Thinking Machines bets on efficiency over size with its second model, Inkling Small

Thinking Machines bets on efficiency over size with its second model, Inkling Small Matthias Bastian View the LinkedIn Profile of Matthias Bastian Jul 31, 2026 Thinking Machines, the AI lab from former OpenAI CTO Mira Murati, has released Inkling Small. According to Artificial Analysis, the open-weights reasoning model scores 40 on the Intelligence Index, one point below Inkling (41), with less than a third of the parameters (276 billion total, 12 billion active). AA says no open model of equal or smaller size scores higher. Inkling Small beats its bigger sibling on several coding and reasoning tests, including Humanity's Last Exam (32% vs. 30%) and GPQA Diamond (89% vs. 87%). It falls behind on agent-based tasks and factual knowledge but is far more token-efficient, averaging 24K output tokens per task compared to 45K for Deepseek V4 Flash and 78K for GPT-5.4 mini. Mira Murati's Thinking Machines ships a smaller, more efficient reasoning model that punches above its weight. | Image: Artificial Analysis The model handles text, image, and speech inputs, has a 256K-token context window, and ships under Apache 2.0. Weights are on Hugging Face, and users can fine-tune it in the browser via Tinker Playground. Thinking Machines positions its models as a foundation for fine-tuning with users' own data. Some see this as the next frontier in AI.AdDEC_D_Incontent-1Ad AI News Without the Hype – Curated by Humans Subscribe to THE DECODER for ad-free reading, a weekly AI newsletter, our exclusive "AI Radar" frontier report six times a year, full archive access, and access to our comment section. Subscribe now Source: Thinking Machines | Artificial Analysis Ask about this article… Search