Thinking Machines, the AI lab founded by former OpenAI CTO Mira Murati, open-sourced its first multimodal language model, Inkling, according to VentureBeat reporting, with The Register separately framing the release as Murati doing "what Altman won't" by publishing genuinely open weights rather than a closed API.
Inkling topped Hacker News with more than 1,000 points on the day of its release, an unusually strong organic technical-community signal for a first major model launch from a lab that's been operating for roughly two years since Murati's departure from OpenAI, and a sign the underlying technical work has real credibility with the developer audience that matters most for open-weight adoption.
Thinking Machines joins a growing cohort of well-funded open-weight labs -- Mistral, Black Forest Labs, and Nous Research, the last of which is separately reported to be in talks for funding at a $1.5 billion valuation -- all betting that open distribution can build a durable, monetizable business through enterprise tooling and hosted infrastructure, rather than functioning purely as a marketing or recruiting play against closed competitors.
For investors evaluating the open-weight thesis broadly, Inkling's strong technical reception adds another credible data point that open models can achieve genuine developer mindshare independent of a closed lab's marketing budget or distribution advantages, reinforcing the case that the open side of the AI stack deserves its own dedicated allocation rather than being treated as a discount version of the closed-lab trade.
The bear case: strong Hacker News reception doesn't guarantee enterprise monetization, and Thinking Machines still needs to demonstrate a path to revenue from hosting, fine-tuning or enterprise tooling built on top of freely available weights, the same monetization challenge every open-weight lab faces. What to watch next: Inkling's adoption among developers building production applications, and whether Thinking Machines announces enterprise or hosted-infrastructure offerings to monetize the model.