Ling-1T: A Trillion-Parameter Model for Efficient Reasoning

Ling-1T, developed by inclusionAI, is the first flagship non-thinking model in the Ling 2.0 series, boasting 1 trillion total parameters with approximately 50 billion active parameters per token. It is pre-trained on over 20 trillion high-quality, reasoning-dense tokens and supports up to 128K context length. A key differentiator is its Evolutionary Chain-of-Thought (Evo-CoT) process, which significantly enhances reasoning efficiency and depth, allowing it to balance accuracy and performance on complex benchmarks.

Key Capabilities

• Flagship-Level Efficient Reasoning: Consistently demonstrates superior complex reasoning across code generation, software development, competition-level mathematics, professional math, and logical reasoning, outperforming many open-source and closed-source models.
• Aesthetic Understanding & Front-End Generation: Excels in visual reasoning and front-end code generation, combining deep semantic understanding with precise code synthesis, and ranks first among open-source models on ArtifactsBench.
• Emergent Intelligence at Trillion-Scale: Exhibits strong emergent reasoning and transfer capabilities, achieving ~70% tool-call accuracy on BFCL V3 with minimal instruction tuning.
• Advanced Training: Built on the Ling 2.0 architecture for trillion-scale efficiency, utilizing innovations like 1/32 MoE activation ratio, MTP layers, and is the largest FP8-trained foundation model to date.

Good For

• Applications requiring highly efficient and accurate complex reasoning.
• Code generation and software development, particularly for front-end code with aesthetic considerations.
• Mathematical problem-solving at competitive and professional levels.
• Developing general, collaborative human-AI intelligence systems.
• Tasks benefiting from long context understanding and advanced chain-of-thought processing.