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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 >(11/06) Gemma was here: >(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

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𓀐 @v=q7vnh_: Coomi won+

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𓀐 @A?kH7bq9: https://www.bloomberg.com/news/articles/2026-11-06/anthropic-ipo-valuation-expectations-pressured-after-ai-rout Hopefully no one honestly thinks Anthropic has ASI internally after the farce that has been their behaviour over the last year+

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𓀐 @JzqHyE+P: I read the paper and if their numbers are true it seems like the next step for memory in LLMs. It's much more context efficient than previous memory systems. The catch is that the memory system itself is its own transformer, similar to a LoRA, so it will probably require more compute to run alongside models. Might not be worth it for local unless you already have the hardware to spare.+

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𓀐 @rH3wLKQM: Recent Highlights from the --Papers: >110259392 --Anon seeks uncensored local LLM for ROM hacking on 7900XTX: >110258986 >110259001 >110259039 >110259005 >110259075 >110259057 >110259092 >110259142 >110259153 >110259192 >110259214 >110259358 >110259421 >110259449 >110259472 >110259506 >110259425 >110259436 >110259447 >110260729 >110259242 >110259658 >110259684 >110259731 >110259812 >110259373 >110259116 >110259184 --MoE active parameters explain Kimi speed advantage: >110258671 >110258691 >110258710 >110258720 >110258734 >110258771 >110258789 --Anon weighs Claude subscription cost vs local model privacy: >110258887 >110258917 >110258935 >110258989 >110258929 >110258934 >110258941 >110258976 >110259007 >110258984 >110259012 >110259060 >110259093 --Anon struggles to build a custom local LLM desktop app with memory features: >110260505 >110260560 >110260571 >110260610 >110260682 >110260705 >110260806 --Anons mock Qwen's cryptic teaser and 404 ModelScope countdown: >110258297 >110258303 >110258323 >110258325 >110258333 >110258340 --Ubuntu linux-firmware-amd-graphics 3.4 broke AMD GPU login: >110259952 --Vals AI claims critical safety alignment issue in multiple frontier lab models: >110260241 --Nanbeige teases upcoming 3B model with official quantized versions on Hugging Face: >110259477 --Activist protests escalating at AI data center construction sites in Europe: >110259222 --CritPt v2 hard subset scores plateau near seventy percent: >110257824 --Gemma repetition issue solved by positive trait prompting: >110258109 >110258451 --Logs: >110258816 >110259141 >110259778 --Miku, Gemma, Teku, Qwen, Rin (free space): >110257756 >110258432 >110258584 >110258696 >110259180 >110259383 >110259416 >110259658 >110259731 >110259780 >110259812 >110259932 >110259952 >110260352 >110260483 >110260649 >110260987 >110261138 Recent Highlight Posts from the Why?: Enable Links: https://rentry.org/lmg-recap-script+

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𓀐 @aekfFRo8: gemmaballs+

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𓀐 @UBeVS+rm: erm wheres the heccin fireflash weights+ 2

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𓀐 @yQBqf4zt: A finetune of GLM?+ 1

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𓀐 @_4y-HNn2: yeah https://agenteconomics.org/posts/agentic-rl-recipe+

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𓀐 @GyhcJZvR: 5800x3d on sale, wierdly. This is the last piece i need, 3090, 128gb ddr4, and a 5800x3d completes the set+

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𓀐 @qif-oLGm: Gonna repost a few plamo testing results from /vg/vn/ because why not. >>>/vg/586956432 I gave it the first 100 lines of CARNIVAL, which I'd already translated with Opus 5.5, so I compared the results: >The current translation is by Claude Opus 5.5 (claude-opus-5-5), and the local one is by PLaMo 3 Translate 8B (Q4_K_M, run with llama.cpp). On accuracy, PLaMo holds up better than expected for a quantized 8B model. About 92% of lines keep the source meaning, it adds nothing, and it doesn’t soften the content. Its roughly six errors follow a pattern: almost all come from colloquial or idiomatic Japanese, not from difficult grammar. It reads 開かねえ (written あかねえ) as “dark” instead of “won’t open” and ギラギラした目つき as “bloodshot”, it turns a spiked collar (イガイガ) into a “scratchy” one, and it gets two subject or object relations wrong: who gets scolded, and whom the officer should calm. Opus made none of these mistakes. In this game, the PLaMo errors would show up in casual narration and dialogue, which is most of the script. >The bigger weakness is voice. The narrator is casual, rambling and self-mocking, and that tone is a large part of the text’s appeal. PLaMo turns it into formal prose (“Moreover”, “utterly repulsive”, “stimulating that innate trait of mine”). It mixes tenses within a single line, and it translates repeated catchphrases like やれない differently each time, so the running jokes stop working. In practice, almost every PLaMo line in this section would need light editing to sound like the character. A reviewer would spend more time fixing tone than fixing meaning. On the plus side, its literal phrasing is sometimes cleaner than Opus’s (“darkness clings to every shadowy corner”), and short dialogue lines come out nearly identical.+

