AMD Instinct MI100 vs NVIDIA RTX A4500 Comparison

The Verdict

The recorded data presents a nuanced picture for these two professional workstation accelerators. The NVIDIA RTX A4500 holds the overall average benchmark advantage, but the margin is narrow and the nature of the workloads matters significantly. In the only direct head-to-head benchmark recorded, the Geekbench OpenCL test, the RTX A4500 scores 141,837 against the AMD Instinct MI100's 139,035, a difference of 2%. This places the two cards in the same performance echelon for compute tasks.

The AMD Instinct MI100, however, is positioned as a compute-focused accelerator. Its 32 GB of HBM2 memory with 1.23 TB/s of bandwidth is a clear indicator of its intended role in memory-bandwidth-bound workloads, such as large-scale scientific computing and AI training. Its percentile ranking of 96 places it above the RTX A4500's 93rd percentile, meaning it outperforms a higher percentage of all GPUs in the database.

The RTX A4500, with its 20 GB of GDDR6 memory and a full suite of display outputs (4x DisplayPort 1.4a), is a more versatile workstation card. It is built on the Ampere architecture and includes 56 RT cores and 224 tensor cores, features absent from the MI100. This makes it a natural choice for a broader range of tasks, including real-time 3D rendering, AI inference, and traditional workstation graphics. The data suggests the MI100 is a specialized compute engine, while the RTX A4500 is a generalist.

FAQ

Q: Which GPU has a higher average benchmark score?

A: The NVIDIA RTX A4500 has a higher average benchmark score of 91,671 compared to the AMD Instinct MI100's average of 139,035. However, this average is skewed for the NVIDIA card because it includes a significantly lower score from the 3DMark Steel Nomad DX12 test (3,196), whereas the AMD card has only one recorded score.

Q: How do the two cards compare in the Geekbench OpenCL test?

A: In this specific test, the NVIDIA RTX A4500 wins with a score of 141,837, which is 2% higher than the AMD Instinct MI100's score of 139,035.

Q: Which card has more memory and bandwidth?

A: The AMD Instinct MI100 has a clear advantage in this area, featuring 32 GB of HBM2 memory with a 4096-bit bus and a bandwidth of 1.23 TB/s. The NVIDIA RTX A4500 has 20 GB of GDDR6 memory on a 320-bit bus, providing 640.0 GB/s of bandwidth.

Q: Is one card better for graphics output?

A: Yes, the NVIDIA RTX A4500 has 4x DisplayPort 1.4a outputs. The AMD Instinct MI100 has no display outputs, indicating it is designed for compute-only tasks.

Q: What are the architectural differences in terms of process and transistors?

A: The AMD Instinct MI100 is built on a 7 nm process at TSMC and contains 25,600 million transistors on a 750 mm² die. The NVIDIA RTX A4500 uses an 8 nm process at Samsung, with 28,300 million transistors on a 628 mm² die.

Q: Which card is positioned higher in the overall performance percentile?

A: The AMD Instinct MI100 is in the 96th percentile of all GPUs, while the NVIDIA RTX A4500 is in the 93rd percentile.

Architecture Differences

The two cards are built on fundamentally different architectures from different vendors, which explains their distinct strengths. The AMD Instinct MI100 is based on the CDNA 1.0 architecture, implemented in the Arcturus chip. This is a compute-focused design, prioritizing raw throughput and memory bandwidth for scientific and enterprise compute workloads. It is manufactured on a 7nm process at TSMC, which enables a high transistor density of 34.1 million per mm² on a relatively large 750 mm² die.

The NVIDIA RTX A4500 is built on the Ampere architecture, using the GA102 chip. This architecture is designed for a wider range of tasks, including both compute and graphics. It is manufactured on an 8nm process at Samsung, which results in a slightly lower transistor density of 45.1 million per mm² on a smaller 628 mm² die. The Ampere architecture is notable for its inclusion of dedicated hardware that the CDNA 1.0 architecture lacks: 56 RT cores for hardware-accelerated ray tracing and 224 tensor cores for AI and deep learning acceleration. This difference is pivotal; the MI100 has no RT or tensor cores, meaning it must rely on general-purpose shaders for all tasks. The MI100's CDNA architecture, however, is optimized for FP32 and FP16 compute throughput, with a 2:1 ratio for FP16, whereas the RTX A4500's Ampere architecture provides equal FP32 and FP16 performance.

Specification Differences

The database records several key specification differences between the two accelerators.

