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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 headingAbout Ling 3.0 Flash

Ling 3.0 Flash is Inclusionai's hybrid reasoning model, built around sparsity: 124 billion total parameters with about 5.1 billion active per token, roughly a one-in-sixty-four expert activation. Inclusionai positions it as matching or beating its own much larger flagship on most benchmarks while activating a fraction of the parameters.

The attention design is hybrid from the start rather than retrofitted. A repeating five-to-one stack alternates Kimi Delta Attention with multi-head latent attention, so linear attention keeps long inputs cheap while periodic full-attention layers preserve exact token-to-token recall. That combination is what lets a model this sparse hold up on reasoning tasks instead of only on throughput.

The context window is 256K tokens, with up to 32K tokens per response. Thinking mode is enabled by default and the model scales its thinking effort to the difficulty of the task, so simple prompts do not pay the full reasoning cost.

Ling 3.0 Flash scores 38 on the Artificial Analysis Intelligence Index, well above the median for open-weight models of comparable size. Weights are published on Hugging Face.

You can integrate Ling 3.0 Flash through AI SDK, Chat Completions API, Responses API, Messages API, or other API formats, from TypeScript or Python.