Interfaze introduces a hybrid architecture that fuses task‑specific CNN/DNN encoders with a transformer backbone, targeting deterministic workloads such as OCR, object detection, and structured output. In head‑to‑head testing across nine benchmarks, it outperformed Gemini‑3‑Flash, Claude‑Sonnet‑4.6, GPT‑5.4‑Mini and Grok‑4.3, leading most scores including OCRBench V2.

Pricing matches flash‑tier competitors at $1.50 per million input tokens and $3.50 per million output tokens, while delivering up to 100× higher accuracy on specialized tasks. The model handles text, images, audio, and files in a 1M‑token context window, and can return bounding boxes, confidence scores, and multilingual translations in a single request.

Developers can access Interfaze via a standard Chat Completions API, allowing drop‑in integration with existing OpenAI‑compatible SDKs. Early adopters report dramatic speed gains in speech‑to‑text, transcribing 209 seconds of audio per compute second, and seamless OCR of dense, multi‑column PDFs with graphic extraction. The service positions itself as a cost‑effective alternative for high‑volume deterministic pipelines.