Moonshot AI Releases Kimi K3.1 Pro With 1 Million Token Context
Moonshot AI introduced Kimi K3.1 Pro in a company blog post, describing it as its most capable 3T class open weight model with a 1 million token context window. The company reports a 65.7% score on Terminal Bench 4.0, narrowly behind Claude Opus 5.5 at 66.4% and ahead of GPT-6 Astra at 58.2%. It says Kimi K3.1 Pro Highspeed runs 2 to 3 times faster than the standard model.
Both versions are available through Kimi.com, Kimi Work, Kimi Code, and the Kimi API. Full model weights will be released by November 4, while access for Kimi Enterprise organizations is disabled by default at launch.
Kimi K3.1 Pro is a post trained version of Kimi K3, with added reinforcement learning for coding, 3D creation, financial analysis, and tool based tasks. Training data related to cyber security was removed from two training stages before the open weight release, reducing its score on an internal vulnerability exploitation test from 90.5% to 81%.
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Whitepaper
Tensordyne Napier: What If One Rack Could Do the Work of Nine?
Tensordyne
This Tensordyne whitepaper presents Napier, an inference-focused AI processor and rack-scale system based on the company’s TDN Math logarithmic number system. It examines infrastructure requirements for large mixture-of-experts and agentic models, compares major inference architecture approaches, and details the TDN AIP processor, TDN72 pod, TDN Link fabric, and Napier Ultra configuration. The paper reports simulation-based performance, cost, and accuracy-validation results, including Tensordyne’s projected comparison of one Napier rack with a nine-rack Nvidia Rubin plus Groq deployment; the chip is reported as taped out and in fabrication.
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