a decisive victory for the newer NVIDIA part, but the comparison also highlights the MI100’s own historical standing and architectural trade-offs.

Head-to-Head Benchmarks

The single available head-to-head benchmark, Geekbench OpenCL, delivers a clear verdict. The NVIDIA B200 scores 345,482 points, while the AMD Instinct MI100 scores 139,035 points. This translates to a 148.5% delta in favor of the B200, meaning the NVIDIA accelerator is roughly two and a half times faster in this compute test. The margin is immense and reflects the massive resource disparity between the two cards.

Contextualizing the B200’s score, it sits in the 100th percentile of all GPUs, a perfect placement that indicates it outperforms nearly every other accelerator in the database. Its nearest rival, the NVIDIA B300 SXM6 AC, scores 369,831, placing the B200 6.6% behind that newer part. More relevantly, the B200 is 3.2% ahead of the NVIDIA H200 NVL (334,891 points) and 8.6% ahead of the AMD Instinct MI300X (317,994 points). The B200’s lead over the MI100 is not just significant; it is orders of magnitude larger than its advantages over its closest competitors, underscoring the vast performance gap between the two generations.

For the MI100, its score of 139,035 places it in the 96th percentile of all GPUs, which is still a strong showing historically. However, its nearest rivals are all older or lower-tier parts. It is only 0.7% ahead of the NVIDIA Tesla V100 PCIe 16 GB (138,063 points) and 0.9% ahead of the Tesla V100 SXM2 32 GB (137,731 points). It also edges out the AMD Radeon PRO V620 by 1.9% (136,472 points) and the AMD Radeon Pro W6800X Duo by 2.4% (135,774 points). The data shows that while the MI100 was a high performer in its day, the B200 has moved the performance needle so far forward that the MI100 is now competing with parts from a previous hardware generation.

Where Each One Wins

The benchmark data provides a clear split: the NVIDIA B200 wins the only compute test available, and it does so by a wide margin. Its victory is rooted in sheer processing power and memory bandwidth, making it the clear choice for any workload that is limited by raw FP32 or FP16 throughput. The B200’s 74.45 TFLOPS of FP32 performance and 1,191.2 TFLOPS of FP16 performance (16:1 ratio) dwarf the MI100’s 23.07 TFLOPS FP32 and 46.14 TFLOPS FP16 (2:1 ratio). For large-scale AI training, scientific simulation, or any heavy compute task, the B200 is the definitive winner.

The AMD Instinct MI100, while losing the head-to-head, still holds a niche in specific legacy or power-constrained environments. Its 300 W TDP is significantly lower than the B200’s 1000 W TDP, and it uses a standard dual-slot design with 2x 8-pin power connectors, making it easier to integrate into existing infrastructure. The MI100’s 32 GB of HBM2 memory, while smaller and slower than the B200’s 90 GB of HBM3e, is still substantial for its era. Its 96th percentile standing shows it remains a capable compute accelerator for tasks that do not require the absolute latest hardware, particularly in systems where a 700 W suggested PSU is preferred over the B200’s 1400 W suggestion. However, the data does not show any benchmark where the MI100 wins; its advantages are purely practical and architectural, not performance-based.

Architecture Differences

The architectural divide between the B200 and MI100 is stark, reflecting a five-year evolution in design philosophy. The NVIDIA B200 is built on the Blackwell architecture using the GB100 chip, manufactured on a 5 nm process at TSMC. It packs 104,000 million transistors. In contrast, the AMD Instinct MI100 uses the CDNA 1.0 architecture with the Arcturus chip, built on an older 7 nm process, also at TSMC, with 25,600 million transistors and a die size of 750 mm². The B200’s transistor count is over four times higher, enabling a massive increase in compute resources.

Memory subsystems differ dramatically. The B200 features 90 GB of HBM3e memory on a 4096-bit bus, delivering a bandwidth of 4.10 TB/s. The MI100 offers 32 GB of HBM2 memory on the same 4096-bit bus width, but its bandwidth is only 1.23 TB/s. The B200’s memory bandwidth is over three times higher, which is critical for feeding its massive compute cores. Clock speeds tell a different story: the MI100 has a higher base clock (1000 MHz vs. 700 MHz) and a lower boost clock (1502 MHz vs. 1965 MHz) compared to the B200, but the B200’s sheer core count overwhelms any clock advantage.