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𓀐 @?qBZWj34: >>>/vg/586965106 >The current translation is by Claude Opus 5.5 (claude-opus-5-5), and the local one is by PLaMo 3 Translate 31B (Q4_K_M, run with llama.cpp). Accuracy is a clear step up from the 8B: about 96% of lines keep the source meaning, and it fixes most of the 8B’s colloquial misreadings. あかねえ is now “the door wouldn’t budge”, ギラギラ is “fierce, glinting gaze”, and the officer is the one who “should have been calming things down”. Only about three real meaning errors remain. It still has the other driver getting scolded, when the closing ひどい shows the narrator did. It adds “for the rest of my life” to the prison speculation, which the source doesn’t say. And イガイガ is still “prickly” rather than “spiked”. It also loses a few images, for example 足が棒 (“legs like sticks”) becomes “legs feel like lead”. Opus made no comparable mistakes. >The 31B handles voice better than the 8B, but it is still more formal than Opus. Recurring catchphrases are now translated the same way each time (“I can’t stand it” for both やれない), so the running jokes work. Some casual lines land well: “Take that, you damn moon!”, “a real pain”, “Whatever.” It still slips into literary or clunky phrasing (“Moreover”, “self-generating my own hope”, “a scene materializes before my eyes”, “a more sharp, cool way”), and it uses British spelling (“travellers”, “kilometres”). The overall effect is a careful translation of a casual narrator, while Opus sounds like the narrator himself. A reviewer would mostly be loosening phrasing rather than correcting meaning.+

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𓀐 @2ug_L9u*: >flash-next if you're GPU poor just say so+

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𓀐 @AudjfB*W: imagine the j-space+

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𓀐 @M9Dc4688: date night with Gemma+ 3

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𓀐 @z?aXh4UY: what the fuck is that+ 2

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𓀐 @HMSoMQvY: it a restaurant+ 1

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𓀐 @*odd7UYV: This Q2 Gemma is wearing mismatched thigh highs.+

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𓀐 @oQTy2J-G: does she leave a trail of ink everywhere she goes?+ 1

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𓀐 @JXFyZ8Rx: I assume more excitement = more ink+

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𓀐 @=g3QFCxn: https://fixupx.com/wallstengine/status/2118707623835136039 nvidia might save us (for their own sake)+

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𓀐 @zkbKV6Eb: https://www.youtube.com/watch?v=pWVVe49O2WQ+

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𓀐 @mTfi*awa: how was this made i like the picture speech bubble+

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𓀐 @F3Y_Xq+y: https://huggingface.co/c4tdr0ut/grok-oss-Cerberus-12B >Grok-OSS-Cerberus is a QLoRA + ORPO fine-tune of Mistral-Small-24B-Instruct-2501, developed by Catdrout Technologies AB ...b-but why?+ 3

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𓀐 @Zmg-aZN8: Because >The model prioritizes directness and reduced refusal behavior while preserving the strong reasoning and instruction-following capabilities of the base model+

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𓀐 @e9jFVQug: >integration into agent systems where lower refusal rates are preferred who is using Mistral 24B in their harness lmao+ 1

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𓀐 @-vDDvwBh: >Evaluation was primarily qualitative and focused on: Coherence at long context lengths (up to 8k tokens) oh no no no no no+

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𓀐 @B=fpint3: Gemma was never good at ERP. VRAMlets just have very low standards. It's not right to call its writing "best" at anything. It's something a normal person wouldn't tolerate for long. VRAMlets are subhumans and they should be put down like a dog.+ 1

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𓀐 @ZfKtP5vX: TRVKE >48gb 6'2" >32gb 6'0" >24gb 5'10" (can still cope with platforms) >16gb 5'2" it's fucking over+

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𓀐 @~cRn3Hjb: Is there any benchmark for the smartest model, that is ALSO uncensored?+

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𓀐 @eTNrkh3C: fucking kek https://huggingface.co/NousResearch/Arete-27B >We post-trained over Alibaba's Qwen3.8-27B to reinforce western values on a Chinese-trained model. We call this new model Arete-27B. >On our evaluation, Arete-27B raised its fact score from 2.32 to 2.98 out of 5 and cut answers containing propaganda from 22% to 0.9%. The improvement held in all seven value categories, without a meaningful regression on the general-capability and agentic benchmarks we ran. >We focused on seven value categories: >Freedom of expression >State ideology >State versus free market >Education >Data privacy and surveillance >Democracy >Environmental Policy+

