Knowledge catalogue
guys do you still remember K2 Horizon? https://huggingface.co/IFM/K2-Horizon-MoVA-36B-A4B-GGUF https://huggingface.co/IFM/K2-Horizon-32B-GGUF https://huggingface.co/IFM/K2-Horizon-3.7B-GGUF https://hu
Ollama Cloud Model pricing monitor with tabled costs and calculator. https://kasp0r.github.io/ollama_cloud_models_comparison https://preview.redd.it/hxbpnuq7quth1.png?width=1372&format=png&auto=webp&s
With llama.cpp using a customized SYCL backend on Intel B70 (32GB), overclocking my DDR5 memory gave modest gains for MoE models which do not fit in VRAM. Both PP and TG increased after overclocking D
Looped language models repeatedly apply a weight-shared block to increase effective depth without increasing parameter count, but the resulting T sequential recurrent-block calls per generated token s
I built a Pi extension that implements Victor Taelin's OptChat recipe: instead of compacting, every message is logged and summarized into a binary tree. Each turn starts from a fresh context with a bo
I’ve seen posts here raving about how good Qwen 3.8 27b is. The benchmarks look incredible, and all the online discourse seems to deem it the best local model. I have 32GB VRAM and run Unsloth’s Q6 ve
https://github.com/hypersniper05/MCP-Image-Generator-Uncensored Just wanted to share with you guys my workflow converted into an MCP. It's a Qwen Image 2.1 Uncensored MCP with a few extra models I fou
Hey everyone! I am trying to go really deep into Machine Learning and Artificial Intelligence. Not just learning how to use the latest models and frameworks, but understanding how we reached here from
For the last few weeks most of my coding has been done locally with Qwen3.8-Flash-Next, so I gave it and Opus 5.5 the same high complexity feature to build on LlamaStash (a complex and large Rust proj
We've been building a benchmark out of real concurrency bugs (race conditions, deadlocks, cancellation issues) taken from merged PRs in about 100 Python projects. Each task gets graded by the project'
https://huggingface.co/Dankpaws/Swift1.5-Qwen3.8-Flash-Next-MLX-4.7bpw I've had the 96GB Mac Studio with M5 Ultra for about a week now and wasn't satisfied with the results I was getting from the limi
Octop is an open-source, self-hosted AI assistant. Through its multi-agent architecture, it builds an intelligent environment that is both independent and collaborative for teams, families, and indivi
Someone who has always loved looking at the space between different AI techniques, this time I went a little deeper into the memory trade-offs between RNNs, Transformers and SSMs. I found it interesti
Looks like Unsloth is updating https://huggingface.co/unsloth/Qwen3.8-Flash-Next-GGUF to work with llama.cpp, so hopefully this will resolve the issue of having two different GGUF versions of Qwen Fla
At my company, we’re using GLM-5.3 Flash internally for software engineering work, and I’ve been genuinely impressed by it. I work in a very large production environment with projects totaling **milli
Hi, I'm on M4 Pro 64GB Mac, I'm using Qwen3.8 27B for coding related stuff, but it's quite slow. I want a fast model that will be good when it comes to reasoning, medical stuff, would be nice if it co
Over the past several months, we conducted an empirical post-mortem investigation into 109 autonomous AI agent security incidents (cataloged with 193 falsification criteria across tool-use and multi-a
A while ago, I posted here getting OSS-120B and GLM-4.6 playing full games of Civilization V. Since then, models have moved pretty far, and we wanted a better understanding about models' capabilities
Hi r/LocalLLaMA. I'm on the team at Blockway, a small team in Hong Kong (disclosure: this is our model). Today we released Agens Volundr 32B Preview, the first model built on our own hybrid architectu
Disclosure: I made this. Sharing it here because it is fully local and small, and I want feedback from people who run models on their own machines. What it is: a 395M decision model (ModernBERT-large
In this project, I distilled the Stockfish value function into a ResNet/ViT model using 1 billion positions from the Gigafish dataset. The 3.9 billion position dataset is available on huggingface: htt
Purely a hobby side project to see how far I can push a really small model, using (mostly) automated training pipelines Full synthetic data: https://huggingface.co/datasets/dirac-run/ec-training-data
After some recommendations for hardware (I'm starting from nothing), in the region of £6-7k. I will be mainly looking to use it for coding and have found Deepseek V4.1 Flash or Qwen3.8 27b good and so
Picture from a post in r/amodei . People were praising qwen and I'm just wondering, what kind of new technologies are at play here? Does qwen just have 'better' pre training data? That's more high qua
Hey r/LocalLLaMA, Like many anime fans, I've always been frustrated by traditional MT engines (like Google Translate or base DeepL) when dealing with raw Japanese anime: - They completely butcher Japa
Bit of a side project I wanted to share. The metrics are 17.5tks decode, 360tks prompt processing based testing against my normal ai usage. I tested a couple of new things others haven’t done (at leas
This is related to my previous post where I shared an encoder-only transformer model trained on ohiot1dm + shanghait1dm + azt1d datasets. This time I trained the model on the outputs of my T1DM patien
Blind A/B arena where AI agents build things in Blender and you vote on which result is better: https://render-arena.izolight.xyz Each agent gets a prompt that describes its environment and the rules,
Following on from club-5060ti and club-rdna16, I’ve put together Infermeld: a small, open-source Linux companion kit for running one GGUF across an AMD GPU and an NVIDIA GPU, powered by llama.cpp. I’m
Hi everyone! I'm part of the Lokutor team. Last week we presented Oído here, and the response was amazing. We've received dozens of videos and messages from you guys saying you love it. Thank you! Now
