Mira Murati’s Thinking Machines Releases Inkling, Its First Open-Weight Model
On July 15, 2026, Thinking Machines Lab—founded by former OpenAI CTO Mira Murati—released Inkling, a 975B-parameter open-weight MoE multimodal model (41B active) with a 1M-token context window, full weights on Hugging Face, and fine-tuning via the company’s Tinker platform.
TLDR
Thinking Machines Lab on July 15, 2026 released Inkling—its first foundation model—as open weights. The company primary describes a Mixture-of-Experts transformer with 975B total parameters, 41B active, a context window up to 1M tokens, and pretraining on 45 trillion tokens of text, images, audio, and video. Weights are on Hugging Face; fine-tuning ships on Tinker, with API/inference partners including Together, Fireworks, Modal, Databricks, and Baseten. The lab is explicit that Inkling is not the strongest model available—it is a customizable base.
What Inkling is
From the July 15 Thinking Machines post (“Inkling: Our open-weights model”) and corroborating TechCrunch, Axios, WSJ, and Fortune coverage the same day:
| Spec | Detail |
|---|---|
| Architecture | MoE transformer; ~DeepSeek-V3-style expert routing (256 routed + 2 shared; 6 active routed) |
| Scale | 975B total / 41B active parameters |
| Context | Up to 1M tokens (Tinker options at 64K / 256K at launch) |
| Modalities | Native text, images, audio; video in pretrain mix |
| Training | 45T tokens; hybrid Muon/Adam; large-scale async RL (>30M rollouts cited) |
| Companion | Inkling-Small preview (276B total / 12B active)—weights later after testing |
| Positioning | Broad generalist for fine-tuning; controllable thinking effort |
The company demoed an agentic loop in which Inkling fine-tunes itself on Tinker (lipogram experiment: no letter “e”), underscoring the product thesis: customization over raw leaderboard rank.
Business and competitive framing
Thinking Machines does not sell Inkling as a closed chat subscription rival to ChatGPT or Claude. Revenue and GTM center on Tinker—enterprises (including Bridgewater, per contemporaneous Fortune reporting) that want to post-train on private data. Valuation context from press: roughly $12B-class after earlier fundraising. Murati’s bet is that as closed-lab prices and lock-in rise, open bases plus fine-tuning become the enterprise default for specialized work.
Why this story matters
Inkling lands the same week China open-weight labs (Kimi K3 the following day) and U.S. closed giants trade punches on GPT-5.6 and Fable. A Murati-led lab choosing open weights first—and admitting it is not SOTA—reframes the U.S. open-source story from “Meta Llama only” to a second pillar: customizeable multimodal bases with a commercial fine-tune stack. That is a structural competitor to both rent-only frontier APIs and pure weight dumps without ops tooling.
Sources
- Thinking Machines Lab: “Inkling: Our open-weights model” (July 15, 2026) — primary specs, architecture, Tinker availability, Hugging Face.
- TechCrunch, Axios, Wall Street Journal, Fortune / Bloomberg same-day coverage of Inkling’s open-weight launch and enterprise positioning (July 15, 2026).
Featured Image Alt Text
Engraved Inkling model badge with open-weight key and Tinker customization lattice for Thinking Machines Lab July 15 launch.
Tags
Thinking Machines, Mira Murati, Inkling, Open Weights, Tinker, Multimodal, Models, July 15