L40S vs RTX A6000

The L40S is built on the AD102 architecture (Ada Lovelace, TSMC 4N), while the RTX A6000 uses GA102 (Ampere, Samsung 8nm). The L40S delivers 183 TFLOPS of FP16/BF16 throughput — 2.4× the 77.4 TFLOPS of the RTX A6000. Neither GPU supports FP8 precision.

Memory capacity and bandwidth are the primary constraints for large language model workloads. The L40S provides 48GB of GDDR6 — the same capacity as the RTX A6000, though in GDDR6. Memory bandwidth favors the L40S at 864 GB/s — 1.1× the 768 GB/s of the RTX A6000. The RTX A6000 supports NVLink at 112 GB/s bidirectional, enabling multi-GPU tensor parallelism; the L40S is PCIe-only with no VRAM pooling across cards.

Power consumption shapes rack density and operating cost. The RTX A6000 draws 300W TDP versus 350W for the L40S. On a TFLOPS-per-watt basis, the L40S is the more efficient option at 2.0× the compute density of the RTX A6000, delivering 183 TFLOPS at 350W.

The L40S is best suited for Inference serving, Generative AI, Mixed compute + graphics. The RTX A6000 targets Large model inference, Multi-GPU NVLink setups, Professional rendering + AI. For high-density inference racks where power budget is the constraint, the RTX A6000's 300W envelope allows more cards per rack than the L40S's 350W. For throughput-bound inference, the L40S's higher TFLOPS ceiling gives it an advantage when the model fits in either card's VRAM.