#Ming-3.0

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Stories, products and papers tagged "Ming-3.0", newest first.
10月21日
10月20日
ModelsBuildersMulti-sourceSelected16:43
Ant Group open-sources 5 Ming-3.0 speech models

The three links are composable and self-deployable, so a team can build a full listen-understand-speak voice agent without paying for proprietary APIs. Deployers in multilingual markets gain a working path for dialect-heavy ASR and instruction-driven TTS in one stack. Compared with closed services like OpenAI's audio APIs, this stack keeps weights local and lets you fine-tune each stage separately.

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AIGCLINK@aigclink5 sourcesSource
ModelsBuildersMulti-sourceSelected02:18
Ant Ling's Ming-3.0 speech models run locally from 0.5B

Small-parameter speech models that top open benchmarks change the calculus for on-device voice assistants, cutting cloud costs and latency. Developers building voice apps in low-connectivity markets across Southeast Asia can deploy these locally without API dependence. Compared with larger proprietary speech APIs, the 0.5B starting size makes experimentation cheap on a single GPU or even CPU.

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@atomic_chat_hq@atomic_chat_hq5 sourcesSource
ModelsBuildersMulti-sourceSelected00:31
Ant Ling's Ming-3.0 speech models get day-0 vLLM-Omni support

Day-0 inference support means developers can productionise open speech models immediately instead of waiting on community adapters, cutting integration work for voice pipelines. Teams building ASR, TTS or audio-understanding agents can compare Ming-3.0's MoE sizing against closed APIs and self-host at lower cost. The 0.5B to 126B-A6.5B spread also gives Southeast Asian startups an on-premise option for multilingual voice work.

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官方账号vLLM@vllm_project5 sourcesSource
Ming-3.0 · AI news | AITOP