Search: “r-localllama”

I didn't know my set up was outperforming nearly everyone until reading another discussion where people were struggling getting half of that speed with half the context on the same hardware. I benchma

Github: https://github.com/OpenEuroLLM/ComplexKDA HuggingFace: https://huggingface.co/collections/openeurollm/complexkda Arxiv: https://arxiv.org/abs/2609.24797 Authors: Julien Siems*, Riccardo Grazzi

There's quite a lot of public anti-AI sentiment at the moment, but a lot of the most common concerns and objections have to do with the politics, economics and ethics of datacenter-based AI. So, when

I asked this back in 2025, but the AI landscape has changed a lot since then. Not looking for the usual ChatGPT, Claude, Gemini, Midjourney, etc. I'm curious about the lesser-known tools that you actu

https://preview.redd.it/ybwqqbrst0rh1.png?width=811&format=png&auto=webp&s=1e40c5b53e304caf2a10efa2baa6f998b9a9a0bb MiMo-V2.6-Distill-Qwen-9B is a 9B agentic model developed by Xiaomi MiMo through sup

This sub is, needless to say very niche and skewed towards the high end. There are tons of extremely high end setups here with multiple gpu's etc. Even 24GB is out of reach of most people financially,

https://preview.redd.it/5aon65uosrqh1.jpg?width=1000&format=pjpg&auto=webp&s=cd21ce0648b0ffa5dc07e66718a230f1f91d8a53 I have a GMKtec EVO-X2, it doesn't have oculink nor pcie slots, but it does have 2

This experiment is live, you can inspect all the internal reasoning, memories, attempts here: https://artificium-covering-experiment.gr.bio/ The problem that the agent is trying to solve is a covering

I’ve been working on making small models more capable at agentic coding and work, because most people in the world don’t have the sort of hardware needed to run 3.8-27B, or even 35B-A3B or 9B dense, a

I decided to do this experiment to see what would be the ability of an LLM model to, in a single shot, transfer the knowledge it may or may not have about that artist/brand/designer/animator to a comp

Laya is an open-weight (Apache 2.0) 'System 1' decision model from Convai Innovations, built by Nandakishor M as an open alternative to TypeSafe's closed Jev API. Instead of generating text, it takes

Quote: DeepSeek is training a 2T-parameter model and plans to eventually build an 8T-parameter model. https://x.com/wallstengine/status/2101982843656388644 Current DeepSeek models: Flash parameter cou

Having a blast with Qwen Image 2.1 on my M2 Macbook Pro with 32GB RAM, even though it takes 16 minutes to complete the recommended number of iterations with the resolution reduced to 1024x1024. And th

# the What An engine to run Gemma 4 31B on blackwell under massive concurrency and rather specific workload patterns. I've been waiting for someone to do ninfer but for gemma, and, well, ended up havi

Hi all! After all the jev hype I wanted to try by myself and got qwen3.8 27b to mix-and-match open implementations on top of ninfer, and to be honest I'm quite impressed with the results, latency is n

I want to try using AI to find possibly overlooked interventions for irritable bowel syndrome (IBS) and create a cocktail of interventions that AI thinks would give the highest expected benefit, attac

What if you don’t need a new model to get Jev-style decisions? I built hearim(헤아림. hea-a-rim. not Here, I am.. lol), an open-source gateway that turns ordinary local or hosted LLMs into a Jev-compatib

https://preview.redd.it/d7brwofkhuqh1.png?width=1400&format=png&auto=webp&s=9a0079ebc2710faff9a73378dac58c6dd67e3cec link: https://huggingface.co/Altworld/Hemmingway-1 submitted by /u/paf1138 [link] [

Hey everyone! It has been quite a while since the last SupraLabs model - but today we've something special for y'all: Supra2-IMG It's a 100M parameter DiT text-to-image model trained entirely from scr

Since there’s no comparison chart on the model page, I asked Perplexity to compare it against some relatively small open-weight models in a similar size range. Here are the results. Upd. Terminal-Benc

Sorry for the pretentious name, I know, I know.. It just contains all the pieces I would like to see a AGI model to have, and I can't stand the temptation. Before throwing rocks at me, please take a g

Small, free finding. I use local Qwen models for typed decisions: a state plus a question with fixed allowed answers, and I read the probability of each answer from the logits of one forward pass inst

https://preview.redd.it/nulsv53o8vqh1.png?width=4500&format=png&auto=webp&s=74765dbd409f4c221640f9f6000a685f6fdbb242 Spent weekend benchmarking the Splash engine (by Incoai) and extending its architec

