Mira Murati's Thinking Machines Lab released Inkling， its first open-weights model.
A 975B-parameter （41B active） open-weights model with multimodal reasoning and adjustable effort.
- A 1M-token context window lets the system process unusually long documents and workflows.
- Trained on 45T tokens spanning text， images， audio， and video from scratch.
- Users can raise reasoning effort for difficult tasks or reduce it for speed.
- The release matched Nemotron 3 Ultra on Terminal Bench using roughly one-third as many tokens.
- Strong Native audio and vision processing. Inkling scored 91.4% on VoiceBench and 82.0% on CharXiv RQ with Python.
- Large-scale reinforcement learning used more than 30M rollouts and steadily improved reasoning scores.
Fine-tuning support arrives through Tinker， while full weights are available through Hugging Face.
Inkling-Small activates 12B parameters and sometimes matches its larger sibling on core evaluations.
Thinking Machines Lab's latest valuation was at $12B， following a $2B seed round. Nvidia later invested an undisclosed amount， while reported $50B talks never produced a confirmed valuation.