Thinking Machines Launches Inkling 2 Small: Big Agentic Gains, Heavy Token Use
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Thinking Machines has released Inkling 2 Small, scoring 31 on the Artificial Analysis Intelligence Index - their plan to release its weights would make it the highest-scoring open weights model developed outside China based on current rankings Inkling 2 Small is launching as a proprietary model, available first-party through @thinkymachines' Tinker platform and Tinker Playground, with weights to be released at a later date. Its score is up 18 points from Inkling Small, with ~4x as many output tokens per task. It matches @GoogleDeepMind's Gemini 3.8 Flash (high) and surpasses @XiaomiMiMo's MiMo-V2.6-Pro on the Artificial Analysis Intelligence Index v5.0.1. Key takeaways: ➤ Large gains over Inkling Small, especially on agentic tasks: AutomationBench-AA rises from 5% to 46% and FrontierCode 2.0 from 5% to 25%. HLE-Diamond also rises from 12% to 29%. ➤ Different coding strengths from Claude Sonnet 5.5 (medium): Inkling 2 Small scores 25% on FrontierCode 2.0 vs. 11% for Claude Sonnet 5.5 (medium), but 13% on Terminal-Bench 4.0 vs. 30%. ➤ Creative agentic scores above Claude Haiku 5.5 and Grok 4.7 on AA-3D: Inkling 2 Small also scores above Gemini 3.8 Flash on both AA-3D and…

Inkling 2 Small posts big agentic gains for $1.18 per task but uses about 4x more output than its predecessor. Weights are promised, not yet released, so plan around API access first.
- token — The chunk of text a model reads and writes in — roughly three-quarters of a word — and the unit AI usage is billed in.
- mixture-of-experts — A model built from many specialist sub-networks where only a few activate per token, giving big-model capability at small-model running cost.
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