In this article
L40 and L40S require separate hardware records and separately attributed results.
NVIDIA L40 is assessed here as an exact Ada Lovelace board configuration. Its published 48 GB capacity is the starting point for a workload qualification, not a measured serving or rendering result.
Exact model and memory variants
The original L40 has48 GB GDDR6 ECC and 300 W passive server construction. It is distinct from the 350 W L40S, despite similar names and memory capacity.
| Variant | Memory | Published board power | Cooling / format |
|---|---|---|---|
| L40 | 48 GB GDDR6 ECC | 300 W | Passive; Full-height dual-slot PCIe |
Specifications: Official product/support documentation.
LLM backend and memory budget
For48 GB L40, validate the build and weight format with a separate cache budget. Do not copy L40S results or power settings merely because both use Ada.
Passing the architecture requirement does not certify every model, quantization kernel or prebuilt package.
Compatibility evidence: vLLM GPU requirements.
Cycles and batch rendering
Qualify L40 as a graphics server product with a complete scene. Video encoding, rendering and LLM execution are distinct jobs, each requiring its own artifact and output validation.
Blender 5.2 LTS GPU rendering manual.
Integration into a server or workstation
Preserve the L40 suffix-free identity in inventory and the 300 W installation boundary. The passive card needs chassis-provided airflow and a verified server layout. A later L40S replacement is a separate hardware change even when the scene fits48 GB on both.
A concrete qualification scenario
An infrastructure sheet mixes L40 and L40S measurements in one row. Split the devices before rerunning an identical model/context case and reference scene. Keep the actual card identity with every output. If video processing is also relevant, record it as a third independent workload. The corrected artifact matrix prevents a shared48 GB capacity from disguising differences in hardware and execution configuration.
The evidence to retain
Keep an ordinary qualification record with the actual test outputs.
Identify the tested variant, software build and execution mode before entering observations. Leave unavailable measurements explicitly unknown.
The fields below separate published specifications from observed allocation and job completion, so a later operator can repeat the same case.
| Evidence field | What this profile must retain |
|---|---|
| Hardware identity | NVIDIA L40; physical variant and reported device identifier |
| Memory boundary | 48 GB published; observed free memory before and after loading |
| Inference artifact | Exact weights digest, quantization, context and offload configuration |
| Render artifact | Scene digest, renderer version, backend and denoising setting |
| System envelope | Driver, container/build digest, enclosure and cooling configuration |
| Completion evidence | Application exit status, output validity and observed memory failures |
A48 GB result without the exact L40 identity cannot establish whether the 300 W or350 W product configuration was actually tested.
Further reading: RAM and VRAM: which memory matters for an AI server?, A GPU inference benchmark you can trust, NVIDIA and AMD GPU catalogue.