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What's happening in robotics and AI — curated by the wujec.ai editors.
Mistral built its name on freely licensed weights — its biggest one is still the model it published in April 2024
Mistral AI became a recognised name in September 2023 by publishing a 7.3-billion-parameter model under Apache 2.0 — the licence that lets anyone download, fine-tune and commercially resell the result without asking. Three months later, Mixtral 8x7B repeated the trick at a size that mattered: 46.7 billion parameters stored, 12.9 billion spent per token, benchmark scores at the level of Llama 2 70B and of the GPT-3.5 base model then serving free ChatGPT. In April 2024, Mixtral 8x22B scaled the same sparse design to 141 billion parameters, 39 billion of them active per token, with a 64,000-token window and native function calling. It, too, went out under Apache 2.0. That April 2024 release is still the largest model Mistral has ever opened. Everything above it changed terms: Mistral Large 2.1, from November 2024, shipped its weights under the Mistral Research License with a separate commercial licence sold on top, and the flagships that followed were never opened the same way. The company that made permissive licensing its signature has kept publishing open weights — but at the small and medium end, while the top of its range moved behind commercial terms. The practical consequence is that Apache 2.0 cannot be revoked. Mixtral 8x22B has disappeared from Mistral's own API line-up, which today lists Large 3, Medium 3.5, Small 4 and Ministral 3, and the company has never announced a shutdown date for it. That is not a problem for anyone relying on it: the weights sit on Hugging Face, third-party providers still serve them, and a licence granted under Apache 2.0 stays granted regardless of what the vendor's catalogue says. wujec.ai has now catalogued all three of these open releases.
Mixtral 8x22B →Alibaba opens both ends of Qwen3.8 — but only the small model gets Apache 2.0
Alibaba has now published downloadable weights for both halves of the Qwen3.8 generation, and the licences attached to them are not the same document. Qwen3.8-27B, released on 14 August, is a dense 27.78-billion-parameter vision-language model under a plain Apache 2.0 licence — no thresholds, no conditions, no separate agreement for commercial use. It takes text, images and video, has a native 262,144-token context that Alibaba says stretches to a million, and runs on Transformers, vLLM, SGLang and TokenSpeed. Alibaba's own benchmark table puts it at 61.7 on SWE-bench Pro against 57.6 for its closed Qwen3.7-Plus, and at 42.2 on DeepSWE 1.1 against 13.3 for the previous 27B generation — vendor-reported figures, not independently reproduced. The flagship went out under different terms. Qwen3.8-Max, 2.446 trillion parameters, is on Hugging Face as Qwen3.8-2.4T-A95B in bf16 and FP8, but under a bespoke "Qwen3.8-Max License". Its text reads like a permissive licence for almost everyone: free use, modification, hosting, fine-tuning and resale. Two clauses change that at scale. A product with more than 100 million monthly active users or 20 million dollars in monthly revenue must display the model's name prominently in its interface. And any company running a model-as-a-service or an AI coding/office assistant business whose revenue passes 50 million dollars over twelve months must obtain a separate licence from Qwen before commercial use — internal deployment excepted. The practical effect is a licence aimed squarely at a handful of named competitors while leaving everyone below those thresholds fully free. It is a pattern worth watching: "open weights" is quietly becoming a spectrum, and the difference between the two Qwen3.8 downloads is not the code but the paragraph that comes with it. Both models are now in the catalogue, with the licence terms written out in full in the specification tables.
Qwen3.8-27B →The model Europe was not allowed to have: Tencent drops the regional carve-outs from Hy3 and goes global
Chinese open-weight models have spent the past two years competing on size and price. Tencent's Hy3 has quietly been competing on something else: who is allowed to download it. When the preview build appeared in April 2026, its licence carried a geographic exclusion — the European Union, the United Kingdom and South Korea were carved out. The official release on 6 July 2026 removed the clause entirely and put the weights under a plain Apache 2.0 licence, one of the most permissive terms yet attached to a model of this scale. On 5 August Tencent completed the move by announcing global availability: the WorkBuddy assistant, the Miora design tool and Tencent Cloud TokenHub, plus third-party access through OpenRouter and downloads on Hugging Face and ModelScope. The model itself is a sparse mixture-of-experts design: 295 billion parameters in total, roughly 21 billion activated per token across 192 experts with top-8 routing, 80 layers, and a separate 3.8-billion-parameter multi-token-prediction stack that speeds up decoding. The context window is 256,000 tokens. The distinctive feature is that the amount of deliberation is a setting rather than a separate product — no_think answers immediately, think_low reasons briefly, think_high runs an extended chain — so one endpoint covers both a chat reply and a long analytical job. Tencent's own framing is that Hy3 performs comparably to flagship models with two to five times as many parameters, across reasoning, instruction following, in-context learning, code generation and agentic work. The company also reports that within a week of launch, API traffic to Hy3 ran 68 times higher than to the previous generation, putting it first on OpenRouter's usage leaderboard. Listed OpenRouter pricing is 0.1288 US dollars per million input tokens and 0.5336 per million output; access through WorkBuddy is free until 31 August 2026. The usage number is the one to watch. Benchmark parity claims from vendors are routine; a 68-fold jump in paid API calls is a statement about how many developers actually switched. Independent coverage broadly agrees with the performance claims, with coding the one area where rival open-weight models still hold an edge.
Tencent Hy3 →