Most capable open-source models make you choose: raw intelligence or token efficiency. Thinking models burn 3–5× more tokens per request. Smaller non-reasoning models cut costs but cap capability. Ling-2.6-1T is built to break that tradeoff. Ling-2.6-1T is a trillion-scale comprehensive flagship model from Ant Group (inclusionAI), designed for immediate task execution. Built on MLA + Hybrid Linear Attention architecture, it achieves a superior intelligence-to-token ratio: strong benchmark performance with minimal output token overhead. On AIME26, it significantly outperforms other non-thinking models. On agent execution benchmarks — SWE-bench Verified, BFCLv4, TAU2-Bench, Claw-Eval — it reaches open-source SOTA. Now exclusively backed by Novita AI as the inference provider. In short: Ling-2.6-1T delivers comprehensive frontier capability for agent workloads — complex reasoning, tool use, multi-step execution, and long-context instruction following — at a fraction of the token cost of thinking models.…