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EnglishWhat Is Velda and What Does It Do?
Updated
Velda is a serverless GPU cloud for AI workloads. It lets you run training, inference, serving, and data pipeline jobs by prefixing a command with vrun, without building container images or managing a cluster. You pay for compute only while jobs run, not during development or between workloads. It fits individuals and small teams through Velda Cloud, and larger organizations through self-hosted or dedicated enterprise infrastructure.
How Velda works
The core mechanism is the vrun prefix. Instead of packaging your code into an image and submitting it through a cluster scheduler, you take a command you would run locally and prefix it:
vrun -P h200-1 python train.py
The -P h200-1 selects the compute profile (here, an H200 GPU), and the rest is your normal command. According to the site, this means:
- No image builds
- No manifests
- No dependency drift
- Your local development experience, with access to remote compute
The job runs from your cloud or cluster, and the compute resource is provisioned when the job runs rather than held during coding.
What you can run
Velda positions itself around AI workloads broadly:
| Workload | Example use |
|---|---|
| Training | vrun -P h200-1 python train.py |
| Inference / serving | Run serving jobs with the same prefix pattern |
| Data pipelines | Distributed processing instead of single-machine multiprocessing |
| Robotics & physical AI | Listed as a product area on the site |
The site also lists a "Slurm Alternative" page, indicating Velda targets teams currently using cluster schedulers like Slurm.
Development environment
Velda provides a browser-based VS Code option, or you can connect with your preferred IDE. Prebuilt templates are available to start quickly — the site shows a PyTorch ML template with base dependencies such as torch==1.12.1, pandas==1.4.2, and matplotlib==3.5.2. You can then tailor the environment to your workflow.
The cost model
The stated billing principle is: pay only for compute when your jobs run. The site contrasts this with a traditional dev machine, where compute sits idle during coding and breaks, and with Kubernetes/cluster setups that add management overhead. Velda's claim is that compute is utilized during heavy workloads and not underutilized between them.
Velda Cloud is described as including a free monthly credit. Specific pricing figures are not given in the available page content — check velda.io/pricing for current numbers.
Deployment options
- Velda Cloud — managed cloud with instant VS Code and GPU access, plus free monthly credit. Aimed at individuals and small teams.
- Enterprise — self-hosted or dedicated infrastructure with premium support, for organizations of any size.
When Velda is a good fit
Choose Velda if you want to run GPU jobs from your existing dev environment without writing Dockerfiles or managing cluster infrastructure, and if your workloads are bursty enough that paying only during execution matters. Consider the enterprise option if you need self-hosting or dedicated hardware. If you already have a well-tuned Slurm or Kubernetes setup and don't mind its overhead, the comparison pages on the site are the place to check whether the tradeoffs favor switching.