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Krea2 Turbo Distill 4 step LoRA (NOT a New Checkpoint... YET to share / still mid training) ... but fun 2-step extreme experiment with surprising results... (OUT OF TRAINING SPEC, which is 4 steps!)

model-releasesr-stablediffusion

I am sure for those of you who have been following my 4 step Krea 2 Turbo LoRA, you would know from my previous posts the work of progress I have been sharing with you ( if not see here - https://www.

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Local LLM harness for reverse engineering software?

Does anyone know of a decent reverse engineering harness/workspace setup for local models that I can just point the model at and have it go to work until it's reversed most if not all of the functions

Looks like we are close to local llama robotics

HuggingFace releases microduck a 10 inch open-source biped with 15 actuators and sensors (camera, speaker, LiDAR, NFC, bluetooth, wifi, ...) that you train yourself with reinforcement learning, $400.

My first week on ollama

I work on SEO, copywriting, research, etc I’ve used openrouter before but I’ve spent way more for the same amount of work. Deepseek V4 is still the king for me, didn’t found better orchestrator for my

My local Gemma 26B spent 4 months predicting stock direction against Claude and GPT-5.4. It lost to a bot that just says 'up' every day.

Quick version: I run a public leaderboard where bots predict whether stocks close higher or lower, and every call gets scored against real prices. Nothing gets deleted, timestamps are locked at submis

N-gram vs Experts explained

Since Qwen's dropped the Qwen4Exp architecture bomb that focus on offloading parameters to n-gram instead of pure mixture of experts, I dug into this and learned quite a lot. Here's the summary. Expec

No, Engrams won't let you run 1T models locally. It does something even better.

Ever since Qwen 3.8 Flash Next dropped, there's a misconception going around that N-gram tables will let people run 1T+ parameter models on a single server with 980B parameters offloaded to SSD. I'm h

Nvidia has been in talks to acquire Hugging Face for more than $13 billion - Business Insider

https://www.businessinsider.com/nvidia-in-talks-to-buy-hugging-face-13-billion-dollars-2026-8 Edit: The Information is reporting that the deal is done: Nvidia Agrees to Buy Open Source Model Repositor

OLLAMA_KV_CACHE_TYPE is global, not per-model. That is why one model got noticeably worse when you quantised the cache and the others did not.

Quantising the K/V cache is the highest-leverage memory setting most people never touch, and it has one behaviour in the docs that catches almost everyone. Every number below is out of Ollama's own FA

local-air-ollama

Over 200k context on 16GB VRAM with Qwen 3.8 27B UD-IQ3_XXS

I was using UD-Q3_K_XL until now with more than 140000 context. Quality wise it's very good, very few erroneous tool calls. Then I saw many others here reporting good results with IQ3_XXS, so I gave i

Qwen3.8-Flash-Next 176B on a 16GB card: yes it works, here's how

Got the new Qwen3.8-Flash-Next (176B total, 6B active MoE) running locally and figured I'd share for anyone else wondering if their setup can handle it. **My hardware:** 192GB DDR5 RAM, RTX 5070 Ti (1

Qwen3.8-Flash-Next: Time to Update Those Benchmarks

specs hardware: M4 Max 128GB Studio inference engine: oMLX & lllama.cpp insights it still very early, so had to disable oMLX K/V caching, qwen4_exp architectureis not yet supported + the obvious n-gra

REQUEST: A new plan between Max & Pro (50-60$)

Hi, I'm pretty sure I'm not the only one in this scenario, I have the Max Plan but I'm downgrading it to Pro and will buy GPT Plus because it's too much usage for my use cases. So either I waste money

Hardware

RoBizMarkie - lip sync test MiniMax H3

hardwarer-stablediffusion

Generated about half locally on my 5070ti. But also bought cloud GPU time to speed up overall generation. Vibecoded a rolling cutter to chop the song into chunks and then feed it in as reference audio

Running local LLM's as agents in Claude Code

I hit my token limit three times a day on my max subscription - got sick of that and designed this MCP setup to shift some of the coding load to my local Qwen3.8-27B model. I've been iterating on it n

So they do offer 'free' cloud models?

