Thinking Machines just unveiled Inkling 2 Small, a 594B-parameter MoE model with only 17B active parameters built for autonomous agentic coding and visual reasoning. It can run experiments, fix bugs, and refine interfaces using visual feedback in the loop. Full weights are slated to drop under Apache 2.0 next week, but you can already test it on Tinker Playground.
Thinking Machines just launched Inkling-Small, an open-weights MoE model with 276B total parameters and only 12B active. Operating at roughly a quarter of the compute cost, it actually edges out the flagship Inkling across reasoning and agentic coding benchmarks like Humanity's Last Exam. Why it matters: You get multimodal reasoning and a 1M context window without the heavyweight inference tax.
Thinking Machines just launched Inkling, an open-weights MoE model featuring 975B total and 41B active parameters alongside a 1M token context window. Pretrained across text, images, and audio, it lets developers dial thinking effort up or down to balance cost against latency. Why it matters: Open-source builders finally get a frontier-scale multimodal base designed from the ground up for agentic fine-tuning.
Thinking Machines just announced a research preview of native interaction models. Instead of turn-based chatting with external scaffolding, it processes audio, video, and text in continuous 200ms micro-turns paired with an asynchronous background reasoning model. This lets the AI interrupt, listen, speak, and search simultaneously without awkward pauses.
Mark Zuckerberg just explored acquiring top AI startups including Thinking Machines Lab, Perplexity, and Safe Superintelligence to overhaul Meta’s AI strategy. While talks fizzled over price and valuation, Meta is aggressively stacking talent under newly hired AI chief Alexandr Wang.
