NVIDIA L40 vs NVIDIA PG506-232 Comparison

The NVIDIA L40 and NVIDIA PG506-232 represent two distinct approaches to server-side acceleration, separated by a full architecture generation. The benchmark data shows a clear overall winner, but the specifics of each card’s design reveal a more nuanced picture than a single score suggests. The L40, built on the Ada Lovelace architecture, delivers a dominant performance lead, while the PG506-232, an Ampere-era product, counters with a unique memory subsystem and a significantly lower power envelope. This analysis will break down the head-to-head results, explore where each card excels, and clarify the architectural choices that define their respective positions in the server market.

Head-to-Head Benchmarks

The sole direct benchmark comparison available between these two GPUs is the Geekbench OpenCL test, and the results are decisively in favor of the NVIDIA L40. In this test, the L40 achieved a score of 330,926, while the PG506-232 scored 225,124. This represents a delta of 47%, meaning the L40 is nearly half again as fast as the PG506-232 in this compute-oriented workload. The magnitude of this gap is not a marginal improvement; it indicates a fundamental shift in compute capability between the two generations.

When placed in the context of their respective peer groups, the scores take on additional meaning. The L40’s average benchmark score is 284,111, which places it in the 99th percentile of all GPUs. Its nearest rival, the NVIDIA RTX 6000 Ada Generation, has an average score of 287,237, which is only 1.1% higher. This shows the L40 is essentially at the top of its class, with only a marginal performance delta separating it from the very best. The PG506-232, while also in the 99th percentile with an average score of 225,124, sits in a different performance tier. Its closest rival, the AMD Radeon PRO W7900D, scores 219,827, a delta of 2.4% in favor of the PG506-232. The data suggests that while both cards are elite performers, the L40 operates in an entirely higher performance bracket.

The 47% delta in the head-to-head test is the single most important number in this comparison. It is not a case of one card being slightly faster; it is a case of one card being in a different league. The L40’s score is closer to that of the AMD Instinct MI300X (317,994), which it trails by 10.7%, than it is to the PG506-232. This positions the L40 as a contender with the most powerful accelerators available, while the PG506-232’s performance is more aligned with upper-midrange server offerings.

Where Each One Wins

Based on the available benchmark data, the NVIDIA L40 wins in the only direct comparison available. However, the specification differences suggest distinct use cases where each card could be the more logical choice, even if the L40 is faster in raw compute. The L40’s victory is rooted in its massive compute throughput and modern feature set, while the PG506-232’s appeal lies in its specialized memory architecture and lower system demands.

The L40 is the clear winner for any workload that prioritizes raw compute throughput. Its FP32 performance of 90.52 TFLOPS dwarfs the PG506-232’s 10.32 TFLOPS, making it the obvious choice for simulation, scientific computing, or any task that relies on heavy single-precision math. Its 48 GB of GDDR6 memory is double the capacity of the PG506-232, which is a critical advantage for large datasets and complex models. Furthermore, the L40’s support for DirectX 12 Ultimate, OpenGL 4.6, and Vulkan 1.4, alongside its 4x DisplayPort 1.4a outputs, makes it a more versatile card that can be used for rendering and visualization tasks, not just pure compute.

The PG506-232, despite its lower compute scores, wins in the efficiency and memory bandwidth categories. Its TDP is 165 W, nearly half of the L40’s 300 W, and it requires a suggested power supply of 450 W versus the L40’s 700 W. This makes it a far more attractive option for dense server deployments where power and cooling are at a premium. More importantly, its memory configuration is fundamentally different. The PG506-232 uses 24 GB of HBM2 memory on a 3072-bit bus, resulting in a bandwidth of 933.1 GB/s, which is actually higher than the L40’s 864.0 GB/s. For workloads that are intensely memory-bandwidth-bound, such as certain AI inference tasks or data analytics, the PG506-232 could potentially offer a performance advantage that the OpenCL benchmark does not capture.

FAQ

Q: Based on the benchmark data, which GPU is faster in the Geekbench OpenCL test?

A: The NVIDIA L40 is significantly faster, scoring 330,926 compared to the PG506-232’s 225,124. This represents a 47% performance difference in favor of the L40.

Q: How does the L40’s performance compare to its closest rival, the NVIDIA RTX 6000 Ada Generation?

A: The L40’s average benchmark score is 284,111, while the RTX 6000 Ada Generation scores 287,237. This makes the RTX 6000 Ada Generation only 1.1% faster, placing the L40 in a near-identical performance tier.

Q: Does the PG506-232 have any performance advantage over the L40 in terms of memory?

A: Yes, the PG506-232 has a higher memory bandwidth of 933.1 GB/s compared to the L40’s 864.0 GB/s, despite having half the memory capacity (24 GB vs 48 GB). This is due to its use of HBM2 memory on a 3072-bit bus.