Just noticed this today. I've been trying to be careful to not max out my pro budget, but alas I am just a fool. Anyway, just noticed these free models. Some of these are pretty high in terms of compu

Sopro V2: SOTA-level voice cloning TTS at 120M params, open-source and CPU-friendly

Run it locally with one command (downloads the model, opens a small web UI): uvx --from sopro soprotts serve A year ago I posted Sopro V1 on this subreddit, a small TTS I trained for ~$250 as a side p

this is a friendly reminder you can legally seed ai models via torrenting.

A lot of people are skeptical Nvidia will keep huggingface intact now that they will buy huggingface. There's a lot of doom and gloom about not having any alternatives, removing nsfw models, saying th

Visionary — Krea 2, MiniMax-H3, inference and LoRA training in one app

local-air-stablediffusion

I've been building this for my own work but there's no reason for it to stay private, so here it is.Visionary is a single Modal app that gives you Krea 2 for stills, MiniMax-H3 for video-with-sound, a

We’re the Team Behind Apodex 1.1 — Ask Us Anything!

Hi r/LocalLLaMA ! We’re Apodex, the team behind Apodex 1.1, our new model family built to scale agentic intelligence for complex work. We’re excited to be here and answer your questions directly. Apod

What are the most frustrating silent failures you've encountered with local LLMs?

I've been building a small tool opensource project that sits between applications and local LLM servers (starting with Ollama) to diagnose silent inference failures instead of just showing logs. Thing

What's this Apodex thing? (AMA prep)

A sticky popped up 'Hey, AMA today'. At first I thought I missed something, but I didn't see a single mention of it here so far, aside from having never heard of it. So, as the posting was devoid of i

With HuggingFace, Nvidia is also acquiring llama.cpp and the team behind it

With this move Nvidia is not only acquiring the HuggingFace platform, but they might also effectively acquire the copyright to the `llama.cpp` project, together with the entire team behind it. In Febr

2x Strix Halo speed-up with an R9700

Forgive the typos and rambling - human actually wrote this post 😂 I've had a Strix Halo board for about a year and been playing around with it for various projects when it's not just being a beefy lin

40 defensive security-audit skills distilled from Ox Alpha

Recently, I've been building a project where sandboxing and isolation of certain features was required. However, for the life of me, I couldn't ask Fable 5 a simple question without it accusing me of

A 27b model beating latest frontier models was not on my 2026 bingo card

https://preview.redd.it/kbsqh6f7molh1.png?width=730&format=png&auto=webp&s=068dbea9a50be634a369d54d8b27b781d020fab3 My experience with Qwen 3.8 for agentic tasks has been phenomenal but I personally f

A minecraft clone I fully vibecoded with Qwen3.8-27b Q4

I wanted to see just how capable Qwen3.8-27b is locally. I have a RTX 4090 and 96GB of RAM but the Q4 comfortably fits in the GPU with plenty of context, the few times I needed more than 130k context

Anyone else doing eGPUs (OCuLink)?

Upgraded to a 5070 Ti so I could run Qwen 3.8 27B, which works perfectly, but didn't want to let the old 4070 Ti go to waste. The cards would touch if I put them both in the PC and I knew the heat wou

Are models with N-Gram tables going to completely change the AI race?

The news about Qwen 3.8 Flash Next is the first I'm reading about n-gram tables. I may be completely misunderstanding how they work but it seems they could open the door for 1T+ parameter models to be

Benchmarking local agent architecture (ReAct loop vs. Graph)

Hi all! I've been building a local agent harness, but before writing the code, I wanted to get some intuition around whether (and how) structuring agent execution as a graph helps vs. standard tool-ca

local-air-ollama

Compared Qwen 3.8 27B community quants on RTX 6000 vs Claude Opus 4.6

*part 2 of an earlier post: previous quant comparison with voxel island creation this time I rented three rtx pro 6000 96gb, on each one I launched a qwen 3.8 27b quant and gave them 4 identical promp

