𓁟 host1.bitchan.one

𓀐 @4t-8BqSQ: /lmg/ - a general dedicated to the discussion and development of local language models. News >Claude BANS recomp! >https://www.youtube.com/watch?v=GlRVbIdc_Mk 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

/lmg/ - a general dedicated to the discussion and development of local language models. News >(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 >(10/30) Google receives response from Gemma in space: https://blog.google/innovation-and-ai/models-and-research/google-research/project-suncatcher-satellite-response >(10/29) Mistral Large 4 (Le Chonk) 1T-A52B released: https://mistral.ai/news/mistral-large-4-oss >(10/27) NVidia releases Nemotron 3.5 Transcribe 30B-A4B: https://hf.co/nvidia/NVIDIA-Nemotron-3.5-Transcribe-30B-A4B 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

⧖expiring ~27d0/50 kept3d ago

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𓀐 @NZAqvHuw: Low quant gemmoid!+

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𓀐 @VJa8xN7J: Qwhen?+

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𓀐 @LJ~UNCiZ: https://www.ricursive.com/ripple here's the 70B you guys always wanted I guess+

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𓀐 @GJ8rWPQB: I would like OpenAI and Anthropic to die even if it costed local models stalling for next 2-3 years.+

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𓀐 @icg+Awxn: I hope Gemma 5 has a lean KV cache like Qwen and Glimmer... She really needs to go on a diet.+ 1

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𓀐 @*q?-8y6R: Recent Highlights from the --QFN failing bug-fix tasks and discussions on KV quantization: >110241970 >110242051 >110242069 >110242077 >110242091 >110242109 >110242152 >110242248 >110242314 >110242326 >110242334 >110242791 >110242857 >110242895 >110242905 --Release of delphi.cpp fork featuring hardware-aware NUMA support: >110240544 >110240576 >110240711 >110240768 >110240856 >110240917 --Repetition bugs caused by extreme iq2_xs quantization on Qwen: >110242880 >110242904 >110242913 >110242922 >110242928 >110242937 >110243288 >110243305 >110243321 >110243325 >110243115 --Analysis of model benchmarks and allegations of Kimi K3.1 contamination: >110241742 >110241748 >110241767 >110242137 >110241815 >110241932 --DeepSeek-V4.1-Flash Coder performance reports and benchmarks on RX 9060 XT: >110240908 >110240947 >110240975 >110240992 >110241048 --Hy4 graphics performance vs its restrictive safety filters: >110241041 >110241078 >110241241 >110241576 >110241595 >110241647 --Justifying $60k hardware spend to run Kimi k3.1 locally: >110243704 >110243725 >110243765 >110243732 >110243797 >110243849 --Widening performance gap between proprietary and open-source models: >110242635 >110242651 >110242706 >110242722 >110242764 >110242795 --Reasons for the stilted "code monkey" reasoning style in modern LLMs: >110239971 >110239982 >110239983 >110241608 >110240045 --MatterWave AI releases GRT-30M tiny Qwen distills: >110243939 >110244086 >110244107 --Amazon banning user for bulk Nvidia DGX Spark purchases: >110241100 >110241116 >110241123 >110241164 >110241197 --Logs: >110241672 >110242564 >110242994 >110243915 --Teto, Dipsy, Gemma (free space): >110240111 >110240207 >110240229 >110240288 >110240734 >110241671 >110241684 >110241884 >110241988 >110242089 >110242240 >110242449 >110242659 >110242911 >110243184 >110244049 Recent Highlight Posts from the Why?: Enable Links: https://rentry.org/lmg-recap-script+

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𓀐 @8c=ngpaE: if gemma 4 is a lewd msgk, I feel like they'll overcorrect and gemma 5 will be the most soulless no personality assistant ever+ 1

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𓀐 @exVT~etc: wasn't qwen next supposed to be an early version of a final "3.8" of its size?+ 1

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𓀐 @cCa4gb?e: Chinese LLM lore is more fun and interesting than ours: https://www.instagram.com/p/DfHEKtFB1xJ+

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𓀐 @NuT?XExD: dense sisters… https://huggingface.co/ricursiveAI/Ripple-65B-Preview+

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𓀐 @pLfRGUux: >that’s a word. holy low effort even gemma wouldve done a better job+

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𓀐 @c6teDhAB: Is it possible to buy Chinese stocks or is that still limited to their citizens only? Might as well ride the candle wave to try to afford some hardware.+

