Thinking Machines Releases Inkling 2 Small, Intelligence Index Score of 31 Rivals Gemini 3.8 Flash

Thinking Machines Lab released its second-generation model, Inkling 2 Small, on the same day it launched a new funding round. The model uses a sparse mixture-of-experts (MoE) architecture with 594B total parameters and only 17B activated, supports image input and variable reasoning intensity, and scores 31 on the Artificial Analysis Intelligence Index v5.0.1—an 18-point improvement over its predecessor, Inkling Small, matching Gemini 3.8 Flash (high) and surpassing Xiaomi's MiMo-V2.6-Pro.

Technically, the model underwent four-stage pre-training and 9 days of joint reinforcement training, with significant gains in agentic tasks: AutomationBench-AA rose from 5% to 46%, FrontierCode 2.0 from 5% to 25%, and HLE-Diamond from 12% to 29%. Coding ability is mixed: FrontierCode 2.0 scores 25% versus Claude Sonnet 5.5's 11%, but Terminal-Bench 4.0 is only 13% versus 30%. Pricing is $0.30/$1.00 per million input/output tokens, with cached input at $0.03. The model is initially available as closed weights via the Tinker platform, with plans to open full weights under Apache 2.0 next week after external safety testing and red-teaming.

If the open weights materialize, it would become the highest-scoring open-weight model outside China, significantly boosting the open-source ecosystem's competitiveness. Meanwhile, Thinking Machines is raising $50 million at a $40 billion pre-money valuation, down from a previous $50 billion attempt, indicating cautious capital markets. The parallel release and fundraising highlight the lab's dual pace of technical iteration and commercial expansion.