# Moonshot Cuts Cyber Capabilities From Kimi K3.1 Pro Before Releasing Its Weights by November 4

Moonshot's own benchmark tables put the 2.8-trillion-parameter mixture-of-experts model ahead of Claude Opus 5.5 on Humanity's Last Exam, but independent scoring ranks it fourth.

- Published: 2026-10-28T06:21:21.801Z
- Canonical: https://polylog.news/ai/2026-10-28/moonshot-cuts-cyber-capabilities-from-kimi-k3-1-pro-before-r
- Publisher: Polylog (AI desk)
- Section: tech
- Sources: [Anthropic News](https://www.anthropic.com/claude-opus-5-5)

Moonshot AI released Kimi K3.1 Pro on October 23 through its own services. It has promised the full weights by November 4 under a license close to MIT, with added conditions for very large companies, [DataCamp reported](https://www.datacamp.com/blog/kimi-k3-1-pro). The model is a mixture-of-experts design with 2.8 trillion total and 104 billion active parameters, a 1-million-token context window and multimodal input. If the checkpoint ships in the same compressed numerical format as K3, called MXFP4, it will take up about 1.56 TB on disk, [according to Yotta Labs](https://www.yottalabs.ai/post/kimi-k3-1-pro-specs-price-open-weights-benchmarks).

Moonshot's published comparisons use [Claude Opus 5.5](https://www.anthropic.com/claude-opus-5-5) as the main baseline. With tools, Kimi K3.1 Pro scores 70% on Humanity's Last Exam, against 67.7% for Opus 5.5 and 57.2% for GPT-6 Astra. It scores 65.7 on Terminal-Bench 4.0, against 66.4 for Opus 5.5, [per MindStudio's review](https://www.mindstudio.ai/blog/kimi-k3-1-pro-benchmarks-review). These are vendor-reported numbers. The independent Artificial Analysis Intelligence Index scores the model at 55, placing it fourth, behind Opus 5.5 at 58 and level with Claude Sonnet 5.5 and Meta's Muse Wonder Full at 56. The gap between the two sets of numbers reflects the normal difference between a lab's chosen benchmarks and a fixed third-party suite.

The more consequential detail is a safety change. Moonshot deliberately reduced the model's offensive-security skills before releasing the weights, [Technology.org reported on October 26](https://www.technology.org/2026/10/26/moonshot-kimi-k3-1-pro-cyber-capabilities/). A downloadable checkpoint cannot be recalled or monitored once it is out. Whatever capability ships in the weights becomes available to anyone who fine-tunes it, which is why removing that capability before release is the only control an open-weight lab retains. Whether the removal survives fine-tuning is an open question that no independent group has yet tested.

The release comes as China's hardware base shifts. Nvidia's share of China's data-center AI chip market fell to 34% in the first half of 2026. Nvidia shipped 678,000 accelerators, down 44% year over year, while Huawei shipped 572,000 for a 28% share, according to an [IDC report covered by Yahoo Finance](https://finance.yahoo.com/technology/ai/articles/u-export-restrictions-drive-nvidia-124325286.html). Beijing is also [drafting its own export-control list](https://startupfortune.com/china-opposes-us-deepseek-ban-as-it-drafts-its-own-export-controls/), adding about 40 items across AI, solar power and biomedicine.

## What this means

A near-frontier model with downloadable weights reaches every government and company that US model-access restrictions exclude, and it reaches them at the cost of hosting rather than at API margin. The exposed parties are closed API vendors that sell to price-sensitive and non-US buyers, and US policymakers who treat model access as a lever of control. The benchmark claim is already discounted, since the independent index ranks the model fourth. What is new is a Chinese lab removing cyber capability before release. That gives Moonshot a defense against the argument that Chinese open weights pose an uncontrolled security risk, an argument that could otherwise justify US or EU restrictions on hosting them. The precedent is DeepSeek-R1 in January 2025. Its open release led to rapid adoption by Western cloud hosts, followed by government bans on its consumer app rather than on the underlying weights. The likelier outcome is that major non-Chinese inference hosts list K3.1 Pro within weeks of the weights appearing, and that the US debate shifts toward restricting the hosting of Chinese weights inside the US. This depends on Moonshot shipping the weights on schedule. A delay past November 4, or an independent red-team test showing the cyber capability returns after light fine-tuning, would prove the read wrong.

## What to watch

- Whether the weights appear by November 4 under the promised license. A delay would suggest pressure from Beijing or a change in commercial plans.
- Whether independent tests show that fine-tuning restores the offensive-security skills Moonshot removed. The answer determines whether removing capability before release can work as a safety control for open weights.
- Huawei's share of China's accelerator shipments in the second half of the year. A further rise would show Chinese labs training and serving models at scale on domestic hardware.