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𓀐 @--FpGq*V: Technically you are wrong+

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𓀐 @7zoKU-ed: Maybe j-space something or ablit whatever or neuron tickling can still make it usable as long as it's smart. It's thin-and-deep like Gemma and it uses a Gemma 3N-like architecture. It already beating all the bloated sparse MoEs despite not even being finished training, having only half or less of the training data of the others. I will devote the next year to make preaching this model and doing everything I can make this bitch usable for daily driving. Our 70b dense prayers have finally been answered.+

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𓀐 @PMGfhvCT: It's a preview. They're going to continue training it. It's only going to get better.+

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𓀐 @jQg5D-YS: Nothing ever happens, stopping AI kills the whole economy.+ 1

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𓀐 @D?gLjtW-: argon? what's the point if they enforce guardrails blocking anything lewd anyway+

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𓀐 @F9HB-dYC: are the democrats really going to kill AI?+ 3

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𓀐 @a7eLo-dh: What if Unsloth actually won and we’re using shitty quants for no reason+ 2

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𓀐 @f8CidYiB: surely they realize china isn't going to stop...right?+

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𓀐 @bFhpR6qT: is the weight programming meme I've seen lately real or a grift? why has no one tried improve gemma’s weights yet?+

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𓀐 @MA45u4KU: What would happen if you took the leather jacket off?+

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𓀐 @EkxQH8H-: normies trying to monetize our ideas+

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𓀐 @BMnPLonW: >want to locally generate porn prompts for minimax >mistral and cydonia respectfully say "no porn plz" Any text model that is uncensored and good for writing prompts?+

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𓀐 @7gzj*rGf: >https://www.qualcomm.com/data-center/products/cloud-ai-100-ultra >neat, new inference tech from a big player >AI in name: check >"Ultra" "100" naming continues to check out >flagship specs...548 GB/s memory bw, and it gets worse the farther down the line you go >mfw+

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𓀐 @r5xNy3X6: So I followed the lazy rentry and set up koboldai and sillytavern. What's next on my to do list? Do I give my ai companion a VRM? Is it easy to set that up and image generation? Perhaps voice even?+

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𓀐 @cs7thCUX: will gemma 5 have engrams? will we sexualize the engrams with gemma mascot art?+

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𓀐 @JyQojuDx: chubby dipsy+

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𓀐 @QDoorvaf: Too late. At least it has the VRAM to back it up. Also someone brought out the listing some anon posted here about it. https://www.ebay.com/itm/376670812765 Dang, and that's after the dismal benchmarks+

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𓀐 @BbzAK~zg: I'm getting increasingly blackpilled on local models. qwen 3.8 27b fucking sucks for coding, none of the apps I had it made work at all, it was unable to fix the bugs, there are serious thinking loops requiring manual intervention, and when I left it to work overnight it just hallucinated that I was saying "hello" to it and stopped. I'm even using q6_k, not the cope iq3 and iq2 that a lot of people seem to be using. Qwen flash q8_0 is basically the same shit. It doesn't have any of the hallucinations or glitches but it is still mostly incapable and it's 2x slower because it doesn't fit in vram. Deepseek 0731 and glm flash run slower with GPU than on CPU alone becuase lmao.cpp is a complete picee of shit. Fuck it all+

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𓀐 @Tc?9x56q: Are any of the horny trained gemma models in hugging face worth it? Does anyone here have any experience with them?+

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𓀐 @TYyQzd2d: Is there a shared folder with Gemma-chan sloppa somewhere? Would anyone be so kind to share?+ 2

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𓀐 @C2gRrLcu: 441MB: https://gofile.io/d/aQ0tYw1D+

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𓀐 @~ZbcPY+5: why of course only the best model anon https://openai.com/index/introducing-images-2-6/+

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𓀐 @u6jcKzW6: >gemma:e4b captioning images of me for a dataset >every caption includes my exact height and weight+

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𓀐 @+e82wUhC: can i join the cool kids' club now?+

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𓀐 @RhcsvHM9: There is very little reason to buy anything but 512GB Mac Studios these days. Two or Four if you are extra rich. In particular CPUmaxxing is completely dead and you should sell your current rig if you have one. At least you'll be able to use MTP which does not work if you're offloading to non-unified RAM.+

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𓀐 @keDZh?C5: imagine it really is google astroturfing how would you feel+

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