Oh and dont sleep on this： Mira Muratis Thinking Machines Lab just released Inkling-Small： a 276B MoE open weight model that activates only 12B parameters per token.
It beats the 41B-active Inkling on Terminal-Bench 2.1 （64.7 vs. 63.8）， HLE （31.6 vs. 29.7）， and SWE-Bench Verified （80.2 vs. 77.6）.
The company says it matches or beats the much larger Inkling on reasoning and agentic coding， while offering native audio and vision， a 1M-token context window， and variable thinking effort.
On-policy distillation plus two weeks of coding RL made the smaller model outperform its teacher on several benchmarks.
Inkling-Small could become a remarkably efficient open foundation for multimodal agents.
Today, we are releasing Inkling-Small. Inkling-Small achieves comparable performance to Inkling at a quarter of its size. It features 276B total parameters, 12B...