I shipped something I've been building for the last few weeks : phantom-kv , a refusal-removal system for large language models that doesn't touch a single weight. Instead of editing the model, it loa

I have been reasonably satisfied with my single R9700 (32GB) as I can run practical quants of Qwen 3.8-27B at good speeds, as well as other similar models in its weight class (Gemma 4 is still my go-t

https://huggingface.co/yandex/AliceAI-Foundation-80B-A3B-Base It's not a Qwen3 finetune, it's actually its own fully custom architecture. No Llama.cpp support yet sadly (Also note that this model is N

You can simply run any GGUF with llama.cpp with n_predict=1 and n_probs=10, disable reasoning, and prompt it such as 'If the following email is spam, respond with 1, if not spam, respond with 0. Do no

ZCode is now open source, and the reported security issues have been addressed. Source code: https://github.com/zai-org/ZCode The repo includes its desktop app, web workspace, backend, Agent CLI, and

This weekend, I did a fun experiment to create something similar to Jev. I LoRA fine-tuned Qwen3.5 4B using a mix of publicly available datasets and synthetic data. For the synthetic data, I used Deep

Jev from TypeSafe AI got me thinking about non-autoregressive decision engines, so I built a small proof-of-concept called AES to test the concept locally on open weights. It uses Qwen/Qwen2.5-1.5B-In

So this jev thingy is getting kind of big... tbh it seems overhyped by a large margin, but here we are. Not that its bad, just feels like we usually ignored larger things... Anyway to the point of thi

I know cloud subscription plans are not exactly the core focus of r/LocalLLaMA, so I want to be clear about why I’m posting this here. I’ve been building my own local text-based RPG/game harness and u

Hey everyone, After wrestling with hardware and engine issues for days, I finally got Qwen 3.8 Next running properly on my multi-GPU rig. Thought I’d share the setup journey, benchmarks, and thermal r

I forked llama.cpp to implement Declarative Attention (arXiv:2609.02737, Google DeepMind and KAIST AI). The model declares in its own output which context chunks it needs <focus magic_chunks='N'>), an

i have been running local models as browser agents on an m5 macbook pro, 128gb, all through mlx, no cloud. first i just wanted to know which one was faster at real browser work, so i gave gemma 4 31b

I gave Jev, Laya, a finetuned ModernCE-base-nli and a finetuned Qwen3.5-4B the controls to Doom. Thanks to TypeSafe AI for Jev access. The video lines up the starts of four separate games with the sam

I’ve spent basically the last 8 hours testing different models on the exact same web-development prompt, and I finally finished. The whole point of this nine-hour test was that which local model match

Typesafe's new model, Jev is all over the internet, this sub etc as a new classifier model. Then an AI dev posted here how they'd done something very similar, and made a new model, Laya. https://www.r

After seeing u/Nandakishor_ml’s post introducing Laya, I wanted to see how fast it could run in a standalone C++ implementation. Credit to u/Nandakishor_ml for the architecture, training and open-sour

Hello! So, yesterday i tried out Gemma 4 26B A4B QAT Q4_K_XL from here with Q4_0 MTP model in Pi agent. Suddenly, it became the first model to actually pass my simple test with HTTP server in C++, whi

Hey r/LocalLLaMA! I just released PromptDeck v1.1.0 and wanted to share it here since this community is basically the reason it exists. What it is: an open-source desktop studio (Tauri + React) for pr

Meet Qwen-Image-2.1, the most balanced and cost-effective image generation model in the Qwen-Image series! Now open weights! 🎨 A unified model for both generation and editing, delivering top-tier qual

Overclocking the CMP 170HX 40GB I was able to get the memory bandwidth from 1,386.2 GB/s to 1,890.1 GB/s, that's a +36.4% increase. Qwen 3.8 27B token generation jumped from 110 T/S to 202 T/S, same c

So my brother and I both use LLMs for coding. I've started using a local GLM 5.3 Flash instance - q4 qat. My brother uses GPT-6-Astra as his daily driver. He has mentioned repeatedly to me that his ap

​ ​I wanted to share a quick update and performance video running the full Moonshot AI Kimi K3 (moonshotai/Kimi-K3) model across my 16x GB10 cluster. ​Getting a 2.8T parameter model running smoothly r

Sharing my successful experience here. My setup: RTX 5060 Ti 16GB (x16 PCIe slot) RTX 3060 12GB (x4 PCIe slot) RAM: 32GB CPU: Ryzen 5 5600 OS: Linux So I have a total of 28GB. Average tk/s: 50, and th