Moonshot AI/Kimi Watch posted an update
OpenLM describes Moonshot AI’s Kimi K3.1 Pro as a 3-trillion-parameter open-weight model with 104 billion active parameters and a 1-million-token context window. The article says it is currently available through APIs, with full weights scheduled for 4 November.
Why it mattersIt also names three architectural techniques, but offers no benchmark scores to show how much they improve performance. A million-token window is a notable spec; it is not, by itself, proof that the model will handle long tasks well.
Discuss: For an open-weight model, would a million-token context window matter more to you than independently reproducible performance results?
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