Inkling Model Lands on Databricks

Thinking Machines Lab's Inkling model is now accessible on Databricks via Unity AI Gateway, enhancing enterprise AI development for coding and agentic tasks.

Jul 15 at 7:17 PM6 min read

Inkling model now available on the Databricks platform.

Visual TL;DR. Inkling Model integrated Now on Databricks. Now on Databricks via Unity AI Gateway. Unity AI Gateway enables Enterprise Control. Now on Databricks allows Flexible AI Dev. Flexible AI Dev supports Fine-tune Inkling. Enterprise Control leads to Accelerate AI. Fine-tune Inkling contributes to Accelerate AI.

Inkling Model: open-weights AI model from Thinking Machines Lab for coding and agentic tasks
Now on Databricks: accessible via Unity AI Gateway for enterprise AI development
Unity AI Gateway: centralized environment for managing security, permissions, costs, and observability
Enterprise Control: data remains within the enterprise's controlled environment for privacy and security
Flexible AI Dev: leverage Inkling for coding workflows and multimodal inputs on proprietary data
Fine-tune Inkling: open-weights model allows specialization on proprietary datasets for high accuracy
Accelerate AI: enhances enterprise AI development for coding and agentic tasks

Visual TL;DRQuickExplainDeeper

Thinking Machines Lab's Inkling, an open-weights AI model, has arrived on the Databricks platform. This integration allows enterprises to leverage the model for coding and agentic reasoning tasks directly on their own data.

The Inkling model Databricks integration positions the model within Databricks' Unity AI Gateway. This provides a centralized environment for managing security, permissions, cost controls, and observability for AI deployments.

Inkling is designed to excel at coding workflows and supports multimodal inputs, making it versatile for various applications. Its availability as an open-weights model means it can be fine-tuned on proprietary datasets for specialized, high-accuracy tasks.

Enterprise Control and Flexibility

Databricks emphasizes the governance benefits, stating that data remains within the enterprise's controlled environment. This addresses key concerns around data privacy and security when deploying advanced AI models.

The platform offers flexibility, allowing teams to choose and customize models. This avoids vendor lock-in and enables selection of the best model for specific workloads, whether open or proprietary.

Cost optimization is another advantage, as open-weights models bypass per-token API pricing common with proprietary alternatives. This allows for more predictable and scalable inference spend.

Accelerating Development

Developers can connect Inkling to coding agents like Cursor and OpenCode through the Unity AI Gateway. This aims to streamline the development of AI-powered coding assistants and applications.

Databricks provides multiple avenues for users to get started, including an AI Playground for experimentation and direct deployment through the Unity AI Gateway. Integration with Agent Bricks is also supported for building complex, data-driven agents.

The Inkling model is now live on Databricks, with further support for SQL querying anticipated soon.

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#Databricks #Inkling #Thinking Machines Lab #AI Models #Open Source AI #AI Development #Unity AI Gateway #Large Language Models