The L40S is a datacenter card that sits between two worlds: it has enough memory for serious inference and the ray-tracing hardware of a graphics card. That makes it a good fit for teams whose week includes both model serving and rendering. Finding an L40S cloud Europe machine on Cloudj means selecting the L40S in the console and filtering the live list of hosts by European country codes. This guide covers which workloads justify the card, how to search the EU, and how it compares with the A100 and the RTX 6000 Ada.
Why teams pick the L40S
The L40S is a 48 GB class GPU of the Ada Lovelace generation. In plain terms:
- 48 GB of memory holds a quantized 30B to 70B class language model, depending on quantization and context, or a mid-sized model at higher precision with room for many concurrent requests.
- Ray-tracing and graphics hardware means renderers such as Blender Cycles with OptiX can use it, unlike compute-only datacenter cards.
- Video encode and decode engines help with transcoding pipelines.
- Datacenter form factor, built for running in servers.
The result is a card that does not need to sit idle when your inference load drops: the same machine can render overnight.
Typical mixed workloads
| Workload | Why the L40S fits |
|---|---|
| Serving a mid-sized LLM for a European product | 48 GB leaves room for KV cache and concurrent users |
| Retrieval pipelines: embeddings plus generation | Embeddings and a generator model fit on one card; see RAG embeddings on a GPU in Europe |
| Product visualisation and architectural renders | RT hardware for Cycles or other GPU renderers; see Blender rendering on a GPU in Europe |
| Image and video generation at high resolution | Room for larger models and batches |
Rendering on Cloudj GPUs is headless: there is no remote desktop. You upload a .blend file and run blender -b scene.blend -E CYCLES -f 1 -- --cycles-device OPTIX, then download the frames. The Blender command line documentation lists the options.
How to search for an L40S in Europe
- Check your account level. The L40S is a datacenter GPU, so it needs a higher level than a new account has. If the console says "This GPU class is not available at your account level", contact Cloudj support from the console.
- Open the deploy page with the L40S preselected.
- Enter European codes in the Country field. A good start is
DE, NL, FR, GB; add more EU codes if you need more choice. Remember the UK isGB. - Read each result: country, reliability, max duration, download speed, bandwidth price per TB and the Datacenter badge.
- If nothing is listed, widen the code list, try later, or consider the alternatives below. Stock changes during the day.
The GPU cloud Europe guide explains when to add each European code. If your reason for staying in Europe is data location, keep only codes you accept and check your own legal obligations; the filter itself makes no compliance claim.
L40S vs A100 vs RTX 6000 Ada
All three appear in the console and all three need a higher account level. A short comparison in general terms:
| L40S | A100 PCIe | RTX 6000 Ada | |
|---|---|---|---|
| VRAM (as listed) | 48 GB class | 40 GB version | 48 GB |
| Generation | Ada Lovelace | Ampere | Ada Lovelace |
| Rendering with RT hardware | Yes | No RT cores | Yes |
| Strong at | Mixed inference and graphics | Training and FP64-heavy compute | Workstation-class inference and rendering |
| Form factor | Datacenter | Datacenter | Workstation |
The A100 PCIe remains a solid training card with HBM memory, but it cannot use RT hardware for rendering. The RTX 6000 Ada is close to the L40S in memory and generation and is often a direct substitute when no L40S is listed. For a fuller comparison, read L40S vs A100 vs RTX 6000 Ada. Live "from" prices for each are on their model pages and on GPU cloud.
A practical rule: if your week is mostly training, look at the A100 first; if it mixes inference and rendering, search the L40S and the RTX 6000 Ada together.
Setting up a mixed machine
A single L40S machine can run your inference server by day and render jobs overnight. Keep them apart:
ssh -p PORT root@HOST
nvidia-smi
tmux new -s infer
tmux new -s renderStop the inference server before a heavy render, or the two will compete for memory. Choose disk size at deploy for both model weights and scene assets, because it cannot be resized later. Copy finished frames and outputs off the machine regularly; the instance and disk are removed at the "available until" date, and hosts have no hardware SLA.
When the L40S is not the right rent
- If your model fits in 24 or 32 GB, a consumer card such as an RTX 4090 or RTX 5090 may do the job at the starting account level.
- If you need very large models on one card, look at H100 or H200 class GPUs.
- If you need a guaranteed machine in one European country every day, a live list of independent hosts is the wrong tool.
FAQ
Can I render with Blender on an L40S?
Yes, headless from the command line. There is no graphical desktop on GPU instances.
Why can't I select the L40S?
It is a datacenter GPU and needs a higher account level. Contact Cloudj support from the console.
Is an L40S listed in Germany right now?
Search with DE and the L40S selected; if a machine is listed, you can deploy it. Stock changes during the day.
Is the RTX 6000 Ada a good substitute?
Often, for inference and rendering. Compare the model pages and test your workload.
Next step
Open the L40S deploy page, enter DE, NL, FR, GB and see what is listed. If nothing fits, repeat the search with the RTX 6000 Ada.