Alibaba Cloud PAI iTAG vs LabelLLM

Alibaba Cloud PAI iTAG is a data-labeling platform for image, text, video, audio and multimodal datasets. Built-in image tasks include classification, object detection, OCR, table recognition and semantic segmentation; official templates also cover image-text explanation, conversation ranking, visual question answering and video OCR. Teams can use official or tenant templates, or create templates for business-specific labeling. A job brings together an OSS-backed dataset and template with labels, subtasks, checks, labelers and reviewers. Manual labeling is free, and selected large-model labeling templates are currently free; OSS storage and data transfer are billed separately. Input data must be in Alibaba Cloud OSS, and the workspace and bucket must be in the same region. Dataset imports require an index file rather than a direct path to a folder of raw files. From August 1, 2026, iTAG 1.0 is allowlist-only and in maintenance mode. Existing customers with prior labeling tasks or datasets can continue using current features. New users seeking AI-powered automatic dataset labeling are directed to Multimodal Data Management. API operations include listing, creating, updating and deleting templates and labeling tasks.

LabelLLM has no write-up on Specifiction yet; its figures are above.