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Ant Group Launches Ling-2.6-1T, a 1T-parameter model focused on task execution

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On-chain news: On April 27, Ant Group’s inclusionAI unveiled Ling-2.6-1T, a 1-trillion-parameter model optimized for task execution. The model employs a "Fast-Thinking" mechanism to enhance efficiency and performance in agent-based workflows. It supports a 262.1K-token context and 32.8K-token output via OpenRouter’s free API. The release aligns with current trends in token listings, as the model is expected to be open-sourced soon.

AIMPACT update, April 27 (UTC+8): According to monitoring by Beating, Ant Group's inclusionAI recently released Ling-2.6-1T, a new trillion-parameter flagship instruction model in the Ling series. Unlike models focused on long-form reasoning, Ling-2.6-1T employs a "Fast-Thinking" mechanism for precise task execution. The official team states it represents a significant upgrade over Ling-1T, with overall intelligence approaching GPT-5.4 in non-reasoning mode, while generating fewer tokens—treating token efficiency as a core metric. This positions it for agent-era execution tasks: code modification, tool invocation, complex instruction following, and high-frequency production environment usage. The OpenRouter page shows that Ling-2.6-1T is currently available via a free API, supporting a 262.1k token context window with a maximum output of 32.8k tokens. The official team has announced that Ling-2.6-1T will soon be open-sourced. (Source: BlockBeats)

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