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Sebastian Raschka
@rasbt
ML/AI research engineer. Ex stats professor. Author of "Build a Large Language Model From Scratch" ( & reasoning (
가입 October 2012
1.2K 팔로잉 중    511K 팬
Now we know: The popular Ox Alpha LLM was GLM-5.3-Flash... Compared to GLM-5.2, this new GLM-5.3-Flash model uses: - a Kimi Linear-style 3:1 (super*) hybrid attention pattern with 34 Kimi Delta Attention layers (KDA) and 11 Multi-heat Latent Attention (MLA) / DeepSeek Sparse Attention (DSA) layers; - a scaled-down GLM-5.2-style sparse MoE backbone, going from 744B-A40B to 320B-A18B; - a DeepSeek V4-style mHC residual path with four parallel streams; - plus a native vision encoder (not shown). * "Super hybrid" because both KDA and MLA/DSA are "efficient" components. E.g., Kimi only uses KDA + full attention GQA, DeepSeek V3.2 uses DSA + full attention MLA. PS: Sry for the excessive tech jargon. Explainers on all these components (MLA, DSA, KDA, mhC, etc.) in my LLM Architecture Gallery PPS: Haha, maybe justification for getting that pricey Mac Studio M5 Ultra 256 GB / 512 GB to run this locally...
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Introducing GLM-5.3-Flash - Leading capabilities at a highly competitive price - Natively multimodal with a 1M-token context window - A 320B-A18B model released under the MIT License - Previously previewed as Ox Alpha, running entirely on Chinese AI chips Blog: Available now across all official platforms: Weights: API: Coding Plan: ZCode: Chat: AutoClaw:
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