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  1. Story1 reports · 1 facts

    StepFun and ACE Studio launch the StepAudio 3 Music music generation model

    StepFun and ACE Studio jointly released StepAudio 3 Music, a foundational music generation model. This is StepFun's first foundational music generation model, capable of generating complete songs based on prompts and lyrics. The model integrates four workflows: song generation, accompaniment generation, music cover, and vocal-to-song arrangement. ABC-COT plans the musical structure and arrangement before synthesis, and users can rewrite prompts, edit ABC notation, and iterate. At the time of release, a Hugging Face Space demo and API documentation were already available, and the ABC-COT API is coming soon. There are currently no reports of further progress.

    e of generating complete songs based on prompts and lyrics. The model integrates four workflows: song generation, accompaniment generation, music cover, and vocal-to-song arrangement. ABC-COT plans the musical structure and arrangement before synthesis, and users can rewrite prompts, edit ABC notation, and iterate. At the time of release, a Hugging Face Space demo and API documentation were already available, and the ABC-COT API is coming soon. There are currently no reports of further progress.

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  2. Story1 reports · 1 facts

    Bailing releases and open-sources native multimodal model Ling-3.0-flash-VL

    On September 9, 2026, Ant Bailing released and open-sourced Ling-3.0-flash-VL, the first native multimodal large model in the Ling series. Built as an extension of the Ling-3.0-flash MoE architecture, the model has 124B total parameters and 5.5B activated per inference, natively supports image, text, and video inputs, and has a 256K-token context window. According to the company, native multimodal joint training improved the model's score on the Artificial Analysis Intelligence Index v4.1.1 by 4 points over the text-only version, and it introduces a visual feedback loop of observe, act, verify, and correct, used for front-end replication, GUI agents, and medical report interpretation. The model is currently available for free trial on Ling Studio, and the BF16 and FP8 versions have been open-sourced on Hugging Face and ModelScope.

    ontext window. According to the company, native multimodal joint training improved the model's score on the Artificial Analysis Intelligence Index v4.1.1 by 4 points over the text-only version, and it introduces a visual feedback loop of observe, act, verify, and correct, used for front-end replication, GUI agents, and medical report interpretation. The model is currently available for free trial on Ling Studio, and the BF16 and FP8 versions have been open-sourced on Hugging Face and ModelScope.

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Friday

  1. Story1 reports · 1 facts

    Baseten and Base Labs Announce Building Open Infrastructure for Model Safety Evaluation and Monitoring

    On September 16, 2026, Baseten and Base Labs announced a joint effort with Goodfire and Hugging Face to build safety evaluation and monitoring infrastructure for the open-source models they serve, integrating safety research directly into training and inference systems. The work covers three areas: the training phase, where models are made to follow explicit policies, recognize the boundaries of their capabilities, and proactively seek help; the monitoring and intervention phase, which studies inputs, outputs, tool calls, and models' internal states, and connects signals to permissions, isolation, and pre-execution checks; and learning from failures. In terms of division of labor, Base Labs is responsible for developing and publicly releasing the methods, while Baseten integrates them into its deployment infrastructure, offering them as a hosted service and publishing the methods and evidence so that customers and external evaluators can verify them independently. There are currently no further developments.

    On September 16, 2026, Baseten and Base Labs announced a joint effort with Goodfire and Hugging Face to build safety evaluation and monitoring infrastructure for the open-source models they serve, integrating safety research directly into training and inference systems. The work covers three areas: the training phase, where models are made to follow explicit policies, recognize the boundaries of their capabilities, and proactively seek help; the monitoring and intervention phase, which studies i

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