Thinking Machines Lab released Inkling, a 975B-parameter open-source AI model trained on 45 trillion tokens, using the same business model as Slate Auto's Blank Slate pickup truck: ship a cheap, customizable base and charge for modifications.
Inkling's weights are free on the company's fine-tuning platform Tinker, but fine-tuning services charge a fee.
This approach demonstrates how open-source AI companies can fund development by monetizing customization rather than the base model itself.
What happened
Thinking Machines Lab released Inkling, a 975B-parameter open-source AI model trained on 45 trillion tokens, designed as a generalist base for customization. The company launched it on Tinker, its fine-tuning platform, where weights are free but customization charges a fee—paralleling Slate Auto's $24,950 Blank Slate electric pickup truck, which ships bare (no stereo, speakers, touchscreen, or paint) to invite customer modification.
Why it matters
This strategy shows how open-source AI labs can fund development without giving away their work. By releasing a deliberately unremarkable general-purpose base and monetizing customization, Thinking Machines creates a sustainable business model similar to how Slate monetizes accessories. For enterprises, it means low-cost entry to a capable model paired with paid services to adapt it to specific needs.
What to watch
Inkling is positioned as a generalist model—good across many domains—rather than specialized. Thinking Machines is betting that the ability to fine-tune on Tinker will be valuable enough to customers to drive revenue, establishing a template for how open-source AI companies can remain viable.
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The article presents a strategic parallel between two companies pursuing what it calls a 'blank slate' model: ship a deliberately unremarkable, general-purpose base at a low price, then monetize through customization. Slate Auto's approach—a $24,950 electric pickup with no paint, stereo, speakers, or touchscreen—strips the vehicle to its essentials and invites buyers to add value themselves through accessories. Thinking Machines applies the same logic to open-source AI: Inkling is described as a generalist model, "good in many domains," released as a foundation "ready to be customized." The key insight is that open-source AI labs need a path to sustainability. By keeping the base model free and charging for the customization service (fine-tuning via Tinker), Thinking Machines solves the business model problem that has traditionally plagued open-source software—how to generate revenue when the core product is given away. This strategy positions Inkling not as a competitor to proprietary models on raw capability, but as a building block for customers who want to adapt it to their own needs.
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