Q: What is the difference in power consumption between the two cards?

A: The PG506-232 has a TDP of 165 W, which is significantly lower than the L40’s 300 W. The PG506-232 also requires a smaller suggested power supply of 450 W, compared to the L40’s 700 W.

Q: Which GPU is better suited for a workload that requires a display output?

A: The NVIDIA L40 is the clear choice, as it features 4x DisplayPort 1.4a outputs. The PG506-232 has no display outputs, making it a compute-only accelerator.

Q: Are both GPUs in the same performance percentile relative to all other GPUs?

A: Yes, both the NVIDIA L40 and the NVIDIA PG506-232 are in the 99th percentile of all GPUs, indicating that both are high-end, top-tier performers, even though the L40 is significantly faster.

Specification Differences

The fundamental differences between the L40 and PG506-232 are stark, reflecting their different architectural generations and design goals. The L40 is built for maximum compute performance and versatility, while the PG506-232 is a more specialized, power-efficient compute accelerator.

| Specification | NVIDIA L40 | NVIDIA PG506-232 |

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

| Process Node | 5 nm | 7 nm |

| Transistors | 76,300 million | 54,200 million |

| Die Size | 609 mm² | 826 mm² |

| Transistor Density | 125.3M / mm² | 65.6M / mm² |

| Base Clock | 735 MHz | 930 MHz |

| Boost Clock | 2490 MHz | 1440 MHz |

| Memory Size | 48 GB | 24 GB |

| Memory Type | GDDR6 | HBM2 |

| Memory Bus Width | 384 bit | 3072 bit |

| Memory Bandwidth | 864.0 GB/s | 933.1 GB/s |

| Shading Units | 18176 | 3584 |

| TMUs | 568 | 224 |

| ROPs | 192 | 96 |

| Tensor Cores | 568 | 224 |

| Pixel Rate | 478.1 GPixel/s | 138.2 GPixel/s |

| Texture Rate | 1,414.3 GTexel/s | 322.6 GTexel/s |

| FP32 Performance | 90.52 TFLOPS | 10.32 TFLOPS |

| TDP | 300 W | 165 W |

| Power Connectors | 1x 16-pin | 8-pin EPS |

| Suggested PSU | 700 W | 450 W |

| Display Outputs | 4x DisplayPort 1.4a | No outputs |

Architecture Differences

The two cards are built on fundamentally different architectures, which explains the vast performance gulf. The L40 is based on the Ada Lovelace architecture (chip AD102), while the PG506-232 is based on the older Ampere architecture (chip GA100). This generational leap is the primary driver of the performance difference.

The L40’s 5 nm process node, manufactured by TSMC, allows for a transistor density of 125.3M per mm², enabling it to pack 76,300 million transistors onto a 609 mm² die. In contrast, the PG506-232 uses a 7 nm process, resulting in a density of just 65.6M per mm². This allows the PG506-232 to fit 54,200 million transistors, but onto a much larger 826 mm² die. The L40’s newer process is a key factor in its ability to achieve much higher clock speeds (2490 MHz boost vs 1440 MHz) and a massive increase in shading units (18176 vs 3584).

The most significant architectural difference is the inclusion of 142 RT cores in the L40, which are entirely absent in the PG506-232. This makes the L40 capable of real-time ray tracing, a feature that the PG506-232 lacks entirely. Furthermore, the L40 supports the latest graphics APIs, including DirectX 12 Ultimate, OpenGL 4.6, and Vulkan 1.4, while the PG506-232 has no API support listed. This confirms the L40 is a true hybrid card capable of both compute and graphics workloads, whereas the PG506-232 is a pure compute accelerator. The memory subsystems also differ completely: the L40 uses GDDR6 on a 384-bit bus, while the PG506-232 uses HBM2 on a much wider 3072-bit bus, a design choice that gives the older card a bandwidth advantage but limits its capacity.

The Verdict

The data presents a straightforward verdict for most users: the NVIDIA L40 is the superior product. It is 47% faster in the OpenCL benchmark, has double the memory capacity (48 GB vs 24 GB), and includes a host of modern features like RT cores and display outputs that the PG506-232 simply does not have. For any workload involving rendering, complex simulation, or AI model training that requires substantial memory, the L40 is the only sensible choice between the two.

However, the PG506-232 is not without its merits, though they are more specialized. Its lower TDP of 165 W and smaller power requirements make it a more compelling option for high-density server installations where power efficiency is the primary concern. Its higher memory bandwidth of 933.1 GB/s, despite lower capacity, could also prove beneficial for specific, bandwidth-bound compute tasks. The decision ultimately comes down to whether raw performance and features (L40) or power efficiency and a unique memory profile (PG506-232) are the higher priority. For almost all standard applications, the L40’s overwhelming performance advantage makes it the definitive winner, but for a niche set of efficiency-focused deployments, the PG506-232 still has a role to play.