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Announcing OpenWorker! An open-source agent that doesn't just chat with you, but delivers finished work -- like hand you a polished document, send a slack message, or update a calendar entry. Ask it to prepare a customer brief, untangle your calendar, draft a report, or triage a Slack alert. It works across your files and everyday tools, produces the deliverable, and checks in before doing anything consequential. OpenWorker runs on your Mac, with Windows support coming soon. It does not lock you into any one model. Bring your own API key and run it with GPT 5.6 Sol, Claude Fable, Gemini 3.6, an open weight model (like Kimi, GLM, DeepSeek, Inkling), or Ollama to keep your data local. Your data does not leave your machine except through an LLM provider and integrations that you choose. @rohitcprasad and I are building OpenWorker because AI coworkers are an important way to get work done, and we want there to be an open, privacy-preserving, model-independent option. Check it out and let us know what you think! Try it out: (requires your own API key) Source code:

The FrontierCode leaderboard is now live: a dedicated page that tracks which models are writing code you’d actually merge. All scores — including Grok 4.5 and Inkling — are available, along with full methodology and sample tasks.

Thinking Machines - Inkling Thinking Machines Lab, the company founded by Mira Murati, has released Inkling, its first open-weights model under the Apache 2.0 license. Inkling is a mixture-of-experts transformer with 975 billion parameters in total, yet only 41 billion of them are active for any given token. Every layer contains 256 routed experts and 2 shared experts, and a router selects just the 6 most relevant experts per token. This means that only about 4 percent of the model performs computation during inference. The backbone is a 66-layer decoder-only transformer that combines local and global attention layers and supports a context window of one million tokens, which is roughly enough to fit eight novels or an entire codebase into a single prompt. The model was pretrained on 45 trillion tokens spanning text, images, audio, and video. Instead of relying on separate vision or audio encoders, it converts images into patches and audio into discrete tokens, then projects everything into one shared hidden space. All modalities are therefore fused from the very first layer. Inkling accepts text, images, and audio as input, while its output remains text only. On public benchmarks, it performs at the level of GPT 5.6 Sol and Claude Fable 5 in reasoning and agentic coding. The weights are available on Hugging Face, and the model can be fine-tuned through the Tinker API. #MiraMurati# #thinkingmachines# #inkling# #OpenSource#

Thinking Machines发布Inkling：Mira Murati团队的首个开源多模态大模型 975B总参数、激活41B的MoE架构，Apache 2.0协议，支持文本、图像、音频输入，输出文本。 跑分处于开源第一梯队中上游，HLE带工具46.0%、SWEBench Verified 77.6%、GPQA 87.2%，与Kimi K2.6、DeepSeek V4 Pro同档，距离闭源模型还有差距。 这是首个1T参数级别的开源多模态模型，且支持在自家Tinker平台做微调定制。 模型：

Today, we are introducing Inkling. Inkling reasons efficiently across text, image, and audio modalities. We are making the full weights available. Available today for fine-tuning on Tinker. Play with it in the Inkling Playground. 🧵

"President Trump single-handedly stopped Iran from getting a nuclear weapon," says @StephenM. "As a result of these negotiations, the United States is closer than ever before to inking an agreement that is going to finally create the roadmap for peace, security, and prosperity in the Middle East."