Vercel, the San Francisco-based company known for its vibe coding platform, has unveiled a new artificial intelligence (AI) model designed to enhance web application development. The announcement made on Thursday revealed that the v0 AI model would be accessible through an application programming interface (API) along with various other formats. This marks Vercel’s first foray into AI model development, focusing specifically on front-end and back-end tasks associated with web applications and ensuring compatibility with OpenAI’s API.
Vercel’s v0 AI Model Can Develop Websites and Web Apps
In a recent post on X, formerly known as Twitter, Vercel’s official handle highlighted the rollout of this innovative AI model. Identified as the underlying technology for the vibe coding platform, the model boasts a strong foundation of website development expertise. It is currently available in a beta format through the company’s API, as an AI software development kit (SDK), or via the AI Playground.
According to Vercel, the AI model, officially called v0-1.0-md, is capable of processing both text and images, ensuring swift response times. It is also compatible with the OpenAI Chat Completions API format, featuring a context window that can accommodate up to 128,000 tokens and allowing for a maximum output context size of 32,000 tokens. Users are granted a limit of 200 messages per day with this model.
The v0 AI model is proficient in framework-aware completions, having undergone testing with Next.js and Vercel’s technology stack. It is equipped to identify and correct bugs, glitches, and other coding issues during the coding generation process, with the ability to implement inline edits when necessary.
Developers with an active Premium or Team subscription along with usage-based billing can access the v0 API in its current beta phase. The pricing structure for utilizing the AI model is set at $3 (approximately Rs. 260) per million input tokens and $15 (around Rs. 1,290) per million output tokens.
Vibe coding is emerging as a preferred method among developers, characterized by the use of natural language to describe coding tasks to AI models, which then execute the coding. This approach enables human operators to adopt a strategy-driven role, focusing on project direction, error-checking, and ensuring the final outcome aligns with their vision.
