NVIDIA L40S vs NVIDIA Tesla V100 SXM2 32 GB Comparison

The NVIDIA L40S and the NVIDIA Tesla V100 SXM2 32 GB represent two distinct eras of NVIDIA's data center GPU design, and the benchmark data shows a decisive generational shift in favor of the L40S. Across the two head-to-head benchmark tests available, the L40S wins both, with an average benchmark score of 295,763 compared to the V100's 137,731. The L40S is the clear choice for any workload requiring maximum compute throughput, modern feature support, or higher memory capacity. The V100 SXM2, while still a capable compute card that sits in the 96th percentile of all GPUs, is best suited for legacy deployments or specific HPC tasks where its HBM2 memory bandwidth and 640 Tensor Cores are still relevant. For any new purchase or upgrade path, the data points exclusively to the L40S.

The Verdict

The data unequivocally favors the NVIDIA L40S for virtually all modern compute scenarios. Its average benchmark score is more than double that of the V100 SXM2, and it wins both the OpenCL and Vulkan head-to-head tests by margins of 151.1% and 81.4%, respectively. The L40S also offers 48 GB of GDDR6 memory versus the V100's 32 GB of HBM2, making it the superior option for large model inference and rendering tasks. The V100 SXM2, with its 96th percentile ranking, is not obsolete, but its performance profile is firmly in the past generation. The L40S's 99th percentile ranking places it among the top 1% of all GPUs, while the V100 sits lower. Users with existing infrastructure built around the V100's SXM module format or specific Volta-optimized code may find value in its continued operation, but the L40S is the only logical choice for new deployments or performance-critical upgrades.

FAQ

Q: How much faster is the NVIDIA L40S than the Tesla V100 SXM2 in OpenCL?

A: The L40S scores 330,727 in the Geekbench OpenCL test, while the V100 SXM2 scores 131,696. This represents a 151.1% advantage for the L40S.

Q: Does the Tesla V100 SXM2 win in any benchmark category?

A: No. In the two head-to-head benchmark tests recorded (Geekbench OpenCL and Geekbench Vulkan), the L40S wins both. The V100 SXM2 has zero wins in this comparison.

Q: Which GPU has a higher memory bandwidth?

A: The Tesla V100 SXM2 has a slightly higher memory bandwidth at 898.0 GB/s, compared to the L40S's 864.0 GB/s. However, the L40S has a larger memory pool of 48 GB versus the V100's 32 GB.

Q: What is the architectural generation difference between the two cards?

A: The L40S is based on the Ada Lovelace architecture (chip AD102), while the V100 SXM2 is based on the older Volta architecture (chip GV100). The L40S also uses a 5 nm process node, whereas the V100 uses a 12 nm node.

Q: Are there any differences in API support that matter?

A: Yes. The L40S supports DirectX 12 Ultimate (12_2), while the V100 SXM2 is limited to DirectX 12 (12_1). Both support OpenGL 4.6 and Vulkan 1.4.

Q: Which card has more Tensor Cores?

A: The V100 SXM2 has 640 Tensor Cores, which is more than the L40S's 568 Tensor Cores. However, the L40S's Tensor Cores are from a newer generation and its FP16 performance is listed at 91.61 TFLOPS (1:1), compared to the V100's 31.33 TFLOPS (2:1).

Architecture Differences

The fundamental architectural split between these two GPUs explains their performance gap. The L40S is built on the Ada Lovelace architecture, utilizing the AD102 chip manufactured on a 5 nm process by TSMC. This allows for a transistor count of 76,300 million on a 609 mm² die, achieving a transistor density of 125.3M per mm². In contrast, the V100 SXM2 uses the older Volta architecture with the GV100 chip on a 12 nm process. It houses 21,100 million transistors on a larger 815 mm² die, resulting in a much lower density of 25.9M per mm². This generational leap in manufacturing technology gives the L40S a massive advantage in raw compute resources.

