AI Coding Live News

On November 5 Ant Group’s Ant Ling (@AntLingAGI) launched Ling-3.2-flash: a 560B-total / 25B-active native multimodal MoE with a 1M context window and native image, text and video input. The official changelog targets complex visual understanding, multimodal long-horizon agents, 3D understanding and interaction, and medical multimodal work; APIs are OpenAI- and Anthropic-compatible and free for the first two weeks. The launch post cites vendor evals versus Claude Opus 5 (max): OmniDocBench1.5 92.21 vs 90.56, ZEROBench(Sub) 43.71 vs 39.52, Vision2Web 85.86 vs 80.20. DesignArena placed it about #10 on Image-to-Frontend with Elo 1238.

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On Oct 27 Ant Ling (inclusionAI) open-sourced Ling-3.1-flash-1019, a further post-trained upgrade of the early-October Ling-3.1-flash: 560B total parameters, 25B active per token, a 1M-token context and an MIT license. Ant says it scores 44 on the Artificial Analysis Intelligence Index v4.3.2 (up from 41), with clear gains on agent tasks such as AA-Briefcase and AutomationBench-AA. It also released Ling-3.1-flash-base, an open foundation checkpoint for further training.

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On October 19 Ant Ling (inclusionAI) open-sourced five Ming-3.0 models under MIT, spanning speech synthesis (tts-0.5B; tts-tiny, 7.9B total/1.3B active), audio understanding (audio-flash, 126B/6.5B active; audio-tiny, 9.3B/2.7B active) and speech recognition (asr-tiny, 8.6B/2B active). Per the vendor, tts-0.5B ranks #1 among open-weight models on Artificial Analysis Controlled Voice at 1069 Elo and ties #1 overall on pronunciation robustness at 93.2%; asr-tiny averages 4.41% error across four ASR categories. Weights are on Hugging Face and ModelScope, with day-0 SGLang and vLLM support.

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