DatabricksAhmed Bilal, Ivan Zhou, Yash Oza, Gautam Venkatesh, Alice Li, Harish GaurAnnouncement
Claude Fable 5 is now available on Databricks, fully governed through Unity AI Gateway
Summary
Claude Fable 5 is now generally available on Databricks, with rollout across AWS, Azure, and Google Cloud through Unity AI Gateway. The Mythos-class model targets long-running, complex, and ambiguous work, including autonomous enterprise workflows, document question answering, code investigation, and multimodal tasks. In Databricks' OfficeQA Pro benchmark, Fable 5 achieved 57.9% correctness, setting a state of the art; compared with Claude Opus 4.8, it was 20% more accurate and used 12% fewer tool calls, but ran approximately 30% slower and generated 2.5x more output tokens. Unity AI Gateway provides unified API access, fine-grained permissions, Unity Catalog logging, request and tool-call guardrails, and spend controls. Agent Bricks supports domain-specific agents, while Anthropic's policy includes 30-day retention for trust and safety purposes only.
Context
Databricks customers need to run highly autonomous, long-running AI workflows against enterprise data while retaining governance, access control, auditability, safety protections, and visibility into increased model spending.
Approach / What changed
Claude Fable 5 is offered through Unity AI Gateway across Databricks cloud environments, with unified API access, permissions, logging, LLM and tool-call guardrails, spend controls, and cost analytics. Agent Bricks enables domain-specific agents that can deploy as managed Databricks Apps with authentication, access controls, and Lakebase-powered memory.
Takeaways
On the OfficeQA Pro benchmark, Claude Fable 5 reached 57.9% correctness, with 20% higher accuracy and 12% fewer tool calls than Claude Opus 4.8, while running about 30% slower and producing 2.5x more output tokens.
Unity AI Gateway logs requests, responses, and tool-call actions to Unity Catalog or Delta tables, while policies can block operations, restrict them to admins, or require consent for writes.
AI Spend Controls support thresholds by user, use case, workspace, and account, and Cost Analytics breaks spending down by model, provider, workspace, and user.
Source and freshness
- Source
- databricks.com
- Published
- Added to Yomu
- Last updated
Summaries are generated from the original by a language model. Check the original before relying on it.
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