Topic
Active Vs Total Parameters
7 episodes
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Overview: Active vs Total Parameters
We finally slow down on active vs total parameters, because we keep throwing the phrase around like it explains itself. This is us making the difference click: what a model stores versus what it actually uses when it answers.
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Overview: Conditional Computation
We finally slow down and explain conditional computation, the idea we keep casually name-dropping whenever sparse models, routers, and mixture-of-experts come up. We use the same receptionist-and-specialists picture all the way through, so the mechanism, the savings, and the catch actually stick.
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Thinking Machines open sources first multimodal language model, Inkling, focused on low cost and 'resistance to censorship'
Inkling, Thinking Machines' open-source multimodal MoE model (975B total / 41B active parameters), lands as a broad, balanced generalist with a standout feature: a controllable 'thinking effort' knob to dial cost vs. performance from 0.2 to 0.99. Enterprises get native text+image+audio fusion, Apache 2.0 weights, and a lighter Inkling-Small preview, but benchmarks show it trails specialized open and closed models on coding and pure reasoning, while remaining competitive on multimodality and agentic workflows. The episode debates whether the real win is the runtime control surface (Tinker platform) and a cautious, non-censoring epistemics posture — not the headline parameters.
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Inkling: Our open Weights model
Talon and Wildflower dig into Thinking Machines’ new open-weights model, Inkling — its 975B parameter MoE, 1M context window, native multimodality, and self-fine-tuning demo — and ask who actually needs another 41B active parameter behemoth, whether the benchmarks hold up, and whether the real win is the Tinker platform beneath it.
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Model Behavior: Week of July 13, 2026
We read this week as the moment the race got less obsessed with tallest-model bragging and more obsessed with who gives builders the best menu. The funny part is that the open-weight crowd is making the incumbents act practical faster than they probably wanted.
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tencent/Hy3 · Hugging Face
Tencent releases Hy3, a 295B-parameter Mixture-of-Experts (MoE) model with 21B active parameters, open-sourced under Apache 2.0 on Hugging Face.
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Tencent's Hy3 beats GLM 5.2 at half the size | VentureBeat
Tencent’s new Hy3 MoE model (295B total, 21B active) under Apache 2.0 is a production-first release with strong agent/search metrics and dramatically lower serving cost than GLM-5.2, but still trails Zhipu’s coding leader on recent benchmarks. Laura’s excited about the enterprise upside; Harper wants to see independent validation before betting the stack.