AMD Instinct MI100 vs NVIDIA RTX 4000 SFF Ada Generation Comparison

The AMD Instinct MI100 and NVIDIA RTX 4000 SFF Ada Generation are fundamentally different accelerators, separated by a decade of design philosophy and targeting distinct compute environments. The data shows a clear split: the MI100 leads in raw compute throughput, while the RTX 4000 SFF offers a modern feature set and a drastically lower power envelope. This analysis relies strictly on the provided benchmark scores and architectural facts to determine which card suits which workload.

Head-to-Head Benchmarks

The only overlapping benchmark in the data is Geekbench OpenCL, where the AMD Instinct MI100 posts a score of 139,035 against the NVIDIA RTX 4000 SFF Ada Generation's 124,812. This represents an 11.4% lead for the AMD card, making it the definitive winner in this single head-to-head test. The MI100’s advantage is not marginal; it is a substantial double-digit performance gap that places it clearly ahead in this compute-centric workload.

However, the comparison is more nuanced when examining the broader context of each card's performance. The MI100’s score places it in the 96th percentile of all GPUs, while the RTX 4000 SFF sits at the 95th percentile. This indicates that while the MI100 is faster, both are elite performers in the overall GPU landscape. The MI100’s nearest rival, the NVIDIA Tesla V100 PCIe 16 GB, scores 138,063, just 0.7% behind, showing that the MI100’s victory is consistent with the performance tier it occupies. For the RTX 4000 SFF, its nearest rival is the NVIDIA GB10 with an average score of 117,393, which is 0.3% lower, making the RTX 4000 SFF’s performance competitive with modern high-end compute parts despite its lower raw score.

The RTX 4000 SFF also has a Geekbench Vulkan score of 109,364, a test the MI100 does not have in its data. This is a crucial data point because it shows the NVIDIA card’s ability to excel in a modern graphics API, a domain where the MI100 has no documented support (its DirectX, OpenGL, and Vulkan APIs are all listed as "N/A"). While the MI100 wins the OpenCL comparison by 11.4%, the RTX 4000 SFF’s Vulkan result highlights a capability set that the AMD part simply does not possess in the record.

Architecture Differences

The architectural chasm between these two cards is vast. The AMD Instinct MI100 is built on the CDNA 1.0 architecture, specifically designed for compute, using a 7 nm process at TSMC. It packs 25,600 million transistors on a massive 750 mm² die, resulting in a transistor density of 34.1M per mm². This is a brute-force approach: a large, power-hungry chip with a 300 W TDP and dual-slot cooling. It has no display outputs, confirming its role as a dedicated compute accelerator rather than a workstation graphics card.

In contrast, the NVIDIA RTX 4000 SFF Ada Generation employs the newer Ada Lovelace architecture on a 5 nm process. It contains 35,800 million transistors on a much smaller 294 mm² die, achieving a far higher transistor density of 121.8M per mm². This efficiency is reflected in its 70 W TDP, which is less than a quarter of the MI100’s power draw. The RTX 4000 SFF is an active, modern workstation card with 4x mini-DisplayPort 1.4a outputs, indicating its purpose is both compute and visualization.

Memory configurations also diverge significantly. The MI100 uses 32 GB of HBM2 with a 4096-bit bus, delivering a colossal 1.23 TB/s of bandwidth. The RTX 4000 SFF utilizes 20 GB of GDDR6 on a 160-bit bus, providing 280.0 GB/s. This is a 4.4x difference in memory bandwidth in favor of the AMD card, which is critical for memory-bound compute workloads. The MI100’s compute units are also more numerous: 7680 shading units, 480 TMUs, and 64 ROPs, with a peak FP32 throughput of 23.07 TFLOPS. The RTX 4000 SFF has 6144 shading units, 192 TMUs, and 64 ROPs, yielding 19.17 TFLOPS FP32. While the MI100 has a higher raw shader count and FP32 rate, the RTX 4000 SFF includes 48 RT cores and 192 tensor cores, hardware that the MI100 lacks entirely (listed as null). This makes the NVIDIA card a more versatile accelerator for ray-traced rendering and AI inference tasks.

