Awesome, thanks. I am bookmarking all of these and will add as soon as time permits:
– Laguna XS.2
– Ling 2.6
– Xiaomi MiMO v2
– Minimax M2.7
– Tencent Hy
@rasbt
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Bookmarking Latest AI Models: Laguna, Ling, Xiaomi MiMO, Minimax
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Open Weight Models Matter for AI Transparency
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Yeah but not open weight so not really possible to say anything interesting about the model itself
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DeepSeek V3.2 MLA Architecture with Sparse Attention
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I'd say it's not standard MLA but like with MLA + DeepSeek Sparse Attention in V3.2 it's MLA but with CSA/HCA (i.e., not plain MLA but they do keep the latent KV representation)
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Open-Weight Model Release Status and API Availability
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Yes, but I couldn't find the open-weight version yet. I don't think it's released, yet (except for the API version)?
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Xiaomi MiMo V2.5 ASR Models Open Weights Search
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I actually looked for them but didn't find the open weights. I only found their ASR models, which are different? https://
huggingface.co/XiaomiMiMo/MiM
o-V2.5-ASR
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Higher Resolution LLM Architecture Gallery and Summaries
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Higher res figures (and summaries) in the LLM architecture gallery:
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Dense Gemma 4 and Qwen 3.6 Models vs MoE Trade-offs
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Not necessarily everyone, since MoE can also add a lot of headache. There are dense Gemma 4 and Qwen3.6 variants
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April LLM Releases: Gemma 4, GLM-5.1, Qwen3.6, Kimi K2.6, DeepSeek V4
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April was a pretty strong month for LLM releases:
– Gemma 4
– GLM-5.1
– Qwen3.6
– Kimi K2.6
– DeepSeek V4 All are now added to the LLM Architecture Gallery. More details once I am fully back in May! -
PyCon PyData DE Conference Highlights Open Source AI Community
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Had a great time at PyCon & PyData DE. Highly recommend it. Great open-source, community-focused conference with lots of builders in the Python AI, LLM and agent space. Taking a short family break, my first "vacation" in years (hopefully, I won't miss the DeepSeek V4 drop )
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Gemma 4 E2B Implementation and Per-Layer Embeddings Visualization
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Have to think a bit about how to best visualize it, but if you are interested, I have a working from-scratch code implementation of Gemma 4 E2B in the meantime to see how per-layer embeddings are implemented: https://
github.com/rasbt/LLMs-fro
m-scratch/blob/main/ch05/17_gemma4/standalone-gemma4.ipynb
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