Interfaze Beta
Interfaze Beta merges specialized DNN/CNN models with an LLM to handle deterministic developer tasks like OCR, scraping, classification, structured outputs, and web extraction. It supports 1M tokens input and 32K tokens output. On AI Gateway, pay $1.5 per million input tokens and $3.5 per million output tokens.
import { streamText } from 'ai'
const result = streamText({ model: 'interfaze/interfaze-beta', prompt: 'Why is the sky blue?'})About Interfaze Beta
Interfaze built Interfaze Beta around a routing layer. Each request goes to whichever specialized model fits the task. Small CNN and DNN models handle perception work like OCR and object detection. An LLM handles language reasoning. Custom tools cover web search, a code sandbox, and configurable safety guardrails. The endpoint is a single OpenAI-compatible URL.
The context window is 1M tokens and maximum output is 32K tokens. Interfaze reports 70.7% on OCRBench V2 for the native OCR path and 98 to 99% accuracy on structured output generation. Inputs accepted include text, images, audio, files, and video. Reasoning is available for harder queries.
Task coverage includes OCR and document extraction, object detection driven by natural language prompts, web scraping (with handling for sites that block bots), speech-to-text with speaker diarization, translation across many languages, classification, structured output, text-to-SQL, and multimodal question answering.
Because the underlying mix of CNNs, DNNs, and an LLM stays opaque behind one endpoint, integration looks identical to any other chat-completions model. Send a prompt with optional image, audio, or file attachments and get back a response that matches your requested schema. See for product documentation and https://interfaze.ai/ for the model page.