Model Release

OpenAI has received US government clearance to broadly release GPT-5.6 after weeks of testing by the Commerce Department's Center for AI Standards and Innovation. The model had been restricted to approximately 20 government-approved partners under Washington's new frontier AI oversight regime.

The U.S. Department of Commerce has approved OpenAI for a broad launch of GPT-5.6 this week, following testing by the Center for AI Standards and Innovation. The model was previously restricted to government-approved entities since June, mirroring earlier restrictions placed on Anthropic's models.

The Trump administration has instructed OpenAI to release its newest model, GPT-5.6, only to a select group of government-approved partners rather than the general public. The Office of the National Cyber Director and Office of Science and Technology Policy will approve access customer by customer during a preview period.

Microsoft has released Lens-Turbo, a 3.8B-parameter foundational text-to-image model designed for efficient training and fast generation. The model was trained on Lens-800M, an 800 million image-text corpus with GPT-4.1 captions, and supports resolutions up to 1440×1440 with 4-step distilled inference.

OpenAI released GPT-5.5-Cyber in limited preview on Thursday, a variant of its GPT-5.5 model with relaxed safeguards for vetted cybersecurity teams. The model is trained to be more permissive on security-related tasks including vulnerability identification, patch validation, and malware analysis.

OpenAI is providing a less-restricted version of GPT-5.5 to vetted cybersecurity defenders through its Trusted Access for Cyber program. The model, dubbed GPT-5.5-Cyber, completed a 32-step simulated corporate cyberattack in 2 out of 10 test runs according to the U.K. AI Security Institute, narrowly trailing Anthropic's Mythos which succeeded in 3 out of 10 attempts.

Alibaba Qwen has released Qwen3.6-35B-A3B, a 35-billion parameter mixture-of-experts model with 3 billion activated parameters and a 262,144-token native context window extendable to 1,010,000 tokens. The model scores 73.4 on SWE-bench Verified and features FP8 quantization with performance metrics nearly identical to the original model.