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GLM-5.2 on 8xB200: the deployment math nobody spells out - NVFP4 + 2x TP=4 replicas should beat TP=8 by ~2x. Full config guidance inside.
We have 8xB200 nodes and users keep asking us how to serve GLM-5.2 on them. Our engineering team wen…
Anthropic Research - "Verbalizable Representations Form a Global Workspace in Language Models"
submitted by /u/cuolong [link] [comments]…
local already feels good enough
This is specifically for coding, technical planning, and hardware setup. _____ The only times Qwen …
Gepard : 0.6B streaming TTS built for real-time dialogue - 20× realtime factor, ~50ms time-to-first-audio, vLLM-native, Apache 2.0
We just open-sourced Gepard 1.0, a TTS model built for real-time conversation. It’s streaming-first:…
I tested freshly merged DFlash in llama.cpp on Qwen 3.6 27B Local AI win. 4.44x faster at 36K context. Here are my findings RTX 6000 PRO.
Hey guys, A month ago I posted my MTP benchmarks here (3.34x on Gemma 4). DFlash support just merged…
Qwen3.6-27B - Effect of KV quantization on KLD - Q8, Q6, Q5 (bartowski)
Lower is better - Quantization increases from right to left I recently made a post here about how I …
mistral.rs v0.9.0: up to 1.8x faster CPU decode than llama.cpp on x86 and ARM!
https://preview.redd.it/nuk5rxceptbh1.png?width=1448&format=png&auto=webp&s=300344dd4c6552379e8536b8…
I tested Anthropic’s new Jacobian Lens on open models, then it turned into a local-model hallucination router
Anthropic dropped their Global Workspace / Jacobian Lens paper yesterday, and I thought it was too c…
Liquid AI - Antidoom (the doom loop remover)
https://x.com/liquidai/status/2074494130126811473 Today we release Antidoom, an open-source method t…
Beijing IS NOT looking at curbing overseas access to China's top AI models (Debunking the Reuters report)
The Lie Reuters' headline and main narrative: " Beijing is looking at curbing overseas access to Ch…
llama.cpp: Hy3 PR + GGUFs
Early stages as the model was just released yesterday, but seems to be working already. Yay! Getting…
A trained fast-weight memory: a 3M-param transformer installs never-trained rules at inference, forward-only — where test-time training transfers nothing (single RTX 3090, fully reproducible)
I'm an independent researcher (single self-funded RTX 3090). I just released a preprint (Zenodo for …