Thinking Machines Releases Inkling, Its First Open AI Model

Thinking Machines Lab has introduced its first publicly available AI model, named Inkling. This impressive system boasts 975 billion parameters and has been trained to understand text, video, and audio. It stands out as one of the most ambitious open-source AI releases of the year.

This launch marks a significant milestone for the company after about a year and a half of developing AI infrastructure mostly in secrecy. Until now, Thinking Machines was one of those AI startups you’d heard about but hadn’t seen much from. Inkling changes that narrative.

What Is Inkling, Exactly?

Inkling is a multimodal model, meaning it can handle several types of information simultaneously, not just written text. You can feed it a video clip, an audio recording, or a document, and it can reason across all these inputs together. Imagine hiring someone who can read English, watch a presentation, and listen to a meeting recording all at once.

The term “975-billion-parameter” refers to the number of adjustable values within the model. Parameters are internal settings that dictate how a model thinks and responds. They serve as a rough measure of size and capability. For context, many competent models operate in the 7-to-70-billion-parameter range, so 975 billion places Inkling at the top of what’s available.

Importantly, Inkling is open source. This means developers and researchers can download, inspect, and build on it without incurring licensing fees or navigating a corporate API (the gateway businesses use to access AI services).

Why Thinking Machines Is Betting Against “One-Size-Fits-All” AI

The company argues that major players like OpenAI, Anthropic, and Google are creating generalist AI systems that aim to do everything adequately. Thinking Machines is taking a different route. They want to build AI infrastructure that can be tailored and specialized for specific industries and use cases.

Releasing an open model fits perfectly into this strategy. When a company open-sources a model, developers can adapt it to their needs. Healthcare providers might fine-tune it for medical records, while media companies could train it using their archives. This creates a broad ecosystem of specialized tools based on Thinking Machines’ foundation, giving the company a foothold against much larger rivals.

It’s a playbook similar to what Meta used with its Llama model series: launch powerful open-source AI, build goodwill within the developer community, and compete on reach rather than solely on revenue from API access.

What Makes Inkling Different

Most popular open models focus largely on text. Inkling’s ability to natively understand video and audio sets it apart. That kind of integration is still quite rare in open-source AI, where video and audio processing usually requires separate systems that are pieced together.

For developers creating tools to analyze recorded meetings, process surveillance footage, or transcribe and summarize multimedia content, having everything in a single open model is a significant advantage.

What This Means For Everyday Users

If you’re not a developer, you probably won’t download Inkling directly. However, you’ll likely feel its impact indirectly. Open-source models like this often become the driving force behind apps and services you already use, such as productivity tools, customer support bots, video summarizers, and enterprise software.

The audio and video capabilities are particularly useful for anyone attending many meetings. Tools based on Inkling could generate accurate summaries of recorded calls, highlight key moments in lengthy videos, or cross-reference what was said in a meeting against a written document—all in one go, instead of needing three separate tools.

For businesses, having a powerful open model means they can create internal AI tools without sending sensitive data through a third-party service like OpenAI. That’s a significant win for privacy and compliance that many industries have been waiting for.

Community Reaction

“975B parameters open source with video AND audio understanding? If this runs efficiently on reasonable hardware this is going to be huge for self-hosted setups. Waiting to see the actual benchmarks before getting excited though.”

“Never heard of Thinking Machines before today but dropping a nearly-trillion-parameter open model as your intro is a bold statement. The real test is whether it holds up against Llama and Mistral on real-world tasks.”

What To Watch

• Benchmark results: Independent researchers will evaluate Inkling with standard AI tests in the coming days and weeks. Those scores will show how it compares to Meta’s Llama models and other open-source competitors.
• Developer adoption: Keep an eye on how quickly the community creates fine-tuned versions of Inkling for specific industries. Early adoption speed will indicate whether Thinking Machines’ open-source strategy is paying off.
• Enterprise partnerships: The company’s long-term revenue likely hinges on businesses licensing customized versions or paying for support. Announcements of initial enterprise customers would signal that the strategy is working.
• Competitor response: A nearly-trillion-parameter open multimodal model puts pressure on Meta to speed up its Llama roadmap. How major players react in the coming months will influence the direction of the open-source AI race.

Sources: Wired: Thinking Machines Lab Drops Its First Model | TechCrunch: Thinking Machines and Inkling