The L40S features 18,176 shading units, 568 TMUs, and 192 ROPs, alongside 142 RT cores and 568 Tensor Cores. The V100 SXM2 has only 5,120 shading units, 320 TMUs, and 128 ROPs, with no RT cores and 640 Tensor Cores. While the V100 has a higher count of Tensor Cores, the L40S's newer Tensor Core design and vastly higher FP32 and FP16 throughput make it far more powerful for AI and graphics work. The L40S also supports a newer feature set, including DirectX 12 Ultimate, which is absent on the Volta-based card. The presence of RT cores in the L40S enables hardware-accelerated ray tracing, a capability the V100 lacks entirely.

Specification Differences

The specification sheets for these two cards diverge significantly across nearly every major category. The L40S operates with a base clock of 1110 MHz and a boost clock of 2520 MHz, while the V100 SXM2 has a higher base clock of 1290 MHz but a much lower boost clock of 1530 MHz. Memory configurations differ substantially: the L40S uses 48 GB of GDDR6 on a 384-bit bus, while the V100 uses 32 GB of HBM2 on a 4096-bit bus. The L40S's memory runs at 2250 MHz (18 Gbps effective), and the V100's at 877 MHz (1754 Mbps effective). Bandwidth is close, with the V100 at 898.0 GB/s slightly edging out the L40S's 864.0 GB/s.

Performance metrics show the L40S's dominance. Its FP32 compute is 91.61 TFLOPS versus the V100's 15.67 TFLOPS. In FP16, the L40S achieves 91.61 TFLOPS (1:1), while the V100 reaches 31.33 TFLOPS (2:1). Pixel rate is 483.8 GPixel/s for the L40S and 195.8 GPixel/s for the V100; texture rate is 1,431.4 GTexel/s versus 489.6 GTexel/s. Power and physical specifications also differ: the L40S is a dual-slot card with a 300 W TDP and a 1x 16-pin power connector, while the V100 is an SXM module with a 250 W TDP and no power connectors. The L40S uses a PCIe 4.0 x16 interface, whereas the V100 uses PCIe 3.0 x16. The L40S also includes display outputs (1x HDMI 2.1, 3x DisplayPort 1.4a), whereas the V100 has no display outputs.

Head-to-Head Benchmarks

The benchmark results are stark and one-sided. In the Geekbench OpenCL test, the L40S scores 330,727 against the V100's 131,696, a delta of 151.1% in favor of the newer card. This is the single largest margin in the comparison and highlights the sheer compute power difference between the Ada Lovelace and Volta architectures. The L40S's advantage is not just incremental; it is a complete overhaul in processing capability.

In the Geekbench Vulkan test, the L40S again wins, scoring 260,799 versus the V100's 143,765. The delta here is 81.4%. While this is a smaller margin than the OpenCL test, it is still a decisive victory. The Vulkan result is notable because the V100 SXM2 supports Vulkan 1.4, the same version as the L40S, yet it still trails significantly. This suggests the performance gap is not due to API feature limitations but rather the underlying hardware's raw compute power and efficiency. Overall, the L40S secures 2 wins out of 2 head-to-head matchups, with the V100 SXM2 failing to secure any.

Where Each One Wins

The L40S is the winner in every measurable benchmark category. Its strengths lie in raw FP32 and FP16 compute, where it delivers 91.61 TFLOPS in both, making it ideal for AI training, inference, and high-fidelity rendering. The inclusion of 142 RT cores gives it a unique advantage in ray-traced workloads, a feature completely absent on the V100. Its 48 GB memory capacity allows for larger datasets and models to reside on a single card, reducing the need for multi-GPU setups. The L40S is therefore the choice for modern data centers, cloud computing, and any workload that demands the highest performance per GPU.

The V100 SXM2's place is more niche. While it loses all benchmark comparisons, it retains some specific advantages. Its memory bandwidth of 898.0 GB/s is slightly higher than the L40S's 864.0 GB/s, which can benefit certain memory-bandwidth-bound HPC applications. Its 640 Tensor Cores, while older, might be supported by legacy software stacks optimized for Volta. Its lower 250 W TDP and SXM module form factor may also appeal to existing SXM-based server infrastructure that cannot accommodate the L40S's dual-slot PCIe design. For users with codebases deeply optimized for Volta's architecture, the V100 SXM2 remains a functional, if not competitive, option. However, for anyone starting fresh or seeking performance, the data shows no scenario where the V100 SXM2 is the better pick.