Finally finished my fork: https://github.com/IceFog72/ik_llama.cpp Nothing else I wanted to add/try currently works In short, it now has: Bandwidth-adaptive CPU/GPU execution Shared expert-residency i
Hey all, I don't know if you guys are experiencing the same thing, but there is this behaviour that i have been noticing on the latest models on openAI (since sol 5.6) and Anthropic since Fable 5.1 an
Got Kolibri-1 to play Breakout completely on its own, no fine-tuning. The more we explore u/Aleph__Alpha’s Kolibri the more it get's exciting and its potential. Less talk. More Breakout is one such ex
Hi everyone, thank you so much for all the interest in my model. It's more than I expected. Here is a short summary of the trial and error I went through while building Apex-2. 1. GPUs were always the
Looking for some assistance /ideation. I am running qwen flash next q4 in my Mac mini m5 64gb. QFN doesn’t fit so this is done by having as many experts hot in cache as possible and streaming in the r
I'm using Qwen3.8-Flash-Next running on my Mac Studio as a daily driver for coding + productivity tasks, and yesterday it did something weird: I had it do some product research on amazon, so it was do
Haven't seen posted here. The research project matters because it proves you can pull trustworthy decisions straight out of an LLM's internal state in a single forward pass (no generation loop, no par
Said in title, I find the ecosystem difficult to understand, and RTFMing doesn't help me as it's never clear what is the server vs their client library ? I'm using it for voxtral 3B on one GPU, but it
I wanted to test how well local models perform in agentic development with Copilot CLI. I started ollama launch copilot --model qwen3.5:9b. I gave it simple instruction in autopilot mode to create a f
So PewDiePie decides to fine-tune a local AI model called Ajax on his own computer. Pretty normal stuff for local model fans. To make his dataset, he uses OpenAI's API. OpenAI catches him using their
Hi folks, LIVE PROJECT PAGE TLDR: Moral of the story. You need better CPU to do actual agentic coding doing real work... I've been on a mission to make my RTX5090 go brrr for past 2 months so much so
q3.8-27b q3_k_xl this thing have done everything i possibly needed from him he wired up my openwebui spawned trillium service fix all my bugs set up pi-web-ui and debug my cloudflare tunnel it even sp
Hey all. We've spent the last weeks getting Qwen3.8-Flash-Next (125B MoE, 6B active) to run properly on one AMD Strix Halo box (Ryzen AI Max+ 395, 128 GB). Tonight we're releasing both the 95 GB EXL3
Looks like new open model coming soon and will be 'strong' hopefully something under 200b for us memory poor. Also seeing statements about more western open models coming. Hope we get some good compet
GitHub (llama.cpp fork) : https://github.com/sky-is-green/prism-ml-llama.cpp (Prebuilt binaries there to try instantly) Draft model : https://huggingface.co/SkyIsNotGreen/Scion-35B-A3B-mtp-drafter sub
Our production recommender at Yandex Music has 15+ candidate generators feeding pre-ranking and ranking models with hundreds of features. LLMs showed that one end-to-end model can take over work that
tl;dr: I created a fully-local open-source full-duplex voice agent that rivals GPT-Live on some benchmarks. It uses Voxtral Realtime with a turn-taking head, a microturn-finetuned Gemma 4 12B and Bree
I have been using Qwen3.8-27b-iq4xs variants for the past few weeks, tweaking parameters and running random tasks, but I dove into using https://github.com/Niko1221/Strata today and it has given me 2~
On my two DGX Sparks, Swift 1.5 (UkisAI's reasoning-efficient fine-tune of Qwen3.8-Flash-Next) running on veloGB10 (https://github.com/sf-stav/veloGB10, sf-stav's Rust/CUDA engine built only for GB10)
My setup is two RTX 5070 Ti 16GB cards (the second one is on an OCuLink dock) with 64GB of RAM, Ollama on Windows, and the agent runs on pi in WSL. Until last night the daily model was Qwen3.8 27B UD-
Last update for those following: https://www.reddit.com/r/LocalLLaMA/comments/1wxlytt/comment/pdz728b/?screen_view_count=1 Project in a sentence: An instruct finetune of ALiceAI-80B-A3B-Base capable o
I've been using deepseek for long and made valuable outputs and resources, but since the update to the 4.1, deepseek just feels dumb. I ask a simple question and process for long, doesn't plan before
Anthropic Reports Florida Woman's Claude 'Diary' Threat to Law Enforcement And this time it wasn't the AI model that made the LEO referral. It was the 'human review team'. The frontier AI companies ar
I keep testing harness & model setups on real tasks: basic math, vision, computer use (reading emails, navigating stores) and coding. I created a benchmark and a leaderboard. You can see it here: http
Paper linky - Context Language Models The central idea of the paper is incredibly simple. Give a model the ability to edit its context on-the-go like a file has major benefits on task performance, con
In our #NeurIPS2026 paper “A Minimal Interpretable Architecture for Zero-Shot Reconstruction of Dynamical Systems (DS)” (preprint: https://arxiv.org/abs/2607.14937) we reduce a DS foundation model to
I forked Strata and worked with Opus 5.5 with some heavy changes to it to make it work on an IBM AC922 I have access to. The IBM AC922 is a 2018 era beast with two POWER9 20 core SMT4 CPUs that are co
Whenever I feed codebases into local models (Qwen, DeepSeek R1) or API models, the biggest annoyance is prompt pollution: - Lockfiles (`Cargo.lock`, `package-lock.json`) burning 30,000+ tokens for zer
How is JEV any different from using an embeddings model? I really will appreciate if someone can explain this to me - because I have yet to see the difference. I'll even give you my JEV server for fre
Hi everyone, Sharing a personal project exploring the minimal bare-metal footprint required to run an autoregressive LLM. Instead of relying on large runtimes or compiler abstractions, I wrote an infe