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Inclusionai

Ling 3.0 Flash

Ling 3.0 Flash is a 124B Mixture-of-Experts model from Inclusionai activating about 5.1B parameters per token, built for token-efficient agent runs across a context window of 256K tokens.

ReasoningTool UseImplicit Caching
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import { streamText } from 'ai'


const result = streamText({
  model: 'inclusionai/ling-3.0-flash',
  prompt: 'Why is the sky blue?'
})
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Copy link to headingFrequently Asked Questions

  • What is Ling 3.0 Flash built for?

    Token-efficient agentic inference. About 5.1 billion of its 124 billion parameters activate per token, so multi-step runs fit inside tighter cost and latency budgets.

  • How is Ling 3.0 Flash different from ling-3.0-flash-free?

    It is the same model on a paid routing tier. Use the free tier for evaluation and prototyping, and this one for production traffic. Compare both on this page.

  • What is the context window for Ling 3.0 Flash?

    The context window is 256K tokens, with up to 32K tokens per response.

  • How does the hybrid attention design work?

    A repeating five-to-one stack alternates Kimi Delta Attention with multi-head latent attention. Linear attention keeps long inputs cheap, and periodic full-attention layers preserve exact token-to-token recall.

  • Is thinking mode on by default?

    Yes, and the model scales thinking effort to task difficulty. On high-volume simple calls, check your output token budget, since reasoning tokens are still spent unless you disable it.

  • Are the weights open?

    Yes. Inclusionai publishes the weights on Hugging Face.

  • Does Ling 3.0 Flash really match a one-trillion-parameter model?

    The parameter-efficiency claim is directionally supported but the precise margin is not. The launch comparison point appears to be a specific expert variant rather than the headline flagship, and no readable data table accompanied the chart.

  • Does Ling 3.0 Flash support Zero Data Retention?

    Zero Data Retention is not currently available for this model. Zero Data Retention is offered on a per-provider basis. See https://vercel.com/docs/ai-gateway/capabilities/zdr for details.