• Process Node and Foundry: The MI100 uses a 7nm process at TSMC, while the RTX A4500 uses an 8nm process at Samsung.
• Transistor Count: The MI100 has 25,600 million transistors, the RTX A4500 has 28,300 million.
• Die Size: The MI100's die is 750 mm², the RTX A4500's is 628 mm².
• Base Clock: The MI100 runs at a base clock of 1000 MHz, while the RTX A4500 has a base clock of 1050 MHz.
• Boost Clock: The RTX A4500 boosts to 1650 MHz, higher than the MI100's 1502 MHz.
• Memory: The MI100 has 32 GB of HBM2 on a 4096-bit bus, while the RTX A4500 has 20 GB of GDDR6 on a 320-bit bus. The bandwidth is 1.23 TB/s vs 640.0 GB/s, respectively.
• Shading Units: The MI100 has 7680 shading units, while the RTX A4500 has 7168.
• Texture Mapping Units: The MI100 has 480 TMUs, the RTX A4500 has 224.
• Render Output Units: The MI100 has 64 ROPs, the RTX A4500 has 96.
• RT and Tensor Cores: The MI100 has no RT or tensor cores, while the RTX A4500 has 56 RT cores and 224 tensor cores.
• Pixel and Texture Rates: The RTX A4500 has a higher pixel rate (158.4 GPixel/s vs 96.13 GPixel/s), but the MI100 has a much higher texture rate (721.0 GTexel/s vs 369.6 GTexel/s).
• FP32 Performance: The RTX A4500 has a slight edge in FP32, with 23.65 TFLOPS vs 23.07 TFLOPS.
• FP16 Performance: The MI100 has double the FP16 throughput at 46.14 TFLOPS, while the RTX A4500 offers 23.65 TFLOPS.
• Power Requirement: The MI100 has a TDP of 300 W and requires a 700 W PSU, while the RTX A4500 is more efficient with a 200 W TDP and a 550 W PSU suggestion.
• Power Connectors: The MI100 needs two 8-pin connectors, the RTX A4500 only one.
• Display Outputs: The MI100 has none, the RTX A4500 has 4x DisplayPort 1.4a.
• API Support: The RTX A4500 supports DirectX 12 Ultimate (12_2), OpenGL 4.6, and Vulkan 1.4, while the MI100 has no API support listed.
• Dimensions: The MI100 is 267 mm long and 111 mm high, while the RTX A4500 is 267 mm long and 112 mm high.

Head-to-Head Benchmarks

The database includes a single direct head-to-head benchmark between these two accelerators: the Geekbench OpenCL test. This is a compute-oriented workload that exercises the general-purpose processing capabilities of the GPU.

In this test, the AMD Instinct MI100 scores 139,035. The NVIDIA RTX A4500 scores 141,837. This is a close result, with the RTX A4500 winning by a margin of 2%. In absolute terms, this is a difference of 2,802 points.

Looking at the nearest rivals provides context for this score. The MI100's 139,035 is 0.7% higher than the NVIDIA Tesla V100 PCIe 16 GB (138,063) and 0.9% higher than the Tesla V100 SXM2 32 GB (137,731). It is also 1.9% ahead of the AMD Radeon PRO V620 (136,472) and 2.4% ahead of the AMD Radeon Pro W6800X Duo (135,774).

The RTX A4500's score of 141,837 is also competitive. Its nearest rivals for its overall average score include the AMD Radeon Instinct MI60, which scored 92,466, and the NVIDIA RTX A4500 Mobile at 91,134. But its OpenCL score of 141,837 is the highest single score recorded for it. The MI100's single score is its entire average, while the RTX A4500's average of 91,671 is dragged down by its 3DMark score of 3,196.

This single data point suggests that for pure compute performance, the two cards are very close. The RTX A4500 has a slight edge in this specific test, but the MI100's massive memory bandwidth advantage (1.23 TB/s vs 640.0 GB/s) suggests that it would likely perform better in memory-bound workloads that are not captured by the OpenCL test. The MI100's FP16 performance at double the rate of the RTX A4500 also indicates a significant advantage for certain types of compute tasks, such as AI training where reduced precision is common.

The data shows a clear division: the MI100 is a specialized compute accelerator with massive memory resources and high FP16 throughput, while the RTX A4500 is a more balanced, feature-rich workstation card with dedicated RT and tensor cores. For users whose workloads are dominated by raw memory bandwidth and FP16 compute, the MI100 is the stronger choice. For those who need a general-purpose GPU with display outputs, real-time ray tracing, and a full API suite, the RTX A4500 is the evident pick.