226 summarised stories about Model Releases, each linking back to the original source. Browse all topics →
The New Stack 2 months ago 18
Alibaba released open weights for its Qwen3.8 2.4T model and also published a dense Qwen3.8 27B version under the Apache 2.0 license for local running.
TechCrunch 2 months ago 35 ● 5 sources
Meta released Glimmer, an open-weight AI model that users can run on their own hardware instead of through Meta’s APIs. The company paired the launch with Mark Zuckerberg’s 6,500-word letter arguing AI should be “for everyone” rather than limited to a few labs. The focus shifts from locked-access models toward downloadable models, while also highlighting practical limits behind the “for everyone” framing.
The New Stack 2 months ago 51 ● 3 sources
Z.ai released GLM-5.3, a coding and agent model built on the same base model as GLM-5.2, with gains attributed mainly to expanded post-training. It reported a jump from 4.6 to 28.3 on Terminal-Bench 3.0. The model is now usable via Z.ai’s Coding Plan and will deliver weights after a two-week hardening and safety period, changing how developers can validate performance locally and run A/B tests.
Hugging Face 2 months ago 30
Hugging Face’s “State of Open Models” report tracked rapid growth on the HF Hub and found major shifts in which labs publish, how downloads differ from likes, and where value accumulates in open-weight models. Public model repositories grew from 2.43 to 2.96 million and datasets from 711,000 to 1 million between January and August 2026. Open-weight adoption is increasingly shaped by hardware/infrastructure companies and by community ecosystems such as Qwen derivatives, while local inference via formats enabled by llama.cpp makes very large models runnable on more machines.
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20 October 2026
The biggest throughline today wasn’t smarter models—it was how teams keep AI usable when it starts behaving less like software and more like an employee. At Fortune’s Most Powerful Women Summit, SharkNinja CIO Velia Carboni made the case for letting systems be “a little rogue,” then finding limits with guardrails, structured human oversight, and day-to-day harnesses. That security-by-process theme echoed across the rest of the day: Anthropic said its defenses against distillation attacks on Claude now cut stolen “reasoning” tokens by 10 to 100 times, while blocking distillers more often and banning many accounts; OpenAI rolled out chat-lock in ChatGPT with a four-digit PIN/Face ID and separate locked storage; and Datadog argued the SDLC bottleneck has shifted from code-writing to testing, pushing teams toward agent-generated, observability-tied test suites.
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