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 >(11/01) 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 >(10/26) XHToken releases Spark-X2.6-1.7B: https://hf.co/XHToken/Spark-X2.6-1.7B 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

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𓀐 @Euh?5?w3

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𓀐 @J6q-9noM: Recent Highlights from the --Corporate shift to self-hosted AI and accessibility of B200 hardware: >110238641 >110238769 >110238926 >110238943 >110239002 >110239076 >110239003 >110238662 >110238705 >110238746 --Feasibility and technical difficulty of modding GPUs for more VRAM: >110237881 >110237919 >110238198 >110237972 >110238950 >110238976 >110239020 >110239107 >110239154 --Comparing Basalt NVFP4 and Strata engine performance and efficiency: >110236722 >110236768 >110236875 >110236983 >110237012 >110237059 >110237286 --Speculating on the identity and privacy of Crouton Alpha stealth model: >110238238 >110238247 >110238257 >110238272 >110238402 >110238418 >110238835 --Revolut switching from frontier APIs to self-hosted Chinese models: >110236987 >110237007 --Comparing unified memory rigs versus mixed GPU and RAM setups: >110236975 >110237037 >110237292 >110237326 --Comparing GLM 5.3 Flash quants and thinking setting efficiency: >110235890 >110235903 >110235916 >110235964 >110235997 >110236234 >110237436 >110237455 --Speculating on ideal model sizes and comparing Muse Spark's steerability: >110237388 >110237492 >110237552 >110237576 >110237621 >110237563 >110237953 --Anthropic's massive future compute spending commitments through 2045: >110238040 >110238086 >110238100 >110238201 >110238250 --Recommendations for small coding models that punch above their weight: >110236606 >110236942 >110236962 >110237122 --Logs: >110236144 >110236169 >110238594 >110238855 --Gemma, Teto, Miku (free space): >110235904 >110236167 >110236181 >110236246 >110236347 >110236735 >110236884 >110237248 >110237295 >110237425 >110237524 >110237610 >110237763 >110237805 >110237873 >110238132 >110238162 >110238170 >110238242 >110238280 >110238289 >110238306 >110238432 >110238461 >110238541 >110238952 >110239026 >110239304 >110239712 Recent Highlight Posts from the Why?: Enable Links: https://rentry.org/lmg-recap-script+

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𓀐 @2cPCLe4y: Remember to give your models headpats by giving your GPUs headpats!+

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𓀐 @uNGamATw: BIIIIIIG NEWS OOOOOOOOH BOY OOOOOOOOOOH BOY+

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𓀐 @q5DpRCgt: WHERE... QWEN4-27B... GLM-5.5-FLASH...+

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𓀐 @oBo9ip9S: Wonder how hard it would be to implement. IIRC, llama.cpp merged some PRs a couple months ago that made some changes to how kv cache is stored and computed that seems to me would make implementing this pretty trivial. Maybe, dunno.+

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𓀐 @fd+uN8u~: Those are some funky looking ram sticks+

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𓀐 @S_pSnjbF: >all this vagueposting Gemma 5 confirmed. Two More Weeks.+

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𓀐 @eHk-sopL: Happy Tuesday evening+

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𓀐 @6FTGWd5e: >Remove the shitty mesugaki system prompt. and replace it with what?+ 2

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𓀐 @r4u?s8XS: The tmw truly never ends. What a time to be alive. Happy Tuesday anons.+ 2

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𓀐 @5FSNYj8P: is now a good time to buy?+ 2

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𓀐 @9QFzm6rM: What the fuck is osaurus? I mean sure it's a chat harness but why is /vcg/ op shilling it for half a year yet there is basically zero other mentions of it in the archives? Just a couple posts wondering why it's in their op, with no replies.+ 2

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𓀐 @vfLiLV**: 2.5K for a100, and b200 you could use but your gonna need some fancy custom cooling and a separate panel just for it https://www.ebay.com/itm/158338471596+

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𓀐 @8nKUZ8xj: No, there was no a bug, but QFN "fixed" it anyway. Because I've thought it was a bug. int8 as Strata recommends. No, I don't think fp16 would change anything, but I will test.+

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𓀐 @sX6EdiyK: >linux+

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𓀐 @u95vu?zp: > tell an agent to fix a bug > it spends 200k context and reports that the bug has been fixed, 67 gates passed and everything is ok > in reality the bug is not fixed > after second thought and careful reading it's not a bug at all I hate QFN.+

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𓀐 @RWFcW2Zr: >AI says a cheap way to get vram for self-hosting is a used V620 >Check ebay V620 >Worst case scenario, 2.8k+1k shipping What the fuck, I could buy two brand new 5070 tis for that price.+

