Fine-tuning LLMs on Chassis

Chassis Team · training, llm, use-case

Use Chassis instances and multi-node clusters to fine-tune open models with prepaid wallet spend and clear $/hr SKUs.

Fine-tuning does not have to mean mystery invoices. On Chassis you pick a GPU SKU, fund the org wallet, and run your training image — then stop when the run completes.

Single node or cluster

Start on one instance for adapters and small datasets. When you need data-parallel training, launch a Chassis cluster: the same image and SKU across nodes with CHASSIS_NODE_RANK and CHASSIS_NODE_COUNT injected for your framework.

Attach a network volume for checkpoints and datasets
Metering draws the wallet while nodes run
Terminate the cluster when the run finishes