Inkling 开源

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.  > **引用原帖 Mira Murati (@miramurati):** > Our first model, Inkling. Trained from scratch, weights are open, fine-tunable on Tinker today. > https://x.com/miramurati/status/2077455974743593100