Core configurations are incomparable. The B200 has 18,944 shading units, 592 TMUs, and 24 ROPs, along with 592 tensor cores. The MI100 has 7,680 shading units, 480 TMUs, and 64 ROPs, with no dedicated tensor cores listed. The B200’s tensor cores are a key differentiator for AI workloads, providing hardware acceleration for matrix operations that the MI100 lacks. The B200 also has a higher texture rate (1,163.3 GTexel/s vs. 721.0 GTexel/s) but a lower pixel rate (47.16 GPixel/s vs. 96.13 GPixel/s), an oddity that reflects its compute-first design over traditional graphics rasterization. The B200 uses a PCIe 5.0 x16 interface, while the MI100 is limited to PCIe 4.0 x16, halving the potential host-to-device transfer bandwidth.

FAQ

Q: Which GPU has a higher Geekbench OpenCL score?

A: The NVIDIA B200 scores 345,482, which is 148.5% higher than the AMD Instinct MI100’s score of 139,035.

Q: How does the memory bandwidth compare between the two?

A: The NVIDIA B200 has a bandwidth of 4.10 TB/s using HBM3e memory, while the AMD Instinct MI100 has a bandwidth of 1.23 TB/s using HBM2 memory.

Q: Is the AMD Instinct MI100 still a competitive accelerator in the current market?

A: Benchmark data shows the MI100 is in the 96th percentile of all GPUs, but it only edges out older rivals like the NVIDIA Tesla V100 by less than 1%. It is not competitive with the B200, which scores 148.5% higher.

Q: What are the power consumption requirements for each card?

A: The NVIDIA B200 has a TDP of 1000 W and requires a suggested PSU of 1400 W. The AMD Instinct MI100 has a TDP of 300 W and requires a suggested PSU of 700 W.

Q: Do both GPUs use the same memory bus width?

A: Yes, both the NVIDIA B200 and the AMD Instinct MI100 have a 4096-bit memory bus width.

Q: What is the transistor count difference?

A: The NVIDIA B200 has 104,000 million transistors, while the AMD Instinct MI100 has 25,600 million transistors.

Specification Differences

| Specification | NVIDIA B200 | AMD Instinct MI100 |

| :--- | :--- | :--- |

| Architecture | Blackwell | CDNA 1.0 |

| Process Node | 5 nm | 7 nm |

| Transistors | 104,000 million | 25,600 million |

| Die Size | Not specified | 750 mm² |

| Transistor Density | Not specified | 34.1M / mm² |

| Base Clock | 700 MHz | 1000 MHz |

| Boost Clock | 1965 MHz | 1502 MHz |

| Memory Size | 90 GB | 32 GB |

| Memory Type | HBM3e | HBM2 |

| Memory Clock | 2000 MHz (8 Gbps effective) | 1200 MHz (2.4 Gbps effective) |

| Memory Bandwidth | 4.10 TB/s | 1.23 TB/s |

| Shading Units | 18,944 | 7,680 |

| TMUs | 592 | 480 |

| ROPs | 24 | 64 |

| Tensor Cores | 592 | Not specified |

| Pixel Rate | 47.16 GPixel/s | 96.13 GPixel/s |

| Texture Rate | 1,163.3 GTexel/s | 721.0 GTexel/s |

| FP32 Performance | 74.45 TFLOPS | 23.07 TFLOPS |

| FP16 Performance | 1,191.2 TFLOPS (16:1) | 46.14 TFLOPS (2:1) |

| TDP | 1000 W | 300 W |

| Slot Width | SXM Module | Dual-slot |

| Power Connectors | Not specified | 2x 8-pin |

| Suggested PSU | 1400 W | 700 W |

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

| Production Status | Active | End-of-life |

| Release Date | Not specified | 2020-11-15 |