GPU Comparison

The AMD Instinct MI100 and NVIDIA L4 are both accelerator cards built for servers, but they target very different workloads and deployment scenarios. Benchmark data shows the NVIDIA L4 holds a narrow lead in the single available compute test, but the two cards diverge sharply in architecture, memory design, and physical requirements, making the choice between them a matter of matching hardware to specific job profiles.

Where Each One Wins

The NVIDIA L4 wins the only head-to-head benchmark recorded in the database: the Geekbench OpenCL test. It scores 140,838 points against the MI100's 139,035, a 1.3% advantage. This is a slim margin, but it represents a real performance edge for the L4 in general-purpose compute workloads that scale well with raw FP32 throughput. The L4's FP32 rating of 30.29 TFLOPS is roughly 31% higher than the MI100's 23.07 TFLOPS, which explains its lead in this test.

However, the MI100 is not without its own territory. The AMD card is built around HBM2 memory with a 4096-bit bus, delivering 1.23 TB/s of bandwidth, over four times the L4's 300.1 GB/s. For memory-bound workloads where data movement dominates computation, the MI100's architecture has a clear structural advantage. It also has significantly more shading units (7680 vs 7424) and texture mapping units (480 vs 240), though the L4 compensates with higher clock speeds.

The L4's wins extend to API support. It offers DirectX 12 Ultimate, OpenGL 4.6, and Vulkan 1.4, while the MI100 lists N/A for all three graphics APIs. This makes the L4 a viable option for compute tasks that also require some rendering or graphics interoperability, whereas the MI100 is strictly a compute-only accelerator with no display outputs.

Architecture Differences

These are fundamentally different designs from different eras. The MI100 uses AMD's CDNA 1.0 architecture on the Arcturus chip, built on TSMC's 7 nm process. It packs 25,600 million transistors into a massive 750 mm² die, yielding a transistor density of 34.1 million per mm². The L4, in contrast, uses NVIDIA's Ada Lovelace architecture on the AD104 chip, fabricated on TSMC's 5 nm process. It crams 35,800 million transistors into a much smaller 294 mm² die, achieving 121.8 million transistors per mm², a density roughly 3.6 times higher.

Clock speeds tell a similar story of generational shift. The MI100 runs at a base of 1000 MHz and boosts to 1502 MHz, while the L4 has a lower base of 795 MHz but boosts to 2040 MHz. This higher boost clock drives the L4's FP32 advantage despite having fewer TMUs and slightly fewer shading units.

The memory subsystems could not be more different. The MI100 offers 32 GB of HBM2 on a 4096-bit interface, running at 1200 MHz (2.4 Gbps effective) for 1.23 TB/s bandwidth. The L4 provides 24 GB of GDDR6 on a 192-bit bus, at 1563 MHz (12.5 Gbps effective) for 300.1 GB/s. The MI100 has four times the memory bandwidth, while the L4 has more than enough capacity for many inference workloads.

Power and physical design diverge dramatically. The MI100 is a dual-slot card consuming 300 W, requiring two 8-pin power connectors and a 700 W suggested PSU. It measures 267 mm by 111 mm. The L4 is a single-slot card at 72 W, needing no power connectors, with a 250 W suggested PSU, and measures just 169 mm by 56 mm. The L4 also includes hardware features the MI100 lacks: 60 ray tracing cores and 240 tensor cores, which the AMD card does not list.

The Verdict

The data points to a clear split. The NVIDIA L4 wins on raw compute performance in the available benchmark, offers modern API support, includes tensor and ray tracing cores, and does so in a fraction of the power envelope and physical footprint. Its 30.29 TFLOPS FP32 and 30.29 TFLOPS FP16 (1:1 ratio) make it a versatile accelerator for AI inference and general compute, and its 95th percentile ranking among all GPUs confirms strong overall standing.

The AMD Instinct MI100, despite being older and end-of-life, retains one overwhelming advantage: memory bandwidth. At 1.23 TB/s, it outclasses the L4 by more than 4x, and its 32 GB capacity is 33% larger. For workloads that are bandwidth-saturated, large matrix operations, certain scientific simulations, or data-intensive analytics, the MI100's architecture is purpose-built. Its 96th percentile ranking is marginally higher than the L4's 95th, suggesting comparable overall performance class.

Pick the L4 if you need a low-power, single-slot accelerator with modern features, tensor core acceleration, and the flexibility of graphics APIs. Pick the MI100 if your workloads are dominated by memory throughput and you have the power and space budget for a 300 W dual-slot card. The benchmark delta is small, but the architectural deltas are enormous.

FAQ

Q: Which card is faster in Geekbench OpenCL?

A: The NVIDIA L4 scores 140,838 versus the AMD MI100's 139,035, a 1.3% advantage for the L4.

Q: How much memory bandwidth does each card have?

A: The MI100 has 1.23 TB/s from 32 GB of HBM2 on a 4096-bit bus, while the L4 has 300.1 GB/s from 24 GB of GDDR6 on a 192-bit bus.

Q: What is the power consumption difference?

A: The MI100 is rated at 300 W with a 700 W suggested PSU, while the L4 is rated at 72 W with a 250 W suggested PSU.

Q: Does either card support graphics APIs?

A: The L4 supports DirectX 12 Ultimate, OpenGL 4.6, and Vulkan 1.4. The MI100 lists N/A for all three.

Q: Which card has tensor cores?

A: The L4 includes 240 tensor cores and 60 ray tracing cores. The MI100 does not list any tensor or ray tracing cores.

Q: What is the transistor density difference?

A: The L4's AD104 chip achieves 121.8 million transistors per mm² on a 294 mm² die, while the MI100's Arcturus chip has 34.1 million per mm² on a 750 mm² die.

Head-to-Head Benchmarks

The only direct benchmark comparison is Geekbench OpenCL, where the NVIDIA L4 wins 140,838 to 139,035, a delta of 1.3%. This is a tight race, but the result aligns with the theoretical FP32 throughput difference: the L4's 30.29 TFLOPS versus the MI100's 23.07 TFLOPS means the L4 has about 31% more raw single-precision compute. The MI100's higher memory bandwidth (1.23 TB/s vs 300.1 GB/s) did not overcome this deficit in this particular test, suggesting the workload was not bandwidth-limited.

The L4's victory is also supported by its position among rivals. Its nearest competitor, the NVIDIA GeForce RTX 3090 Ti, scores 131,938, which is 0.7% lower than the L4's average of 131,072, meaning the L4 actually outperforms its closest listed rival by a small margin. The RTX 4000 Ada Generation, A10M, and AMD Radeon PRO W6800 all score between 135,218 and 135,396, putting them roughly 3.1–3.2% ahead of the L4's average score.

The MI100's average score of 139,035 places it 0.7% ahead of the Tesla V100 PCIe 16 GB, 0.9% ahead of the Tesla V100 SXM2 32 GB, 1.9% ahead of the Radeon PRO V620, and 2.4% ahead of the Radeon Pro W6800X Duo. These are all modest margins, indicating the MI100 sits in a competitive performance band.

While the L4 wins the compute benchmark, the MI100's structural advantages should not be dismissed. The 4x bandwidth lead and 33% larger memory capacity are decisive for specific workloads. The data shows two cards designed for different bottlenecks: the L4 for compute throughput and efficiency, the MI100 for memory-intensive operations. In a straight compute race, the L4 edges ahead; in a memory-bound scenario, the MI100's HBM2 design would likely dominate. The 1.3% benchmark delta is real but narrow, and the architectural chasm between the two is far wider.