Ep 820: The Most Important AI Model You’ll Probably Never Use That Just Dropped
July 16, 2026
AI Summary
5 min readWhen Thinking Machines Lab—the company founded by former OpenAI CTO Mira Murati—released its first model, Inkling, in late July 2025, it landed with a benchmark score of 41 on the Artificial Analysis Intelligence Index. That is nearly 20 points behind frontier leaders like Fable 5 (60) and GPT-5.6 Soul (59). But the company's own release notes were unusually candid: "Inkling is not the strongest overall model available today. Instead, a combination of qualities make it a good open weights base for customization." That honest positioning is the whole point. Inkling is a 975-billion-parameter mixture-of-experts model with 41 billion active parameters, a 1-million-token context window, and native multimodal support for text, images, and audio. It was pre-trained on 45 trillion tokens. And it is American-made open-weight—a category that, until now, China had dominated. The model itself matters less than what it signals: the re-emergence of fine-tuning as a practical enterprise strategy, powered by frontier models that have finally become smart enough to teach smaller ones.
Why an American Open-Weight Model Unlocks Procurement
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What you'll learn
- 1 (00:00) **Episode Introduction & Thesis** - Host Jordan Wilson introduces Inkling, the new open-source model from Thinking Machines Lab, led by former OpenAI CTO Mira Murati.
- 2 (01:26) **The Core Thesis: Why Inkling Matters** - Frontier models are now powerful enough to fine-tune smaller, practical models, potentially reviving the fine-tuning category for enterprise AI.
- 3 (03:57) **Context: The Enterprise AI Overhang** - Jordan explains that frontier models are often "too much" for many enterprises, creating a market for bespoke, middle-of-the-pack AI.
- 4 (05:27) **Inkling Model Details** - The model is a 975-billion parameter mixture-of-experts transformer with 41 billion active parameters and a 1-million token context window.
- 5 (07:51) **The Real Product: Tinker** - Thinking Machines Lab's core business is "fine-tuning as a service" through their platform, Tinker.
- 6 (10:34) **Benchmarking Inkling's Position** - Inkling scores a 41 on the Artificial Analysis Intelligence Index, about seven months behind the frontier (leaders at 59-60).
- 7 (13:37) **Strategic Reset #1: American Open Weights** - Inkling provides a credible American alternative to Chinese open-source models, reopening procurement for many enterprises.
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Guests on this episode
Show Notes
You've probably never heard of Inkling.
It's the newest (and first) model from Thinking Machines Labs, and it could very well be a small snowball that picks up major momentum in today's enterprise AI landscape.
If you haven’t heard of Thinking Machines, they’re led by Mira Murati, the former CTO at OpenAI.
The big bet with Inkling?
The future of AI could be using smaller models fine-tuned and optimized for smaller tasks.
Will it work?
Tune in live as we dive in.
The Most Important AI Model You’ll Probably Never Use That Just Dropped -- An Everyday AI Chat With Jordan Wilson
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Topics Covered in This Episode:
- Inkling AI Model Launch Overview
- Thinking Machines Lab Leadership Highlight
- Inkling's Multimodal and Agentic Capabilities
- Open Source vs. Proprietary AI Models
- Enterprise Procurement with American AI Models
- AI Fine Tuning as a Service (Tinker)
- Benchmark Scores: Inkling vs. Frontier Models
- Customization and Model Shopping for Enterprises
- AI Token Costs Driving Model Efficiency
- Bridgewater Case Study: AI Model Customization
- Frontier Models Enabling Efficient Fine-Tuning
- Future Trends: Specialized Small Language Models
Timestamps:
00:00 Inkling: A new AI model release
05:43 Inkling AI model details
09:08 China's dominance in open source AI
11:48 Launch and model updates discussed
15:21 Concerns over using Chinese open-source models
19:06 Training smaller AI models
20:22 Using GPT for AI Model Training
23:54 Predicting Rise of Small Language Models
28:38 Choosing the right AI model
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