It makes it easy to interact with a number of different models without changing the shape of my code. Review collected by and hosted on G2.com.

It can occasionally add some overhead to working with the more mainstream model providers. Review collected by and hosted on G2.com.

I like how easy it is to add AI features to an application. The streaming support and simple APIs make development faster and reduce the amount of code needed. Review collected by and hosted on G2.com.

The documentation can take some time to understand, especially when working with more advanced features and integrations. Review collected by and hosted on G2.com.

The interface and workflow make it much easier to work with. Review collected by and hosted on G2.com.

It still have some complex ui and also its free model don't really show its full potential Review collected by and hosted on G2.com.

This allows us to add polished AI features very quickly to our existing web applications. Review collected by and hosted on G2.com.

It makes building the AI interface easier, however it does not remove the difficulty of making the underlying AI accurate, secure and compliant. Review collected by and hosted on G2.com.

it provides the best clean and eco-friendly applications with API working with different models. Review collected by and hosted on G2.com.

it feels like complex problems and difficult to handle and debugging issues. Review collected by and hosted on G2.com.

It have no vendor lock-in and it's agentic features. Review collected by and hosted on G2.com.

Hosting on vercel costs too much like 20 dollars per month. Review collected by and hosted on G2.com.

Vercel AI SDK continues to work reliably and integrates smoothly with frameworks like React, Next.js and Node.js. I like how easy it is to set up and how well it fits into modern frontend and full-stack workflows. The developer experience remains consistent and well-documented. Review collected by and hosted on G2.com.

One area of improvement could be broader support for additional frameworks and deployment environments. More advanced examples and use cases in the documentation would also help developers adopt the SDK faster for complex AI-driven applications. Review collected by and hosted on G2.com.

Works with almost AI providers such as Gemini, Mistral etc. Review collected by and hosted on G2.com.

Sometimes, it takes some time for updates to be reflected. Review collected by and hosted on G2.com.

Serverless deployment is easy and can be done with very little effort and time. Review collected by and hosted on G2.com.

There isn’t much I can dislike about Vercel. Review collected by and hosted on G2.com.

I explored the AI SDK by Vercel, a TypeScript toolkit designed for building AI-powered applications and agents across frameworks like React, Next.js, Vue, Svelte, and Node.js. With the recent release of AI SDK 5 Beta, the platform has introduced several architectural and usability improvements.

Here’s my experience:

• Extensive Multi-Provider Support

The SDK efficiently manages connections to a broad spectrum of AI model providers, including OpenAI, Anthropic, Google Generative AI, Mistral, Cohere, Perplexity, and xAI Grok. This abstraction allows developers to interact with a consistent API, regardless of the underlying model provider. The approach reduces the overhead of learning and maintaining multiple vendor-specific SDKs, and it simplifies the process of switching or combining models as requirements evolve.

• Robust Core and UI Libraries

The toolkit is structured with a clear separation between its core and UI libraries. The core library is focused on text generation, structured outputs, tool calls, and agent construction, while the UI library provides framework-agnostic hooks for building chat and generative interfaces. This modularity ensures that developers can use only what they need, and it supports integration with popular frontend frameworks such as React, Next.js, Vue, Svelte, and Node.js.

• Significant Architectural Improvements in v5 Beta

Version 5 Beta introduces a redesigned architecture, most notably through the new `LanguageModelV2` interface. This change enables support for richer outputs—such as text, images, reasoning, and sources—organized as ordered content parts. The new design enhances type safety and extensibility, making it easier to adopt new model capabilities without requiring changes to the SDK’s core logic.

• Advanced Message System and Agentic Controls

The message system has been overhauled to distinguish between `UIMessage` (used for UI state and history) and `ModelMessage` (used for LLM input). This separation clarifies the flow of data and prevents accidental loss of information. Additionally, the introduction of agentic control primitives like `prepareStep` and `stopWhen` gives developers granular control over agent behavior, tool selection, and step management, supporting more sophisticated conversational and agentic use cases.

• Flexible Streaming and Integration Patterns

The adoption of Server-Sent Events (SSE) as a standard protocol for streaming output enhances compatibility across browsers and simplifies debugging. The new transport-based configuration for the `useChat` hook allows for flexible backend integration and improved state management, accommodating a wide range of deployment scenarios. The SDK also offers a suite of starter kits and templates, which accelerates the setup process for different frameworks and application types. Review collected by and hosted on G2.com.

• The learning curve can be significant, especially with the introduction of new concepts in v5 Beta such as message type separation and agentic controls. Adapting existing projects may require careful migration and understanding of the new architecture.

• As the v5 Beta is still under active development, APIs may change and some instability or breaking changes can be expected. This requires pinning versions and extra caution for production use. Review collected by and hosted on G2.com.