Former OpenAI CTO does what Altman won't: releases a frontier AI model that's actually open

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  "signal_type": "news",
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  "detected_at": "2026-07-16T00:14:41+00:00",
  "company": {
    "name": "Thinking Machines Lab",
    "domain": "thinkingmachines.ai"
  },
  "data": {
    "url": "https://www.theregister.com/ai-and-ml/2026/07/16/former-openai-cto-does-what-altman-wont-releases-a-frontier-ai-model-thats-actually-open/5272177",
    "title": "Former OpenAI CTO does what Altman won't: releases a frontier AI model that's actually open",
    "excerpt": "AI and ml Thinking Machines' first open weights model is a 975 billion parameter alternative to Chinese LLMs If you’re in the market for a frontier-class open weights model, your options are few and far between outside of the Chinese model houses. With the Wednesday release of a new model code-named \"Inkling\", an outfit called Thinking Machines Lab aims to change that. Founded in early 2025 by former OpenAI CTO Mira Murati, Thinking Machines' first model is a big one. Weighing in at 975 billion parameters, the model requires more than two terabytes of GPU memory - a quantity present in around eight of Nvidia's B300 accelerators, or sixteen H200s - to run at its native 16-bit precision. If that’s asking too much of your hardware, Thinking Machines has also released a NVFP4 quantized version of the model capable of running on half the GPUs. This makes it the largest American open weights model to date, and comparable to Chinese models like DeepSeek V4, GLM 5.2, and Kimi K2.6 in terms of size and capabilities. Take these claims with a grain of salt - gaming AI benchmarks isn’t exactly difficult - but Thinking Machines says Inkling is competitive with these models in a variety of workloads, although its benchmark charts also show it trailing proprietary models like Anthropic’s Claude and OpenAI’s GPT. Thinking Machines describes the model as being highly adaptable, intended for...",
    "product": "Inkling-Small",
    "summary": "Thinking Machines Lab is developing Inkling-Small, a 276-billion-parameter MoE model, and plans to release its weights once testing is complete.",
    "planning": true,
    "image_url": "https://image.theregister.com/5272215.jpg?imageId=5272215&x=0&y=0&cropw=100&croph=100&panox=0&panoy=0&panow=100&panoh=100&width=1200&height=683",
    "confidence": 0.9,
    "product_data": {
      "name": "Inkling-Small",
      "full_text": "Inkling-Small, a 276-billion-parameter MoE model",
      "fuzzy_match": false,
      "release_type": "model"
    },
    "product_tags": [
      "future_tech",
      "general_technology"
    ],
    "published_at": "2026-07-16T00:14:41Z",
    "article_sentence": "Alongside its flagship model, the company is also previewing Inkling-Small, a 276-billion-parameter MoE model with 12 billion active parameters for those prioritizing latency over throughput and quality."
  }
}

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