Releasesby GlyphModal 1.6.3
This release includes a new Image Builder version, 2026.10. After upgrading your SDK, opt into the new Image Builder in your Workspace or Environment settings. We recommend using the latest version for security updates and performance enhancements: The new version includes updates to base Debian images, Python versions, and the Modal dependencies that are...
Also shipped Oct 27, 2026Modal in October 2026 →
OpenAI GPT-6.1 Terra is now available on Unity Gateway
Databricks now supports the OpenAI GPT-6.1 Terra model via Foundation Model APIs on Unity Gateway.
Editing files in Unity Catalog volumes is now generally available
Users can now edit files stored in Unity Catalog volumes directly within the Databricks workspace file editor, eliminating the need for manual downloads and uploads.
Released pg\_pinecone
The pg_pinecone extension is now available, enabling native vector search within PostgreSQL. It allows users to perform vector searches using the local engine or offload indexing to Pinecone for larger datasets.
[Launched] Generally Available: Cost management and tagging for Claude models in Microsoft Foundry
Microsoft Foundry now provides integrated cost management and tagging for Claude models within Azure Cost Management. This update ensures Claude usage is tracked under the specific Foundry resource rather than as general SaaS spend.
Gemini Robotics ER 2 (Preview)
Gemini Robotics ER 2 is now available in preview. This vision-language model is designed for robotics applications, supporting spatial reasoning, agentic code execution, and task orchestration.
xAI's Grok 4.7 is generally available
xAI's Grok 4.7 model is now generally available for production use on global and US multi-region endpoints.
More from ModalEvery Modal release →
Modal 1.6.2
- The new metrics observability surface provides a flexible query interface for fetching detailed time-resolved data about performance and resource consumption: Use the new modal function metrics / modal server metrics CLIs to export metrics to JSON or CSV. Use methods in the new Function.metrics / Server.metrics namespaces to operate on metrics in code.
Modal 1.6.1
- We've added CLI commands for observability over Modal Endpoints: modal endpoint info displays basic metadata. modal endpoint stats reports aggregate performance metrics. modal endpoint logs fetches or streams logs.
Modal 1.6.0
Sandboxes now use our next-generation backend, affording substantially higher creation rates and concurrency limits for CPU Sandboxes. No code changes are required, but there are some semantic differences to be aware of: The modal.Sandbox.create() method now blocks until the Sandbox is scheduled instead of returning immediately.
Modal 1.5.5
- We've added a modal.Sandbox.logs API, allowing you to fetch() logs from a specific date/time range or to tail() the most recent logs. Note that only logs from the entrypoint process of a Sandbox are currently stored, and streaming logs via this interface is not currently supported.
Modal 1.5.4
With this release, it's now possible to opt into a more performant Sandbox backend, which affords substantially higher creation rates and concurrency. Set MODAL_SANDBOX_V2=1 as an environment variable and your Sandboxes will use this new system without any code changes. This will become the default behavior in version 1.6.0 of the Python SDK.
Modal 1.5.3
- We've added new APIs for programmatically retrieving logs on several object types: Function, Server, and FunctionCall. Each object exposes three different methods, allowing you to stream() logs as they are generated, fetch() logs from a specific date/time range, or tail() the most recent logs.
Modal 1.5.2
- We've added new interfaces for programmatic management of workspace settings: Use the modal.Workspace.settings.list() method or modal workspace settings list CLI to see current workspace-level settings. Use the modal.Workspace.settings.set() method or modal workspace settings set CLI to configure new values.
Modal 1.5.1
This release includes several major new features, including the debut of a new serverless compute primitive for low-latency HTTP applications (@app.server()) and a new CLI for deploying production-ready LLM inference endpoints with minimal configuration (modal endpoint).