Most custom model projects do not fail on the model. They fail on the plumbing around it: choosing hardware, writing a training configuration that actually fits that hardware, checking the dataset before spending anything, and finding out the real cost only when the run ends.

Nistivo is a managed platform I built to take that plumbing away. You describe the model you need. The platform drafts a configuration, validates it against the hardware before quoting, and gives you one fixed price for the whole job. That price is final. There is no hourly meter.

How a run works

  1. Describe the goal. Fine-tune a base model or train from scratch. Six families are supported: language, vision, image generation, speech, embeddings and classification.
  2. Configuration is drafted, then validated. The drafting step proposes architecture and training settings. Server-side validation checks them against real hardware limits: memory fit at the chosen context length, the platform's size ceilings, and a profit floor that keeps the quote honest. A configuration that does not fit is refused before it can be quoted, not after it fails.
  3. One fixed quote. The quote is computed from the validated configuration and locked. The GPU rate inside it is locked for 72 hours.
  4. Training with checkpoints. Checkpoints are saved and verified during the run. If a paid run fails before its first verified checkpoint, it is refunded in full. If it fails after one, it is re-run free from that checkpoint.
  5. Delivery with lineage. The finished model arrives as a versioned download: weights, configuration, checkpoints, and a model card covering what it was trained on, the recipe, intended use and limitations.

The tradeoff, stated plainly

A fixed quote means the job is scoped before it starts. If you want a shell on a GPU and full control of the training loop, a managed platform is the wrong tool, and this is a managed platform by design. What you get in exchange is a known price and a finished model you own outright.

Numbers

Runs use up to 8 GPUs at once, 16 on the Pro plan, across 15 GPU types. New accounts start with $100 in training credit, covering up to 40% of a quote. Pro is $49/mo for 20% off every quote.

It launched today: https://nistivo.com/?utm_source=devto&utm_medium=launch&utm_campaign=launch-2026-11

Happy to answer technical questions about the quoting math, the validation checks, or the checkpoint verification. What would you train first?