Thinking Machines Lab Releases Inkling: A 975B-Parameter Open-Weights Multimodal MoE With 41B Active Parameters And Controllable Thinking Effort
Thinking Machines Lab just released Inkling, their first model trained from scratch, weights are open, fine-tunable on Tinker. The lab pitches it as a base for customization. What is Inkling? Inkling is a Mixture-of-Experts transformer with 975B total parameters and 41B active. It supports a context window of up to 1M tokens. Pretraining covered 45 trillion tokens of text, images, audio, and video. Inputs accept text, images, and audio; output is UTF-8 text only. The research team also
Thinking Machines Lab released Inkling, an open-weights artificial intelligence model with 975 billion total parameters that can process text, images, and audio as inputs while producing text outputs. The model uses a Mixture-of-Experts architecture where only 41 billion parameters are active at any given time, allowing it to balance capability with efficiency. A key differentiating feature is "controllable thinking effort," which lets users adjust how many tokens the model spends reasoning about each task, making both cost and latency tunable rather than fixed. The model was trained on 45 trillion tokens of multimodal data and performs competitively on various benchmarks, with deployment options available through multiple frameworks and hosted APIs.
Explainer: What Is a Mixture of Experts Model and Why Does It Use Fewer Resources?
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