New ModelsOpen weights
Inkling-Small
Thinking Machines releases Inkling-Small: 276B/12B open MoE that beats its 975B sibling on agentic coding
The efficient sibling previewed alongside Inkling ships as open weights: 276B total with 12B active, natively multimodal with an encoder-free architecture (images via hierarchical patch encoding, audio via dMel spectrograms straight into the decoder), and variable thinking effort. On-policy distillation from Inkling plus two extra weeks of agentic-coding RL let it beat the 975B teacher on SWE-Bench Verified (80.2% vs 77.6%) and ARC-AGI-2 (40.1% vs 36.5%), though factual recall regressed hard (SimpleQA 20.6% vs 43.9%). Priced at $0.30/$1.20 per million tokens, roughly 3-4x cheaper than Inkling, with day-zero SGLang, Unsloth GGUF, and Baseten support. Dropped just after the July 30 show aired.
276B / 12B total / active parameters80.2% SWE-Bench Verified, beating the 975B Inkling's 77.6%$0.30 / $1.20 per 1M tokens in/out
New ModelsOpen weights
Inkling
Thinking Machines releases Inkling, a 975B open-weights MoE trained on 45T multimodal tokens
Mira Murati's Thinking Machines shipped Inkling, a 975B-total/41B-active Mixture-of-Experts transformer pretrained from scratch on 45 trillion tokens of text, images, audio and video, released under Apache 2.0. The ThursdAI panel called it the top US open-weights model right now — 41 on the Artificial Analysis Index — with encoder-free native reasoning over text, image and audio and a 1M-token context window. A leaner Inkling-Small (276B/12B active) was previewed alongside, and both run on the Tinker platform at a limited-time 50% discount.
975B / 41B total / active parameters45T multimodal training tokens41 Artificial Analysis Index — top US open-weights model
