How Databricks rolls out frontier models to 12,000 employees on Day 1

Summary

Databricks provides 12,000 employees Day 1 access to new frontier models through a pipeline using Unity Gateway for governance, cost management, and observability. New models are immediately made available on an experimental basis with per-user budgets to control costs and mitigate risk from models that may not be on the efficiency frontier. Budgets include monthly maximum, daily runaway limit, quality frontier budget, and experimental budget, with configurations pushed via Unity Gateway CLI running on employee laptops. After three days, Databricks evaluates models using benchmark data, user-reported quality, and cost tracking via OpenTelemetry traces to decide whether to promote the model. Opus 5.5 was promoted as higher quality and lower cost than predecessors, while GPT-6 Sol was included in the smart router due to its cost advantage over GPT-5.6 Sol.

Takeaways

1. 1

   New models are released experimentally with per-user budgets to control costs and limit risk from models that may not be on the efficiency frontier.

2. 2

   Databricks stratifies sessions by complexity (single/multi-turn, file edits) and reweights distributions to fairly compare model costs per session.

3. 3

   Opus 5.5 was 29% cheaper per session than Opus 4.8 with higher quality, while GPT-6 Sol had a 48% cost reduction but did not replace the default model.

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