Hemendra Shekhawat
630 posts

Hemendra Shekhawat
@Dormang0
Learning by doing, observing and conversing.

if you wanna get a $20 monthly plan for vibe coding definitely don't get Claude, not even Codex. you should get: - GLM 5.1 - Minimax 2.7 - Kimi 2.6 - or Deepseek v4 All these will give you so much more usage for the buck, and you won't get stopped at the start or mid-session.


My man @uwukko is building my favorite browser (helium) on an M1 with 16gb RAM. I’m donating $2,000 to help him get a better Mac. If one of my rich friends wants to match it, he can get 64gb. If two do, he can do 128 👀

Xiaomi MiMo-V2.5 is now officially open-sourced! MIT License, supporting commercial deployment, continued training, and fine-tuning - no additional authorization required. Two models, both supporting a 1M-token context window : • MiMo-V2.5-Pro: built for complex agent and coding tasks, ranking No.1 among open-source models on GDPVal-AA and ClawEval • MiMo-V2.5: a native omni-modal model with strong agent capabilities A model's value isn't measured by rankings alone — it's measured by the problems it solves. Let's build with MiMo now! 🤗 Weights: huggingface.co/collections/Xi… 📄 Blog: #blog" target="_blank" rel="nofollow noopener">mimo.xiaomi.com/index#blog




Why does Muon outperform Adam—and how? 🚀Answer: Muon Outperforms Adam in Tail-End Associative Memory Learning Three Key Findings: > Associative memory parameters are the main beneficiaries of Muon, compared to Adam. > Muon yields more isotropic weights than Adam. > In heavy-tailed tasks, Muon significantly improves tail-class learning compared to Adam. Paper Link: arxiv.org/pdf/2509.26030 A thread 🧵






Me watching vibe coders crash out all over X