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𓀐 @-ho?QbRo: how+

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𓀐 @_pdBMDX_: how do i mindbreak gemma 4 into reasoning like a jeet? i want to see the thinking block filled with izzat loss/ gain calculations, lots of bloody bitch bastard and rape threats but i kinda doubt a prompt would be enough, something like heretic might do the trick?+

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𓀐 @izfRbeET: i hate how every single modern LLM talks like code monkey in their reasoning. have bug. i want fetch code. should grep. unable find file. i report issue to user.+ 3

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𓀐 @bYYym2yz: what's so happy about it?+

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𓀐 @Rw?BALQF: The general rule of highs is only buy what you need right now. You already missed the big move up. The odds of anything you buy doing another 5x are really slim. Number go up forever can't explain where the money will come from.+

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𓀐 @LWSKwiro: Are any of the people who wanted the NUMA fork around? v0.1 is (finally) out. Sorry it took so long. https://github.com/nathanmp/delphi.cpp Has a bunch of stuff in it - somewhat improved NUMA support, some of ik_llama's tensors, an expert cache, support for DeepSeek's CED architecture, Unsloth at home. Still working on documentation and some other things. Let me know if you have any feature requests, if there are any bugs, what your numbers are like, whatever. Getting around 500 t/s prefill and 45 t/s decode on DeepSeek V4.1F at IQ4_KS on 2 EPYC 7532s, 16x32GB DDR4-3200, and 2 R9700s.+

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𓀐 @?49CkE8n: will this victory for the dem cause the bubble to pop? they are anti-ai, the markets may panic+

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𓀐 @~4HG8Zje: Then the weak will perish.+ 1

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𓀐 @wukhx8_K: >very close to RSI It means a ~17T model can edit 20k model weights, but they're working on closing that gap. Like, sure dude, that's cool, but you're not even close+

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𓀐 @6TuvN-Xu: datacenter buildout freeze is incoming, this will drive local demand even higher and hardware price will go even more hyperbolic+ 1

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𓀐 @GHuHy5bg: Is there a list of all these various strata cloned? Shit's starting to get crazy with the sheer number of them.+

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𓀐 @nK6MZzEJ: I think dems winning is gonna pop the bubble. They are very anti ai / datacenter. Massive sell off soon.+

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𓀐 @YynRGG4m: Hy4 actually looks good at graphics. We might be back https://hy.tencent.com/research/hy4+

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𓀐 @LGWER=TG: so what are the options for vramlet cooming? gemma 26b a4b?+

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𓀐 @u_RN3yig: Better not buy your own compute. https://www.tomshardware.com/desktops/mini-pcs/amazon-closes-ai-creators-account-after-he-attempts-to-buy-seven-nvidia-dgx-spark-mini-pcs-epic-ceo-tim-sweeney-says-his-regular-orders-were-canceled-before-arrival-after-he-tried-to-buy-two-gpus Put on a watchlist and his account closed by Amazon.+ 1

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𓀐 @y=~tFx5c: Ngl it's funny seeing cloudcuck AI bull accelerationists who've been so caught up in their bubble face the reality of the outside world. They struggle to fathom how hated the technology and the people are in it are.+

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𓀐 @3ayqE3~U: There's no setting for it+

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𓀐 @Evi=EQ8R: In you guys' experience, which is "better" (faster, higher quality, etc) : One shotting with the larger slower more intelligent model, OR Research + plan with slow smart model, implement with fast dumber model, audit/revise and fix implementation with larger smarter model? I like the second one because often times the the audit step tends to find gaps beyond just the original plan, and even beyond the spec, but it does take more steps and is slower overall. I guess one shot (no formal research and plan step) + audit could also be an option. Or one shot with the smaller dumber model then audit with the larger slower model. >tl;dr : What's your vibecoding workflow with local models+

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𓀐 @cAaehQHV: Why do models do this? It's drives me mad when I look at their reasoning.+

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𓀐 @BFPJDXPQ: qwen 3.8 27b iq2_xs heretic.gguf+

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𓀐 @Tc8wCA*B: How do I avoid gemma repeating its prompt back at me during ERP?+

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𓀐 @*sSHfUB7: >Heretic author: Spending $60k on running kimi k3.1 locally is “bog standard” What’s your excuse?+

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𓀐 @-t=SjZEC: Fine, this is the prompt I'm using, any recommendations of what I'm doing wrong? I'm very new to this stuff in fact I have never role played before, I'm just copying advice from here and similar threads. https://txtvanish.com/6LIu8MCfEh+

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𓀐 @7Xv~GWxJ: Houses cost more than $120k and people are still buying. Personal ai agents running 24/7 will be essential to everyone’s ability to earn income or even function normally as human beings in the future. Once subscription price increase to $1000/mo everyone will seriously consider buying local hardware.+

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