
Today, Sakana AI launched Sakana Fugu. It is a multi-agent orchestration system that behaves like one model. You send a request to a single endpoint. Fugu decides how to handle it internally. It solves a task directly when that is enough. It also assembles and coordinates a team of expert models when needed. The complexity of a multi-agent system never reaches your code. TL;DR Fugu delivers a multi-agent system behind one OpenAI-compatible API. Fugu Ultra leads most published coding a
Will Sakana Fugu appear as a listed model on Sakana AI's official website by June 27?
Resolves by Jun 27, 2026
Sakana AI launched Fugu, a multi-agent orchestration system that coordinates multiple language models behind a single API endpoint. Instead of users managing multiple models directly, Fugu learns when to handle tasks itself and when to delegate to specialist models, then combines their outputs into one answer. The system was designed partly as a response to export controls on certain models, allowing it to route around restrictions by swapping different models into its pool. Early community reaction has been skeptical, with critics questioning whether it represents a meaningful advance beyond existing model routing services.

Today, Mistral AI released OCR 4, its latest document-understanding model. This new release adds bounding boxes, block classification, and inline confidence scores alongside extracted text. It supports 170 languages across 10 language groups and runs in a single container for fully self-hosted deployments. OCR 4 also serves as an ingestion component for enterprise search, RAG, and domain-specific retrieval pipelines. TL;DR OCR 4 returns bounding boxes, typed-block labels, and per-word c

Datalab has released lift, a 9B open-weights vision model for structured extraction. You pass it a JSON schema, and it returns a JSON object that matches. The model reads PDFs and images directly, then decodes against your schema. This is Datalab’s first model built purely for extraction. The team already ships open-source OCR tools: chandra, marker, and surya. lift extends that work into schema-driven field extraction. lift scores 90.2% field accuracy on Datalab’s 225-documen

Mistral OCR 4 delivers enterprise document AI with 170-language support, bounding boxes, and self-hosted deployment.
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