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Moonshot's K3.1 Pro is primarily a post-training update to K3, not a new architecture, and the research detail is thin. Its headline claims (near-frontier benchmarks, 2-3x faster Highspeed output, and a 2.8T-parameter open-weight release promised for November 4) are company-reported and still need independent verification. Readers should watch the open-weight release and third-party evaluations, and note that the Highspeed price and speed claims conflict between sources.
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[AINews] Kimi 3.1 Pro 104BA-2.8T: Fable-5.1-Class Open Weights narrows Closed-AI lead to 1 month... and Pro Highspeed API with 2-3× speed

Latent Space69 min de cititArticolul și perspectiva sunt în engleză.

We have Fable at home... or so we are being told by paid shills

As usual we don’t get much research detail - the update is somewhat similar to Z.ai’s 5.2-5.3 bump - a minor version bump for a lot more post-training: Kimi K3.1 Pro is a post-trained version of Kimi K3, with substantially larger post-training compute. To enable large-scale joint RL across hundreds of downstream domains, we optimized every layer of the stack — the RL framework, long-context inference, training efficiency, sandbox infrastructure, rollout scheduling, and a shared platform for environment quality checks — so that each increment of RL compute delivers stable, predictable returns. As a result, K3.1 Pro achieves consistent gains in every domain. Top Story: Kimi K3.1 Pro launch and reactions Moonshot launched Kimi K3.1 Pro with near-frontier independent benchmark results, a substantial increase in model size, and an open-weight release promised for November 4, 2026. The model: Moonshot describes K3.1 Pro as a multimodal, “3T-class” mixture-of-experts model with 2.8 trillion total parameters, 104 billion active parameters, and a 1-million-token context window. Its advertised strengths include full-project coding, Blender/CAD work, financial modeling, and long-running agents. @Kimi_Moonshot The model: Moonshot describes K3.1 Pro as a multimodal, “3T-class” mixture-of-experts model with 2.8 trillion total parameters, 104 billion active parameters, and a 1-million-token…

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