Vercel

Vercel AI Gateway Logs Add Session Affinity View

Vercel's AI Gateway logs now include a Sessions view that groups requests by session and displays how session affinity routed each request. This update helps track coding agent interactions within sessions.

Why it matters: Understanding session affinity in AI Gateway logs allows developers to better monitor and optimize AI coding tool usage. It provides clearer insights into request routing and session management.

Reader impact: Teams using AI at work may want to compare this against current productivity and review workflows.

DeepSeek V4.1 Flash 1017 Released on AI Gateway with Coding Improvements

DeepSeek V4.1 Flash 1017, a minor update to the previous version, is now available on AI Gateway. It enhances reasoning, coding, agentic tasks, and image understanding capabilities.

Why it matters: These improvements can boost the efficiency and accuracy of AI-assisted coding and related tasks. Access via AI Gateway facilitates integration into developer workflows.

Elorian AI's Glimpse Visual Reasoning Model Now on AI Gateway

Elorian's Glimpse, a visual reasoning AI that processes images and video to track objects and interpret spatial relationships, is now accessible via AI Gateway. The model can zoom into details, revisit video segments, and link actions to their physical outcomes.

Why it matters: This integration enables developers to leverage advanced visual reasoning capabilities in their applications, enhancing AI's understanding of dynamic visual content. It supports more nuanced analysis of motion and spatial context in real time.

Reader impact: Hardware and robotics watchers may want to track whether this becomes a product, benchmark, or deployment signal.

Perplexity Decider V1.2 Models Now on Vercel AI Gateway

Perplexity's Decider V1.2 27B and Decider Flash V1.2 4B multimodal decision models are now available on Vercel's AI Gateway. These models assist in content classification and request routing.

Why it matters: Access to advanced multimodal decision models on a popular AI platform enables developers to integrate sophisticated content classification and routing capabilities more easily. This can improve AI-driven workflows and user experiences.

Vercel Ship 2026 recap

For a decade, Vercel has shaped how the web is built. Now, we’re doing the same for agents. The companies that win the next decade will build on infrastructure designed for agents from the start, and thousands of people gathered across London, Berlin, Ne...

Reader impact: Teams using AI at work may want to compare this against current productivity and review workflows.

Open weight takes 71.5% of tokens and 23% of spend

AI Gateway Production Index — October 2026 Every month, AI Gateway routes tens of trillions of tokens between production applications and AI labs. That traffic gives us a view of what AI usage actu...

Introducing Vercel Drives: persistent storage for agents

Agents often handle complex work that continues across runs. As that work evolves, they may need a new environment with different tools, runtimes, or compute. They should be able to continue working with the same files when they change environments. ...

Python on Vercel Now Generally Available with AI and Workflow Support

Vercel has launched general availability for Python applications, supporting popular frameworks and libraries. The platform offers automatic build configuration, scalable Fluid compute, and Python SDKs for storage, queues, workflows, and AI integration.

Why it matters: This enables developers to deploy Python apps seamlessly on Vercel with built-in support for AI and durable workflows, improving scalability and ease of use. It broadens Vercel's appeal beyond JavaScript, facilitating AI-powered application development.

Muse Spark Open from Meta now on Vercel AI Gateway

Muse Spark Open, an open-weight reasoning model from Meta, is now available on Vercel's AI Gateway. It supports coding and agentic workflows with text and image inputs and a 1M-token context window.

Why it matters: This model enhances AI agents' ability to handle complex coding tasks like multi-file refactoring and debugging. Its large context window allows for better understanding of extensive codebases and related images.