{"contentHash":"297b2c729cee5fd3fd445e4df199d16b5e02d3d791ff7e0778cb4263477aa27f","protocol":"bitcoin","authorPubkey":"a1ee2a0e44a0f1e83a95c0e9713f38c8093051b7ac30290ba3186dc88cfc5e2d","text":"/lmg/ - a general dedicated to the discussion and development of local language models. News >(11/06) PLaMo 3 Translate released: https://preferred.jp/en/blog/tech/plamo-3-translate-weight-release >(11/05) Baidu releases ERNIE-5.5-Flash-Base 280B-A14B: https://ernie.baidu.com/release/ernie-5-5-flash-base >(11/04) Ricursive Ripple 65B dense model released: https://www.ricursive.com/ripple >(11/04) MoonshotAI Kimi K3.1 Pro released on HF: https://hf.co/moonshotai/Kimi-K3.1-Pro >(11/01) Longcat-2.5 released: https://longcat.ai/blog/longcat-2.5 News Archive: https://rentry.org/lmg-news-archive Links: https://rentry.org/LocalModelsLinks Official /lmg/ card: https://files.catbox.moe/cbclyf.png Getting Started https://rentry.org/lmg-lazy-getting-started-guide https://rentry.org/lmg-build-guides https://rentry.org/IsolatedLinuxWebService https://rentry.org/recommended-models https://rentry.org/samplers https://rentry.org/MikupadIntroGuide Further Learning https://rentry.org/machine-learning-roadmap https://rentry.org/llm-training https://rentry.org/LocalModelsPapers Benchmarks LiveBench: https://livebench.ai Programming: https://swe-rebench.com Agentic Coding: https://deepswe.datacurve.ai Context Length: https://github.com/RecapAnon/NoLiMa GPUs: https://github.com/XiongjieDai/GPU-Benchmarks-on-LLM-Inference Tools GGUF VRAM Calculator: https://hf.co/spaces/NyxKrage/LLM-Model-VRAM-Calculator Sampler Visualizer: https://artefact2.github.io/llm-sampling Token Speed Visualizer: https://shir-man.com/tokens-per-second Text Gen. UI, Inference Engines https://github.com/lmg-anon/mikupad https://github.com/oobabooga/text-generation-webui https://github.com/LostRuins/koboldcpp https://github.com/ggerganov/llama.cpp https://github.com/theroyallab/tabbyAPI https://github.com/vllm-project/vllm https://rentry.org/custom-uis","topicHash":"913c62c2ee31793c7e8517600dbc8f0c337afae133700a128a7d8ffb8a21c93e","topicName":"technology","parentHash":"e1e861ed31e83729a8762ccd9dc0210c83d58cdb674a3a04315dd8f837210edf","costSunk":"0","biasSupport":0,"biasOppose":0,"biasVouch":0,"biasNull":0,"blockHeight":null,"confirmations":0,"timestamp":"2026-11-06T20:05:23.470Z","tripFp":"0d70cbe089fb","viewCount":0,"powDifficulty":0,"relation":0,"ephemeral":true,"nonce":"51af5a82a5538347","sig":"387caa2a3acd07303d388e2ba485b0d3a233c553f74d78169c34f1c28c52a6b14980c92ef58a96476bad148f832e1731c9833acd213e35d2b1f1bb85ee9f9011","ephStamp":{"blockHashHex":"00000000000000000000d541103f1d49fd6b0e382efbbbabfc5b4093dea4b5c5","nonceHex":"be2b000000000000"},"replyCount":32,"chainReplyCount":0,"vaporReplyCount":32,"clusterSize":44,"receiptHeight":974850,"expiryHeight":979170,"authorMarks":{"since":"2026-11-06T10:04:06.075Z","via":"sight","inscribed":0,"likes":0,"biases":0},"lang":"en","servedBy":{"host":"6af58b1822e0cabfe57d76540f745d059b438f489a796ec6a705c6540233845e","t":"2026-11-08T19:38:59.766Z","sig":"3e33a0c185c0b71fbdc4e712bee9eb7a5e6dbd9c15ac666b3b60bb80e5592c44bffbe66618b912ee8941dd99f493f562fae88f926f3964f099d173b2f1b68a52","h":"0000000000000000000149fda0f179108ae890d4c4e6c5c08289bcf8490e054f"}}