Upstage AI Integrations

Solar Pro 2 is Upstage’s latest frontier‑scale large language model, designed to power complex tasks and agent‑like workflows across domains such as finance, healthcare, and legal. Packaged in a compact 31 billion‑parameter architecture, it delivers top‑tier multilingual performance, especially in Korean, where it outperforms much larger models on benchmarks like Ko‑MMLU, Hae‑Rae, and Ko‑IFEval, while also excelling in English and Japanese. Beyond superior language understanding and generation, Solar Pro 2 offers next‑level intelligence through an advanced Reasoning Mode that significantly boosts multi‑step task accuracy on challenges ranging from general reasoning (MMLU, MMLU‑Pro, HumanEval) to complex mathematics (Math500, AIME) and software engineering (SWE‑Bench Agentless), achieving problem‑solving efficiency comparable to or exceeding that of models twice its size. Enhanced tool‑use capabilities enable the model to interact seamlessly with external APIs and data sources.

Solar Mini is a pre‑trained large language model that delivers GPT‑3.5‑comparable responses with 2.5× faster inference while staying under 30 billion parameters. It achieved first place on the Hugging Face Open LLM Leaderboard in December 2023 by combining a 32‑layer Llama 2 architecture, initialized with high‑quality Mistral 7B weights, with an innovative “depth up‑scaling” (DUS) approach that deepens the model efficiently without adding complex modules. After DUS, continued pretraining restores and enhances performance, and instruction tuning in a QA format, especially for Korean, refines its ability to follow user prompts, while alignment tuning ensures its outputs meet human or advanced AI preferences. Solar Mini outperforms competitors such as Llama 2, Mistral 7B, Ko‑Alpaca, and KULLM across a variety of benchmarks, proving that compact size need not sacrifice capability.

Upstage Document Parse transforms complex documents, PDFs, scanned images, spreadsheets, and slides containing text, tables, charts, and even handwriting, into structured, machine‑readable HTML or Markdown with enterprise‑grade speed and accuracy. Leveraging advanced layout understanding, it recognizes complex tables, charts, and element coordinates, processes pages at an average of 0.6 seconds each (100 pages in under a minute, 5–10× faster than competitors), and delivers over 5% higher layout and table recognition accuracy (TEDS: 93.48, TEDS‑S: 94.16). Easily invoked via a REST API or deployed on‑premises or through marketplaces like AWS, it fits seamlessly into existing pipelines using simple client libraries. Use cases span retrieval‑augmented enterprise search, AI‑powered document summarization, legal and compliance digitization, and financial report processing, preserving intricate layouts and ensuring clean, searchable outputs for downstream LLM workflows.

Syn is a next‑generation Japanese large language model co‑developed by Upstage and Karakuri, featuring under 14 billion parameters and optimized for enterprise use in finance, manufacturing, legal, and healthcare. It delivers top‑tier benchmark performance on the Weights & Biases Nejumi Leaderboard, achieving industry‑leading scores for accuracy and alignment, while maintaining cost efficiency through a lightweight architecture derived from Solar Mini. Syn excels in Japanese “truthfulness” and safety, understanding nuanced expressions and industry‑specific terminology, and offers flexible fine‑tuning to integrate proprietary data and domain knowledge. Built for scalable deployment, it supports on‑premises, AWS Marketplace, and cloud environments, with security and compliance safeguards tailored to enterprise requirements. Leveraging AWS Trainium, Syn reduces training costs by approximately 50 percent compared to traditional GPU setups, enabling rapid customization of use cases.