Thinking Machines Lab, the AI startup founded by former OpenAI CTO Mira Murati, has unveiled its first in-house AI model, Inkling. Designed as a response to the growing demand for open-weight AI systems, Inkling gives developers and enterprises greater control over how large language models are trained, adapted, and deployed.
Unlike closed AI models such as ChatGPT from OpenAI and Claude from Anthropic, which are primarily accessed through hosted products or APIs, Inkling’s weights are available for outside developers to download, modify, and fine-tune. This open-weight approach allows organizations to customize the model for their specific needs, rather than relying on a controlled environment.
What is Inkling?
Inkling is a 975 billion-parameter LLM with a one-million-token context window. However, it does not use all 975 billion parameters for every task. Thanks to its mixture-of-experts architecture, it activates around 41 billion parameters per task, making the model more efficient. The model was trained from scratch on 45 trillion tokens of text, image, audio, and video, and it now generates textual outputs such as code, structured data, and formatted diagrammatic artifacts.
According to Thinking Machines, Inkling is a generalist model developed for agentic tasks, coding, reasoning, and structured outputs. The company states, “That breadth matters for customization and real-world use: different users need models that can adapt to very different workflows, not just excel on benchmarks.” The model can also be configured to adjust its “thinking effort,” allowing it to trade off speed and reasoning depth depending on the use case.
How Inkling Differs from ChatGPT and Claude
The primary distinction is openness and customization. Closed frontier models like ChatGPT and Claude are accessed through controlled apps or APIs and must be used in a controlled environment. Inkling, by contrast, is an open-weight base model that enterprises can tune using Thinking Machines’ model customization platform, Tinker.
This makes Inkling more attractive for organizations that want to create domain-specific AI systems with their own processes and information. However, it also means companies take on more responsibility for safety, alignment, and security after fine-tuning the model.
Performance and Limitations
Thinking Machines notes that Inkling performs well for coding and reasoning but acknowledges that it is “not the strongest overall model available today, open or closed.” Instead, the company positions Inkling as the first step in a broader model family. Alongside the main model, it also showcased Inkling-Small, a lighter model with only 12 billion active parameters that offers lower costs and faster response times.
Inkling represents a significant shift toward more open and customizable AI, giving enterprises new options for building tailored AI solutions.
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