NVIDIA A100 SXM4 80 GB vs NVIDIA L4 Comparison

The NVIDIA A100 SXM4 80 GB and the NVIDIA L4 serve entirely different segments of the server market, and the benchmark data reflects that divide. The A100 SXM4 80 GB, built on the Ampere architecture, is a high-power compute accelerator designed for maximum throughput, while the L4, based on Ada Lovelace, is a low-power, energy-efficient inference-oriented card. The single head-to-head benchmark available—Geekbench Vulkan—shows the A100 SXM4 80 GB scoring 183,725 against the L4’s 121,306, a 51.5% advantage. However, this single result only tells part of the story, as the two cards have fundamentally different strengths in raw compute, memory bandwidth, and power efficiency.

Where Each One Wins

The A100 SXM4 80 GB wins decisively in the only direct benchmark comparison available. Its Geekbench Vulkan score of 183,725 places it in the 98th percentile of all GPUs, while the L4’s best score of 140,838 (from its OpenCL test) places it in the 95th percentile. In the head-to-head Vulkan test, the A100 outperforms the L4 by 51.5%, a massive margin that suggests the A100 is far better suited for graphics-heavy or compute-intensive workloads that leverage Vulkan. The A100’s average benchmark score of 183,725 is also dramatically higher than the L4’s average of 131,072, reinforcing its superiority in raw performance.

The L4, however, wins in the efficiency and form-factor arena, though the data does not include a direct efficiency benchmark. The L4’s TDP is 72 W compared to the A100’s 400 W, and its suggested PSU is 250 W versus 800 W. This means the L4 can be deployed in far more power-constrained environments, such as edge servers or dense multi-GPU configurations, where the A100’s power draw would be prohibitive. The L4 is also a single-slot card measuring 169 mm in length, while the A100 uses an OAM Module form factor, making the L4 far easier to integrate into existing PCIe slots. For workloads that are memory-bandwidth-sensitive rather than compute-heavy, the A100’s 2.04 TB/s bandwidth versus the L4’s 300.1 GB/s gives the A100 a clear edge, but the L4’s 24 GB of GDDR6 memory may be sufficient for many inference tasks.

Architecture Differences

The architectural divide between these two cards is stark. The A100 SXM4 80 GB uses the GA100 chip, built on a 7 nm process at TSMC, with 54,200 million transistors on an 826 mm² die. This results in a transistor density of 65.6M per mm². The L4 uses the AD104 chip, fabricated on a more advanced 5 nm process, also at TSMC, packing 35,800 million transistors into a much smaller 294 mm² die, yielding a density of 121.8M per mm². The L4’s newer process node allows for nearly double the transistor density, which is a key factor in its dramatically lower power consumption.

Clock speeds also differ significantly. The A100 has a base clock of 1275 MHz and a boost clock of 1410 MHz, while the L4 runs at a lower 795 MHz base but boosts to 2040 MHz. This higher boost clock on the L4 helps it achieve 30.29 TFLOPS of FP32 performance, compared to the A100’s 19.49 TFLOPS. The L4 also has more shading units (7424 versus 6912) but fewer TMUs (240 versus 432) and ROPs (80 versus 160). The A100 counters with 432 tensor cores, while the L4 has 240; the A100’s FP16 performance is 77.97 TFLOPS (4:1), whereas the L4 achieves 30.29 TFLOPS (1:1). The A100 also features no RT cores, while the L4 includes 60 RT cores, making the L4 more capable for ray-tracing tasks.

Memory architecture is another major divergence. The A100 uses 80 GB of HBM2e on a 5120-bit bus, delivering 2.04 TB/s of bandwidth. The L4 uses 24 GB of GDDR6 on a 192-bit bus, providing 300.1 GB/s. This 6.8x bandwidth advantage for the A100 is critical for large datasets, while the L4’s smaller memory pool may be a bottleneck for certain workloads. The A100 has no display outputs, and neither does the L4, but the L4 supports DirectX 12 Ultimate, OpenGL 4.6, and Vulkan 1.4, while the A100’s API support is not listed.

Head-to-Head Benchmarks

The only direct comparison in the data is the Geekbench Vulkan test, where the A100 SXM4 80 GB scores 183,725 and the L4 scores 121,306. The A100 wins by 51.5%, which is a substantial margin. To put this in context, the A100’s nearest rival is the NVIDIA RTX 5000 Ada Generation, which scores 184,664, just 0.5% higher. The A100 also trails the A100 SXM4 40 GB by 1.8% (that card scores 187,147) and beats the GeForce RTX 4090 D by 3.2% (which scores 178,050). This places the A100 in a competitive tier with modern high-end cards, despite being from an older architecture generation.

The L4’s Vulkan score of 121,306 is weaker, but its OpenCL score of 140,838 is notably higher, suggesting the L4 performs better in compute-oriented APIs. The L4’s average benchmark score of 131,072 puts it near the NVIDIA GeForce RTX 3090 Ti, which averages 131,938 (0.7% higher), and the RTX 4000 Ada Generation, which scores 135,218 (3.1% higher). The L4 also trails the NVIDIA A10M by 3.1% and the AMD Radeon PRO W6800 by 3.2%. These comparisons show that the L4 is competitive with mid-range to high-end workstation cards, but it is not in the same performance class as the A100.

