CoreWeave Model Distillation
Managed post-training workflow that trains a smaller open-weight model on examples from a production task with Serverless supervised fine-tuning, scores it against the model already in use on held-out traffic, and moves traffic over gradually; in preview inside CoreWeave Forge.
Find alternatives to CoreWeave Model Distillation
What it does
- Model training
Sources
- Pricing
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Official documentation · 18 Oct 2026
"Model Distillation isn't billed separately. You pay standard rates for the services the workflow uses, including Serverless SFT at $2.70 per GPU-hour"; no charging model is stated for the preview itself.
- Description
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Official documentation · 18 Oct 2026
"Train a smaller model for the task you already run in production. Turn real examples into training data, compare candidates against your current model, and move traffic when the results meet your quality bar."; "Train a smaller open-weight model on examples from your task using Serverless supervised fine-tuning (SFT)."
- What it does
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Official documentation · 18 Oct 2026
"CoreWeave Model Distillation is a managed post-training capability available through CoreWeave Forge. It uses supervised fine-tuning to train a smaller open-weight model".
- Sold within
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Official documentation · 18 Oct 2026
"Model Distillation is part of CoreWeave Forge"; "Model Distillation isn't billed separately."
- Name
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Official documentation · 18 Oct 2026
"CoreWeave Model Distillation".
- URL
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Official documentation · 18 Oct 2026
The product's own page, titled "CoreWeave Model Distillation" and linked from the Forge menu as "Model Distillation Preview".
- Deployment
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Official documentation · 18 Oct 2026
"Deploy through CoreWeave Inference and set the share of requests each model receives." CoreWeave manages the training infrastructure.
- Intended for
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Official documentation · 18 Oct 2026
For teams that already run a frontier model on a production task and want to test "whether a smaller, specialized model can meet your quality requirements".
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