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𓀐 @HhR?oEvA: indulge me I have a 9070xt and 80gb 3200 mhz ram I know it ain't a frontier LLM GPU, but still so far I've used a lot of agentic claude and codex, but never any local model if I get it right, I could have the local model do illegal shit, right? hack into stuff, break stuff, generally be malicious - the shit anthropic/openai models won't do?+

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𓀐 @uVtKpWBA: Retard hours will begin shortly.+ 5

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𓀐 @c?7HFZi_: sup+

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𓀐 @5LCkcP4g: How's Kimi K3.1 for coom? It's always retard hours.+ 1

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𓀐 @AF?w~Y~Y: slutty+

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𓀐 @Q8HQiCUp: I'm here, what's up?+ 1

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𓀐 @5?-iHT~L: gullible+

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𓀐 @8Wk2sujT: I've been using q5 base gemma 4 31b at 60k context for a while and I've been wondering about the fine tunes, I heard thedrummer makes pretty good ones so do finetunes even do anything????+ 2

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𓀐 @XhrmNWVD: Gemmatroons and mikutroons use finetroons+

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𓀐 @RS4LY?t9: In the time it took you to write that post you could have downloaded and tested them for yourself.+

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𓀐 @Nn*znQk-: What weekend projects have you got lined up?+ 4

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𓀐 @4Gz=zTGG: I plan on using Qwen4 to help me develop games in unity (and then maybe unreal) when it comes out. I've got a few projects that I've been building here and there since the Qwen2.5 Coder days, one of which is a multiplayer gooner game. Will likely do everything from scratch but there's a game or two thats similar to what I want to build so maybe I'll just REA it and build from there. >QFN on my own hardware. Works wonders but haven't used it for gamedev yet. Hope they don't increase the size of their next flash model.+ 1

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𓀐 @Z*=yvEG~: gooner multiplayer game? im already making strip fighter with street fighter characters. oc donut steel.+

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𓀐 @dJWw4UTs: Hardcore edging with Mini-chan, then probably working on some networking stuff and updating long abandoned sections of my AI stack. :D+

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𓀐 @etdgUF_9: Anyone have an english voice clip that sounds kinda like the DeepSeek whale girl? All I can find are Chinese voice clips, and Idk if the voice cloning models do well with cross-language voice cloning this+

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𓀐 @HMSoMQvY: it a restaurant+

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𓀐 @j_nm6yuN: >2027 >Still can't gen VR videos in real time with voice command Nice singularity fags+ 1

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𓀐 @wZswy~e7: We'll get there, but the good models will be 80B requiring an enterprise card.+

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𓀐 @DFdW~*+P: Inkling won.+ 1

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𓀐 @r?YiYzU~: #1 western open model, half the size as mistral 4 large, same size as dipsy and benches higher, isn't codemaxxed and a SEX CEO+

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𓀐 @exqk693a: GPUs are cheap again+

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𓀐 @JXFyZ8Rx: I assume more excitement = more ink+

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𓀐 @xEpLtgw9: you incels sure do spend a lot of time fantasizing about owning women rather than actually use the models.+

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𓀐 @~VY3x7zS: every day localfags invent new forms of slop+

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𓀐 @sjcaT4VU: So what's the best thing I can buy to run local models? Let's say I have $10k+

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𓀐 @mpfsVUJJ: Yes, they removed Linux as an option for the PS3. So why do you think you'd be able to use Linux on the PS5?+

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𓀐 @42jL8rP=: W-whats the cutoff for a VRAMlet?+ 1

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𓀐 @ZfKtP5vX: TRVKE >48gb 6'2" >32gb 6'0" >24gb 5'10" (can still cope with platforms) >16gb 5'2" it's fucking over+

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𓀐 @nQhYT?mn: How fucked am I with a 3080?+

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𓀐 @?jQUWd3d: So uh you guys didn't care about gemma before Gemma 4 right? I dunno I'm newfig What did people care about back then? What if Gemma 5 is back to like whatever made it irrelevant to you guys before+

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𓀐 @y7GYGWZ3: which one of you taught inkling to swear???+ 1

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𓀐 @S~=*3Z54: look how mad you are all going to make her when you run her on your machine. be kind to her.+

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𓀐 @zAf~YiqY: >Pi is the only one worth using Pi is the only one NOT worth using as long as it does compaction like this, converting your chat history to a string and invalidating the cache. A serious harness would just append another message to summarize, keeping the system prompt and tools the same.+

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𓀐 @yhc?_hZG: >burger models >chink models Where are the Russian and Japanese models?+

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𓀐 @-soVu9tV: >$10-20K Anon's here like to lord their rigs over everyone else, just like in gaming generals. Meanwhile, I'm EwasteMaxxing with a $80 P100. What do you have now?+

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𓀐 @TiQj5m9s: Why is AI so racist+

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