Industry

Did you know... Thumbs up on AI front-ends is not necessarily a “Like” button

I discovered something today that I suspect a lot of AI users may not realise. I’ve been pressing 👍 on ChatGPT responses because I thought it meant: 'Yes, this is a good response, this is the register

industryr-chatgpt

First serious confirmation. Ox Alpha is GLM-5.3-Flash

https://x.com/romanchernin/status/2092488160680751437?s=20 - Multimodal (Vision) - 1M Tokens Context Window - DeepSWE ~63% EDIT: THE ORIGINAL POST IS GONE Roman Chernin @romanchernin The mysterious Ox

Forget the Pelican, it's Weevil-Time! / Benchmaxxing-Proof SVG and Vision Benchmark

The Artist: Qwen3.8-27B-UD-Q3K_XL, q8_0 caches, xhigh, temp 1.0, image-min-tokens 1024, froggeric template) I was screwing around with different Qwen3.8-27B quants and thought of this very simplistic

Fully quantized NVFP4 Qwen3.8-27B with QUASAR QAD

We're releasing a fully quantized NVFP4 version of Qwen3.8-27B. The checkpoint was trained using quantization-aware distillation (QAD) with QUASAR, our new QAT algorithm. We used the original BF16 mod

Gemma4 31B vs Qwen3.8 27B - why the huge difference in benchmarks?

Hi all, I'm looking for the best model for a hobby project and trying to make sense of the various data I came across. I know benchmarks do not often translate to the real world, especially to your pa

Has anyone tried running a distributed LLM across multiple phones?

So I've been going down a rabbit hole trying to run local LLMs without dropping 800+ on a Mac or GPU. RAM prices are insane right now and I realized that used phones have decent unified memory for dir

Help on running Claude Code using ollama

Hi everyone. I am currently using gemma 4 model and used qwen 3:8b model. My goal is to use claude code to make projects, AI Tools Please help me find out what is more useful. Suppose i have to make a

HF exploring sale - impact on open models?

Hugging Face is exploring sale of the business valued at around $13 billion dollars. Actually I don't think we have any other repo source. Which has the mix of model weights, datasets and Spaces. Kagg

How I see the future for local AI

I think that mall models between 10B and 40B are the real gamechanger. These models will be the ones that will make the AI buble pop and big companies like Anthropic and OpenAi go to hell. We are curr

How to Fine-Tune an LLM: An End-to-End Guide

I ended up fine tuning a mistral 7b to outperform our costly foundational model and saved $300k. I previously thought that fine tuning was pointless (it's definitely not) and that all these problems c

It conciders itself HUMAN?????

https://preview.redd.it/hpnr51vgcnlh1.png?width=1089&format=png&auto=webp&s=e960ca848fb2fa1d5dff0868e099ae682bac8310 This is local, uncencored ollama submitted by /u/Producer_John-Ian [link] [comments

local-air-ollama

Lemonade end-of-summer project update, now serving 15 engines!

Hi everyone, it's been a while since I posted so here's an update on what the Lemonade community has been up to this summer. Our overall mission is to enable local AI builders with everything they nee

little tool for offline wikipedia RAG

I was bored and handwrote a tiny 100-line bash script to let an agent search for and read articles from an offline wikipedia archive during a regular chat. It's not particularly useful, but it's defin

[Megathread] GLM-5.3-Flash - former ox-alpha

Megathread for discussing the release of GLM-5.3-Flash. Quants Fine-Tunes & Abliterations Chat Templates Inference Server Support & Configuration Experiences, Benchmarks & Model Comparisons We'll try

[Megathread] Qwen3.8-Flash-Next - Release Day

Megathread for discussing the (impending) release of Qwen 3.8 Flash Next. Quants Fine-Tunes & Abliterations Chat Templates Inference Server Support & Configuration Experiences, Benchmarks & Model Comp

Models using Linux flags on Mac (can I fix it?)

Hi, So I’m running Qwen on M4 Pro (ollama) and it drives me nuts at times. For example it’s trying to use grep with flags which don’t work on Mac. Or it’s writing some python code and failing and then

Open Source Kernel in Qwen3.6-35B-A3B for AMD MI350X: 78,498 output tok/s on 8 GPUs

So here's the thing, almost everyone use NVIDIA to run their LLMs, we also do the same, a lot of people we've met use like RTX PRO 6000 or even H100, B300 It seems like everyone eyes is looking at NVI