翻訳待ち：Z.ai’s GLM-5.3 goes open weight, but its new license aims at hyperscalers

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Earlier in August, Z.ai, the Chinese AI lab behind the viral ox-alpha model that turned out to be GLM-5.3-Flash, launched its flagship GLM-5.3 model. On Friday, the company made the weights of the model available on Hugging Face, which may soon be owned by Nvidia. A number of third-party inference services already host it and make it available on services like OpenRouter, which will soon be owned by Stripe. As The New Stack’s Amanda Caswell reported when the model originally launched, Z.ai’s focus on training GLM-5.3 was on post-training. The result of that isn’t simply a large jump in benchmark performance over its predecessor, GLM-5.2, but a model that is often ahead of other Chinese open-weight models and able to keep pace with current models from the large U.S. frontier labs. A new license only hyperscalers won’t love One thing Z.ai definitely changed is the model’s license. While GLM-5.2 shipped under the permissive MIT license, the new model ships under what the company calls the GLM-5.3 license and it has one major caveat: companies that want to host the model (not just route it like OpenRouter or embed it into a product), and have an aggregate revenue of more than $10 billion over any 12 consecutive months, “must pass Z.AI’s security review before using the Software or its derivative works for any commercial purpose.” For individual users, nothing really changes — the license is more specific to models and includes the rights to run, deploy, and fine-tune. But for hyperscalers (and the neoclouds — once they hit these revenue numbers), there are now hoops to jump through. The company says it held the GLM-5.3 open weights back for two weeks for safety evaluation and hardening. GLM-5.3 hits 84.5 percent on CyberGym, a vulnerability discovery benchmark, which Z.ai says is the best published result. That number is self-reported, of course, and nobody outside the company has reproduced it yet. Z.ai says it used the model to find 2,436 vulnerabilities across 269 open-source projects, including the Linux kernel, though only a few dozen of those findings are publicly inspectable so far. GLM-5.3 is now available for download, local deployment, fine-tuning, and commercial use under the GLM-5.3 License. Given the model’s advanced cybersecurity capabilities, we conducted two additional weeks of comprehensive safety evaluations before releasing the weights. Under… https://t.co/imV0F2O6bA — Zixuan Li (@ZixuanLi_) August 28, 2026 Despite the safety framing, it’s worth noting that the license itself contains no acceptable-use section and also says nothing about cyber or offensive security. Whether Z.ai changed its license for security reasons or to be able to better monetize its own models is a question worth asking, of course. With the launch of GLM-5.3-Flash, the company stressed that the inference was running on Chinese chips, so Z.ai definitely has shown interest in owning the inference layer for these models, after all. And now that these open-weight models are getting so close to the performance of what U.S. frontier labs are producing, there’s more money to be made there, too. Back in 2023 and 2024, Z.ai also used a custom license for models like ChatGLM3-6B. Under that license, registration was required for commercial use. From then on, though, all new Z.ai models used the MIT license. Z.ai’s license is also more restrictive than what other Chinese labs are currently using. Moonshot, for example, says that if a model-as-a-service provider offers access to Kimi K3 and has more than 100 million active users or more than $20 million in monthly revenue, “‘Kimi K3’ must be prominently displayed on the user interface of such product or service.” DeepSeek still uses the basic MIT license for its flagship models. Running GLM-5.3 Under the hood, GLM-5.3 is the same 753-billion-parameter mixture-of-experts architecture as GLM-5.2, with a 1 million-token context window and a maximum output of 128,000 tokens. The weights ship in BF16 and FP8 and run on vLLM, SGLang, KTransformers, and Hugging Face’s own Transformers library. Credit: Z.ai. The two-week gap between the API launch and the open release is new for Z.ai. GLM-5.2’s weights were available on launch day. Even though the model is now open-weight, you’re not all that likely to run it locally — unless you have a very powerful machine. Even the 2-bit quants, which Unsloth says will still achieve about 86 percent top-1 accuracy, need 245GB of memory. That just fits on a Mac with 256GB of unified memory. The 8-bit quants need 810GB. For $1.40/$4.40 per million input/output tokens, it’s also significantly cheaper to use than virtually all of its most direct competitors — though the GLM-5.3-Flash model at $0.15/$0.47 has a pretty unbeatable price/performance ratio right now. What’s next? At first glance, the license is a small change in absolute terms, but it arrives in the same week that Nvidia moved to buy Hugging Face for a reported $12.9 billion and Stripe agreed to buy OpenRouter. If both deals close, the repository where developers download open-weight models and the marketplace where they rent them will belong to American companies, while the models themselves increasingly come out of Chinese labs. Z.ai kept MIT for Flash, so the company hasn’t abandoned permissive licensing completely, but it has stopped applying it to its best model. If GLM-5.4 ships the same way, the company’s MIT years will look like the customer acquisition phase, and open weights will start to look less like a gift to the ecosystem and more like a distribution channel with terms attached. The post Z.ai’s GLM-5.3 goes open weight, but its new license aims at hyperscalers appeared first on The New Stack.