Now, there’s another Nvidia investment and partner Thinking Machines, throwing its hat into the open weights US model challenge, with a model named Inkling. The company of course was founded by ex-OpenAI executives. They’re alternatives to the industry leading closed AI models from Anthropic and OpenAI in particular. With former open source leader Meta, and Elon’s SpaceXAI also with recent closed AI model offerings. And championed by Nvidia no less.
“Thinking Machines Lab’s first model is an ‘open weights’ model designed to chip away at the lead of OpenAI and Anthropic.”
“Thinking Machines Lab, led by former OpenAI technology chief Mira Murati, released its first AI model, an open-weights model called Inkling.”
“Inkling has 975 billion total parameters and was designed to balance cost against performance rather than achieve state-of-the-art power.”
“Thinking Machines said it tested the model for safety risks, including its potential to help build biological weapons or aid hackers with cyberattacks, and it performed well.”
“Former OpenAI technology chief Mira Murati is betting on more customizable artificial-intelligence models to chip away at the lead that frontier labs such as her former employer hold over the technology.”
“Thinking Machines Lab, the company led by Murati, released its first AI model on Wednesday—and did it with “open weights,” meaning others can modify it with their data. Called Inkling, the model has 975 billion total parameters, making it far smaller than estimates of the most advanced closed-source models from rivals such as OpenAI and Anthropic.”
“We trained it to be a broad, balanced foundation model: strong across many domains, flexible enough to adapt. Inkling is not the strongest overall model available today, open or closed,” the company said.”
It’s a timely offering when big tech companies like Microsoft are looking for US model alternatives for their global customers. Especially vs the frontier AI companies Anthropic and OpenAI.
“Thinking Machines’s push into the decentralized ecosystem of open-weights AI models comes amid a broader industry backlash against the “walled garden” approach of frontier labs such as OpenAI and Anthropic.”
“Industry leaders such as Palantir Chief Executive Alex Karp and Microsoft’s Satya Nadella have warned that companies risk undermining their own business models by feeding their core institutional data into centralized, generalist models they don’t control.”
I’ve talked about the above trend of course at length in my recent ‘Us vs Them’ podcast discussion.
“The release is also part of a push within Silicon Valley to build homegrown open-weights models as an alternative to those developed by China’s Alibaba and a younger crop of startups such as Z.ai. Many U.S. companies have been turning to Chinese open-weight models to help complete less-sophisticated AI tasks, in an effort to control costs and diversify their approach.”
“Rather than focus on raw power like the frontier labs, the Thinking Machines model was designed to balance “cost against performance,” the company said. Of the nearly 1 trillion parameters that Inkling has, only 41 billion are “active,” meaning that only a fraction of the AI’s “brain” will be woken to deal with any query, making it cheaper and faster to use.”
It’s likely a ‘good enough’, affordable AI model that makes up with its open weights malleability, what it doesn’t have in terms of frontier AI model chops.
“The model can be customized through Thinking Machines’ first product, Tinker, a cloud-based fine-tuning tool for AI developers and researchers released last year. The goal of Tinker is to allow a developer sitting at a laptop to customize and train large industrial AI models without having to worry about the supercomputing infrastructure underneath.”
“Last month, the hedge fund Bridgewater Associates and Thinking Machines released a report on Bridgewater’s use of Tinker to fine-tune the Chinese open-weights model Qwen3-235B on its own data, leading to a model that Bridgewater said outperformed GPT-5 and Claude Opus on financial document triage, while cutting computing costs by over 13 times.”
“Thinking Machines pretrained it from scratch on 45 million tokens of text, images, audio and video. During post-training—when the model is taught how to behave—Thinking Machines used a combination of distillation, which relies on other AI models, and its own reinforcement learning process.”
“It was trained entirely on state-of-the-art Nvidia hardware. Thinking Machines and Nvidia announced a multiyear partnership in March in which Nvidia invested in the startup, which agreed to deploy at least one gigawatt of cutting-edge chips to train and serve its frontier AI models.”
And of course Thinking Machines is highlighting the cybersecurity safety features of its latest release.
“Thinking Machines said it tested the model for safety, including for risks such as the potential for it to help build biological weapons or aid hackers with cyberattacks, and it performed well. The company said it is still studying how safeguards it built into the model can be tweaked because it is open weights—a safety concern raised in part by some proprietary model developers.”
And the company released its expected AI essay/manifesto, table stakes currently in the global AI models game.
“On Friday, Thinking Machines released its first manifesto, outlining its vision for a future in which AI was decentralized and built on local knowledge. The company, whose CEO, Murati, witnessed the collapse of communism in her native Albania as a child, compared the current dominant AI paradigm of close-source frontier labs to “central planning”—great for bounded tasks like chess and math, but not for the real work humans do every day.”
Overall, it’s a welcome addition to the US open source AI model offerings this AI Tech Wave.
And further cements Nvidia’s central role has a key backer of the next generation of open source AI companies. Stay tuned.
(NOTE: The discussions here are for information purposes only, and not meant as investment advice at any time. Thanks for joining us here)
Happy shopping day. I want to thank all my readers so today I am offering a 50 percent discount on all your insults to me for this already free newsletter....
Three AI stories landed in one news cycle on April 21 — a pre-IPO M&A bet on AI coding, OpenAI’s return to images inside ChatGPT, and a top global law...