The 51.5% delta in Vulkan performance is the clearest indicator of the performance gap. However, it is worth remembering this is a single test, and the L4’s higher FP32 throughput (30.29 versus 19.49 TFLOPS) suggests that in certain compute workloads, the L4 could close the gap or even outperform the A100, despite the Vulkan result. The A100’s advantage likely stems from its massive memory bandwidth and higher tensor core count, which are critical for AI training and large-scale matrix operations.

FAQ

Q: Which GPU has higher raw FP32 compute performance?

A: The NVIDIA L4 delivers 30.29 TFLOPS of FP32 performance, which is 55% higher than the A100 SXM4 80 GB’s 19.49 TFLOPS. This indicates the L4 may be better suited for single-precision compute tasks.

Q: How do the memory bandwidths compare?

A: The A100 SXM4 80 GB has a bandwidth of 2.04 TB/s, which is over 6.8 times the L4’s 300.1 GB/s. The A100 also has 80 GB of HBM2e memory versus the L4’s 24 GB of GDDR6, making the A100 far superior for memory-intensive workloads.

Q: What is the power consumption difference?

A: The L4 has a TDP of 72 W and a suggested PSU of 250 W, while the A100 has a TDP of 400 W and a suggested PSU of 800 W. The L4 is thus significantly more power-efficient, which is a key advantage for dense deployments.

Q: Which card is better for Vulkan-based applications?

A: The A100 SXM4 80 GB wins the Geekbench Vulkan test with a score of 183,725, which is 51.5% higher than the L4’s 121,306. The A100 also places in the 98th percentile of all GPUs, compared to the L4’s 95th percentile.

Q: Does the L4 support ray tracing?

A: Yes, the L4 has 60 RT cores, while the A100 has no RT cores listed. This makes the L4 more capable for ray-tracing or graphics workloads that benefit from dedicated RT hardware.

Q: What are the physical form factor differences?

A: The L4 is a single-slot card measuring 169 mm in length, while the A100 uses an OAM Module form factor. The L4 also has a lower power draw, making it easier to install in standard servers.

The Verdict

The data clearly shows that the A100 SXM4 80 GB is the superior performer in the single benchmark available, with a 51.5% lead in Geekbench Vulkan. Its 98th percentile ranking and 2.04 TB/s memory bandwidth make it the obvious choice for high-end AI training, large-scale scientific computing, or any workload that demands massive memory throughput. The A100’s 80 GB of HBM2e memory is also a significant advantage over the L4’s 24 GB, allowing for larger models and datasets to be processed without spilling to system memory.

The L4, however, is not without merit. Its 30.29 TFLOPS of FP32 compute is substantially higher than the A100’s 19.49 TFLOPS, and its 72 W TDP is a fraction of the A100’s 400 W. For inference workloads that are compute-bound rather than memory-bound, the L4 may offer better performance per watt. The L4 also supports ray tracing via 60 RT cores, which the A100 lacks, and its smaller size and lower power requirements make it far more flexible for edge deployments or multi-card servers. The L4’s OpenCL score of 140,838 is also respectable, showing it can handle compute tasks effectively.

For users prioritizing raw performance and memory capacity, the A100 SXM4 80 GB is the clear winner from the available data. For those needing efficient, compact, and lower-power acceleration, the L4 is the more practical option, despite its lower benchmark scores. The choice ultimately hinges on whether the workload is memory-bandwidth-bound (favoring the A100) or compute-bound with power constraints (favoring the L4).

Specification Differences

| Specification | NVIDIA A100 SXM4 80 GB | NVIDIA L4 |

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

| Architecture | Ampere | Ada Lovelace |

| Process Node | 7 nm | 5 nm |

| Transistors | 54,200 million | 35,800 million |

| Die Size | 826 mm² | 294 mm² |

| Transistor Density | 65.6M / mm² | 121.8M / mm² |

| Base Clock | 1275 MHz | 795 MHz |

| Boost Clock | 1410 MHz | 2040 MHz |

| Memory Clock | 1593 MHz (3.2 Gbps effective) | 1563 MHz (12.5 Gbps effective) |

| Memory Size | 80 GB | 24 GB |

| Memory Type | HBM2e | GDDR6 |

| Memory Bus Width | 5120 bit | 192 bit |

| Memory Bandwidth | 2.04 TB/s | 300.1 GB/s |

| Shading Units | 6912 | 7424 |

| TMUs | 432 | 240 |

| ROPs | 160 | 80 |

| RT Cores | N/A | 60 |

| Tensor Cores | 432 | 240 |

| Pixel Rate | 225.6 GPixel/s | 163.2 GPixel/s |

| Texture Rate | 609.1 GTexel/s | 489.6 GTexel/s |

| FP32 Performance | 19.49 TFLOPS | 30.29 TFLOPS |

| FP16 Performance | 77.97 TFLOPS (4:1) | 30.29 TFLOPS (1:1) |

| TDP | 400 W | 72 W |

| Slot Width | OAM Module | Single-slot |

| Suggested PSU | 800 W | 250 W |

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

| Display Outputs | No outputs | No outputs |

| DirectX Support | N/A | 12 Ultimate (12_2) |

| OpenGL Support | N/A | 4.6 |

| Vulkan Support | N/A | 1.4 |

| Dimensions (Length) | N/A | 169 mm |

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

| Release Date | 2020-11-15 | 2023-03-20 |

| Predecessor | Tesla Turing | Server Ampere |

| Successor | Server Ada | Server Hopper |