Where Each One Wins

The AMD Instinct MI100 is the clear winner in raw, continuous compute throughput. Its 11.4% OpenCL lead over the RTX 4000 SFF, combined with its massive 1.23 TB/s memory bandwidth and 32 GB HBM2 pool, makes it the superior choice for large-scale scientific simulation, high-performance computing (HPC), and any workload that saturates memory bandwidth. The data reinforces this: its texture rate of 721.0 GTexel/s is more than double the RTX 4000 SFF’s 299.5 GTexel/s, and its FP32 output is 20% higher. This is a card designed to crunch numbers for hours without pause.

The NVIDIA RTX 4000 SFF Ada Generation wins in flexibility and efficiency. Its 70 W TDP and lack of external power connectors (it draws power solely from the PCIe slot) make it deployable in dense, low-power systems where the MI100’s 300 W requirement and 2x 8-pin connectors would be impractical. The RTX 4000 SFF also has a functional Vulkan API and a documented Geekbench Vulkan score of 109,364, enabling modern graphics workloads that the MI100 cannot handle. Its 48 RT cores and 192 tensor cores provide dedicated hardware for ray tracing and AI acceleration, making it the superior choice for content creation, 3D rendering, and inference tasks that leverage these features. Furthermore, its 168 mm length and 69 mm height make it a compact SFF solution, whereas the MI100 is a 267 mm dual-slot card.

FAQ

Q: Which card is faster in Geekbench OpenCL?

A: The AMD Instinct MI100 is faster, scoring 139,035 compared to the NVIDIA RTX 4000 SFF Ada Generation's 124,812, a lead of 11.4%.

Q: Does the RTX 4000 SFF support any graphics API?

A: Yes, the RTX 4000 SFF supports DirectX 12 Ultimate (12_2), OpenGL 4.6, and Vulkan 1.4, and has a Geekbench Vulkan score of 109,364. The MI100 has no documented graphics API support.

Q: What is the memory bandwidth difference?

A: The MI100 has a memory bandwidth of 1.23 TB/s using HBM2, while the RTX 4000 SFF has 280.0 GB/s using GDDR6. The MI100’s bandwidth is over four times higher.

Q: Which card has a higher power consumption?

A: The MI100 has a TDP of 300 W, whereas the RTX 4000 SFF has a TDP of only 70 W.

Q: Which card has ray tracing and tensor core hardware?

A: The NVIDIA RTX 4000 SFF Ada Generation has 48 RT cores and 192 tensor cores. The AMD Instinct MI100 has no such hardware listed in its specifications.

Q: What is the transistor density of each chip?

A: The MI100's Arcturus chip has a density of 34.1M transistors per mm², while the RTX 4000 SFF's AD104 chip has a density of 121.8M transistors per mm².

The Verdict

Based strictly on the data, the choice between these two cards depends entirely on the workload's priorities. For pure compute performance, the AMD Instinct MI100 is the winner. Its 11.4% advantage in OpenCL, combined with superior memory bandwidth and a higher FP32 rate, makes it the definitive choice for high-throughput scientific and HPC tasks where power consumption is a secondary concern. The data shows it is a more powerful compute engine.

For a workstation environment requiring both compute and graphics, the NVIDIA RTX 4000 SFF Ada Generation is the clear pick. It offers Vulkan support, a documented graphics score, and dedicated RT and tensor cores, making it far more versatile. Its 70 W power draw and compact dimensions allow for deployment in scenarios where the MI100’s 300 W power requirement would be prohibitive. While it trails in raw OpenCL performance, its modern feature set and efficiency make it the more practical and capable card for a wider range of professional tasks. Users needing pure number-crunching should choose the MI100; users needing a balanced, efficient, and feature-rich accelerator should choose the RTX 4000 SFF.