Ling 3.1 Flash 1019 is InclusionAI's upgraded Ling 3.1 Flash, a hybrid reasoning mixture-of-experts model with 560B total parameters, 25B activated parameters and a 1M-token context window. Further post-training improves reasoning and real-world agentic performance.
Ling 3.0 Flash Sante is Inclusion AI's health and medicine enhanced 124B-parameter mixture-of-experts model with approximately 5.1B active parameters per token. It is designed for medical knowledge reasoning, clinical safety, evidence-based retrieval, and long-horizon medical tasks while retaining general reasoning, coding, and agentic capabilities.
Ling 3.0 Flash VL is Inclusion AI's 124B-parameter mixture-of-experts model with approximately 5.1B active parameters per token. It builds on Ling 3.0 Flash with native visual perception and advanced visual-agent capabilities while retaining strong language, reasoning, coding, and agentic performance.
Ling 3.0 Flash Fin is a finance-enhanced version of Inclusion AI's Ling 3.0 Flash, a 124B-parameter mixture-of-experts model with approximately 5.1B active parameters. It is optimized for complex, multi-step investment workflows and long-horizon planning while retaining general reasoning, coding, and mathematics capabilities.
Ling 3.0 Flash Fin is a finance-enhanced version of Inclusion AI's Ling 3.0 Flash, a 124B-parameter mixture-of-experts model with approximately 5.1B active parameters. It is optimized for complex, multi-step investment workflows and long-horizon planning while retaining general reasoning, coding, and mathematics capabilities.
Ling 3.0 Tiny is Inclusion AI's 7.9B-parameter mixture-of-experts model with 1.3B active parameters per token, designed for responsive agents, instruction following, and multi-turn conversations.
Ling 3.0 Flash is Inclusion AI's 124B-parameter mixture-of-experts model with approximately 5.1B active parameters per token, designed for token-efficient, production-scale agentic inference.
Ling 3.0 Flash is Inclusion AI's 124B-parameter mixture-of-experts model with approximately 5.1B active parameters per token, designed for token-efficient, production-scale agentic inference.
Ring 1T 2.5 is a 1T-parameter-scale thinking model with 63B active parameters, built for real-world agent workflows that require both strong capability and operational efficiency.
Ring Flash 2.0 is an instant (instruct) model from inclusionAI with 104B total parameters and 7.4B active parameters, designed for real-world agents that require fast responses, strong execution, and high token efficiency.
Ling Flash 2.0 is an instant (instruct) model from inclusionAI with 104B total parameters and 7.4B active parameters, designed for real-world agents that require fast responses, strong execution, and high token efficiency.
Ming Image 0.1 Design, Novita's text-to-image image generation model.
Ling 2.6 Flash is InclusionAI's 104B-parameter sparse MoE instruction model with 7.4B active parameters, optimized for fast, token-efficient agent workflows, tool use, planning, and software-engineering tasks.
Ring 2.6 1T is InclusionAI's trillion-parameter instruction model for high-capability reasoning, coding, mathematics, tool use, and long-horizon agent workflows.
Ling 2.6 1T is an instant (instruct) model from inclusionAI and the company's trillion-parameter flagship, designed for real-world agents that require fast execution and high efficiency at scale.
Ling 3.1 Flash is InclusionAI's hybrid reasoning language model with 560B total parameters and 25B activated parameters.
Ling 3.1 Flash is InclusionAI's hybrid reasoning language model with 560B total parameters and 25B activated parameters.