Together AI, read from an operations desk

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Together AI launches Post-Training for custom open-model tuning

Together AI has launched Together Post-Training, a service for building custom models from open-weight LLMs using SFT or reinforcement learning. Customers write the training loop on dedicated GPUs while Together runs the infrastructure. An introductory price of $9 per B200 GPU-hour applies for the first eight weeks.

What changes for operators — For a 10-200 person B2B company, this is relevant only if one narrow, high-volume task, such as ranking leads or scoring candidates, is costing too much on a closed model. Jack & Jill's case in the source is that shape: an open model matched a closed model in offline tests and is cheaper to serve. Billing is per GPU-minute, so budget an experiment before you start. Without ML staff, you would lean on Together's forward-deployed engineers, which the source offers as a partner option.

Together AI ships a $17 recipe for custom support-ticket classifiers

For a support team fielding a few hundred tickets a day, this is a concrete blueprint for a first-line triage bot: feed in the customer message plus your existing intent list, get back a single label in under a token's worth of output, and route accordingly. The training cost (~$17) and time (~25 minutes) make it cheap enough to iterate on your own historical tickets rather than rely on a general-purpose LLM call for every classification, and the fixed temperature=0, max_tokens=8 setup makes outputs predictable enough to feed directly into a routing rule or CRM webhook without a human review step for high-confidence cases.