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Ant Ling has 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, it has 124B total parameters and 5.5B activated per inference, natively supports image, text, and video inputs, and has a 256K Token context window. The company says 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 for front-end replication, GUI Agent, and medical report interpretation. The model is now available for free trial on Ling Studio, and the BF16 and FP8 versions have been open-sourced on Hugging Face and ModelScope.

and has a 256K Token context window. The company says 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 for front-end replication, GUI Agent, and medical report interpretation. The model is now 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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Mastra released the open-source software factory Mastra Factory Beta, which connects GitHub, Linear and Slack and runs agents in phases according to a configurable kanban board, with each phase settable to manual or automatic. The company says that since the alpha version launched in July, Factory has automated 25-35% of PRs and closed 50-60% of issues, and the project receives more than 100 issues and merges about 200-250 PRs per week. The team also introduced a graph-based wiki knowledge base, AgentController session management and the Signals real-time correction mechanism, and plans to release the knowledge graph as an independent primitive.

Mastra released the open-source software factory Mastra Factory Beta, which connects GitHub, Linear and Slack and runs agents in phases according to a configurable kanban board, with each phase settable to manual or automatic. The company says that since the alpha version launched in July, Factory has automated 25-35% of PRs and closed 50-60% of issues, and the project receives more than 100 issues and merges about 200-250 PRs per week. The team also introduced a graph-based wiki knowledge base,
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