Training research expands to twelve commercial offerings
The research adds Modal and Baseten to a twelve-provider comparison for proposed training from scratch. It proposes different candidates for small experiments, enterprise training and supplier-assisted model development.
Candidates by training need
The research proposes Modal and AWS SageMaker AI for a first small independent model. It proposes AWS as the default enterprise bidder and Cerebras for a supplier-assisted model development proposal. These recommendations assess fit, not measured performance or lowest cost.
Modal and Baseten assessments
The research describes Modal’s small-model training example and Baseten’s custom training scripts. It proposes checks for checkpoint recovery, execution limits, regional costs and usable model delivery. Baseten’s suitability for a specific pretraining implementation remains an inference that needs a pilot.
Starting-weight checks
The research distinguishes training with newly initialized weights from further training of existing models. It identifies Tinker, Together Custom Training and Baseten Loops as products whose documented operations do not establish a from-scratch route. It proposes supplier demonstrations of launch configurations to verify starting weights.
Documentation listing
The README now describes twelve providers across managed jobs, GPU clusters and contracted model development. Its research listing includes initialization checks, artifact delivery and proposed content-rewards integration.
Files in this change
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README.md | modified | +1 −1 |
docs/COMMERCIAL_LLM_PRETRAINING_PLATFORMS_RESEARCH.md | modified | +90 −11 |