Qwen

A high-quality embedding model from Qwen for converting text into dense vector representations. Supports semantic search, clustering, and retrieval-augmented generation (RAG), with strong multilingual coverage and robust out-of-domain generalization.

A multimodal model from Qwen for text, image, and video understanding with fast response times. It supports a 1M-token context window, a 131K-token maximum output, tool calling, structured output, prefix continuation, and context caching. It is suitable for long documents, codebases, complex conversations, coding assistance, agent workflows, and visual analysis.

A compact 3.8-billion-parameter language model balancing performance and efficiency. Well-suited for resource-constrained deployments, edge inference, and cost-sensitive applications. Offers solid instruction following, reasoning, and multilingual capabilities relative to its size. Good fit for lightweight chatbots, text summarization, and classification tasks.