Databricks adds Inkling open-weights model for AI agents and coding
Databricks has integrated the Inkling open-weights model from Thinking Machines Lab via its Unity AI Gateway. This allows enterprises to build and deploy AI agents and coding applications using their own data, benefiting from customizable models, centralized governance, and cost-effective deployment. Inkling is available now on Databricks and can be accessed through the AI Playground or deployed via the Unity AI Gateway.
- →Inkling model available on Databricks platform
- →Model optimized for coding and agentic reasoning
- →Governed deployment via Unity AI Gateway
- →Benefits of open-weights models for enterprises
- →Getting started with Inkling
Features (3) ›
- Inkling model available on Databricks platform
The open-weights Inkling model from Thinking Machines Lab is now accessible through Databricks' Unity AI Gateway. This integration enables enterprises to leverage the model for building AI agents and coding applications on their proprietary data.
- Model optimized for coding and agentic reasoning
Inkling is designed to excel in coding workflows and agentic reasoning, and supports multimodal inputs. It offers flexibility for customization on enterprise data to achieve higher quality, lower cost, and reduced latency for specialized tasks.
- Governed deployment via Unity AI Gateway
Inkling can be governed through Unity AI Gateway, providing centralized security, permissions, cost controls, and observability. This ensures data remains within a controlled environment and allows integration with coding agents like Cursor and OpenCode.
Notes (2) ›
- Benefits of open-weights models for enterprises
Open-weights models like Inkling can be fine-tuned on proprietary data for improved accuracy, offer greater control over deployments, provide flexibility in model choice, and enable cost optimization compared to per-token API pricing.
- Getting started with Inkling
Users can try Inkling in the AI Playground, deploy it through Unity AI Gateway for governed endpoints, build agents using Agent Bricks, or refer to the Foundation Model API documentation. Support for querying in SQL is expected soon.
https://www.databricks.com/blog/inkling-thinking-machines-lab-now-databricks
Related releases
- Databricks Introduces Real-Time Mode for Spark Structured Streaming Databricks Blog ·
- Databricks: Data-Native AI Agents Offer Integrated Governance and Security Databricks Blog ·
- Databricks applies GenAI to improve higher education student advising Databricks Blog ·
- Databricks SDK Go v0.159.0: New fields, one breaking change Databricks Go SDK Releases ·
- Databricks Genie One launches native mobile apps for iOS and Android Databricks Blog ·
- Guide to Python App Hosting for Data and AI Workloads Databricks Blog ·