Today we are introducing our second model generation with Inkling 2 Small. It is a Mixture-of-Experts model with 594B total parameters, 17B active, and supports image inputs and variable effort. Inkling 2 Small far surpasses our previous models’ scores on the Artificial Analysis Intelligence Index with a score of 31, reflecting gains in performance on agentic coding, vision, knowledge work, and reasoning.
The increase in capabilities comes from improvements made at every step of our training process, including more efficient pre-training and a large, unified RL run. Inkling 2 Small will initially be available through Tinker, with closed weights, following the approach we outlined in a safe path to open weights. We intend to make the full weights available under an Apache 2.0 license next week after the completion of external safety testing and red-teaming.
Inkling 2 Small is more capable across the board than our first generation, particularly in long-horizon autonomous work. Its vision and agentic capabilities enable it to incorporate visual feedback to iteratively build and refine websites, games, and 3D designs with interactive elements. The model was trained with RL on hundreds of thousands of long-horizon coding tasks across multiple agent harnesses and context-compaction strategies, resulting in a model that is both stronger at coding and easier to use inside real agent loops.
Source: Hacker News · Summarized by HeadlinesBriefing