惯性聚合 高效追踪和阅读你感兴趣的博客、新闻、科技资讯
阅读原文 在惯性聚合中打开

推荐订阅源

雷峰网
雷峰网
IT之家
IT之家
Last Week in AI
Last Week in AI
J
Java Code Geeks
L
LangChain Blog
Recent Announcements
Recent Announcements
Martin Fowler
Martin Fowler
H
Hackread – Cybersecurity News, Data Breaches, AI and More
Google DeepMind News
Google DeepMind News
博客园 - Franky
博客园 - 司徒正美
月光博客
月光博客
博客园 - 叶小钗
Vercel News
Vercel News
腾讯CDC
钛媒体:引领未来商业与生活新知
钛媒体:引领未来商业与生活新知
小众软件
小众软件
Cyber Security Advisories - MS-ISAC
Cyber Security Advisories - MS-ISAC
GbyAI
GbyAI
B
Blog RSS Feed
人人都是产品经理
人人都是产品经理
H
Help Net Security
G
Google Developers Blog
D
DataBreaches.Net

Interconnects AI

Open-Source AI & Open Models Reading List One resignation turned the embers of AI fear into a wildfire When will average people feel AI’s impact? Teaching Everyone to Fish for Tokens GLM-5.3: How Chinese labs keep stride with the frontier I wrote an AI textbook — how long until AI can do it better? 5 useful things you'll learn in my post-training textbook Lessons from the hacks Introducing our Artifacts Hub and Adoption Dashboard Latest open artifacts (#23): Laguna S2.1, Inkling, & Kimi K3 show the utility of open models on the Pareto frontier Open models recap: more on Kimi K3, Qwen 3.8, Xi's WAIC speech, distillation, the open-closed gap, and what's next Kimi K3: The open-weights escalation 6 months to live for open models Latest open artifacts (#22): Zyphra, Cohere, and Poolside are expanding the breadth of the ecosystem GLM-5.2 is the step change for open agents Banning Open Source AI Would Be A Mistake State of the blog Frontier post-training recipe review with Finbarr Timbers Welcome to the AGI era of AI governance Claude Fable 5 and new safety fables Farewell Ai2 Open and closed models are on different exponentials Some ideas for what comes next, May 2026 Latest open artifacts (#21): Open model bonanza! Gemma 4, DeepSeek V4, Kimi K2.6, MiMo 2.5, GLM-5.1 & others How open model ecosystems compound Notes from inside China's AI labs The distillation panic Reading today's open-closed performance gap My bets on open models, mid-2026 What I've been building: ATOM Report, post-training course, finishing my book, and research
Latest open artifacts (#24): Motif-3, GLM-5.3, Hy4-previe...
Florian Brand · 2026-09-08 · via Interconnects AI

Avid Artifacts readers know that we have been covering not only models but also their licenses for quite some time. There was a period when custom licenses were all the rage, for example the custom Qwen2.5 72B-Instruct license or the Llama licenses. DeepSeek had a custom license for DeepSeek V3 before R1 changed it to MIT, which has resulted in many (Chinese) model makers adopting MIT or Apache 2.0 licenses in 2025.

In 2026, open models are more competitive than ever, which has led to two interesting developments: Western model makers adopt open licenses, with both Google and Meta switching to Apache 2.0. Chinese model makers at the frontier, however, are becoming more restrictive: Kimi K3 comes with a license which requires commercial agreements for those who run inference or fine-tuning services, and MiniMax M3 requires agreements above a revenue threshold and has prohibited use cases.

The newest addition is Zhipu’s GLM-5.3, which switched from MIT (GLM-5.2 and earlier) to a custom license with the following clause for inference and fine-tuning providers:

If the Licensee or any of its affiliates operates a Model as a Service business, and the aggregate revenue of the Licensee and its affiliates exceeds 10 billion US dollars (or the equivalent in other currencies) in total over any consecutive 12 months, the Licensee must pass Z.AI’s security review before using the Software or its derivative works for any commercial purpose. The scope and method of the security review shall be reasonably determined by Z.AI.

While the 10 billion US dollar threshold is very high compared to other licenses of this kind, “affiliates” is not defined in the license, which adds uncertainty and creates barriers to adoption. Furthermore, the license is provided in both English and Chinese, with the Chinese text using “关联方” for affiliated parties, which does have a definition in Chinese law.

We are by no means legal experts and there are obvious reasons why those licenses are created. However, we want to highlight the issues that come with creating such licenses, especially in a world with a lot of valid open and closed alternatives.

Share

  • Motif-3 by Motif-Technologies: Motif is one of the few hidden gems out there, showcasing innovation in their model training with very limited resources compared to others. Motif-3 comes with an MIT license and impressive scores for its size. Given the trajectory of model releases from Motif 2.6B, which we covered in 2025 and Motif-2-12.7B, the improvements are impressive.

  • dots3-note-prev by dots-studio: RedNote/Xiaohongshu, the Chinese Instagram, is also getting more serious about model training, although they aren’t exactly a newcomer, having released models as early as 2025. dots3 was also able to win the IMO 2026 with a perfect score using an internal harness. We expect more from them in the near future.

    General Reasoning and Agent evaluation results
  • Qwen3.8-Flash-Next by Qwen: A preview of the next version of Qwen models in terms of architecture: 125B-A6B with 51B n-gram embeddings. It uses GDN and Qwen Sparse Attention. Similar to Qwen3-Next-80B-A3B-Instruct, we expect similar architectures to become more popular and the ecosystem to fix integrations by the time Qwen4 drops.

  • GLM-5.3-Flash by zai-org: This release perfected the version of the Chinese model playbook we’ve written about in 2025: The model got released as a free-to-use “stealth model” under the name “Ox-Alpha” on OpenRouter and OpenCode, which got people excited to try it out in the first place. They then speculated about its creator and size, alleging it is a >1T model from Cursor/xAI, Gemini or a new pre-train from open source labs. Because the model is relatively performant, people kept speculating for days about its creator, thus building up hype. It also dampens the accusations of benchmaxxing which accompany every (open) model release.

    bench_53
  • Hy4-preview by tencent: Tencent is becoming a serious player in the open model space, increasing the size of their flagship model while spinning the post-training flywheel. The result, Hy4-preview, is a competent model which currently has an issue with overthinking. However, if the trajectory from Hy3-preview to Hy3 is any indication, the final model might be a legit shot at the front ranks of open models.

View more details on all the models in this issue at our Artifacts Hub.

Visit artifactshub.ai

  • NVIDIA-Nemotron-3.5-Lightning-30B-A3B-BF16 by nvidia: An update to Nemotron, which comes with performance — but especially speed improvements — across the board.

    bench_53
  • Ling-3.0-flash by inclusionAI: Ant Ling is a frequent guest at the Artifacts Log; they are now on their third iteration of models, adopting a hybrid design (KDA + Gated MLA), similar to others. They also release a small 7.9B-A1.3B version.

  • Qwen3.8-2.4T-A95B by Qwen: In a rather surprising turn of events, Alibaba started to openly release their biggest versions of Qwen as well. However, it comes with a custom license and its performance is behind other models of its size.