All entries

https://github.com/paulknysh/raggy A lightweight CLI tool for Retrieval-Augmented Generation (RAG) over local documents built with Ollama. Hybrid database (vector + BM25 index) and embedding generatio

I've been running Claude Code as my daily driver and wanted Ollama models in the loop without giving up the harness. So I built gremlord, a small Go binary that points the unmodified claude binary at

Getting anywhere from 10 - 20 tps. Thinking Off . Took about 4 mins and 7 mins. Running on about 'IQ3_S - 3.4375 bpw' 37.03.960.932 I slot print_timing: id 0 | task 2665 | prompt processing, n_tokens

The fix: run the server detached/headless instead of keeping it attached to a console window. RTX 5090, ~27B NVFP4 model via ninfer: Terminal focused: 130–200 tok/s Terminal unfocused: 50–60 tok/s Cli

Cosmos3 INT4 T2I + I2V on Apple Silicon — code, weights and a Grok comparison GitHub - https://github.com/gtrg55/cosmos3-quant-mlx-cuda HF weights - https://huggingface.co/JuliaML/Cosmos3-Super-Text2I

Surveillance plagiarism - Hosted AI company pumps their stock price by training upon researchers' AI sessions, so that their internal model can solve problems with seemingly less human guidance, but r

Hi, I have the biggest pro subscription.. had it for months.. been using more or less the same models (GLM 5.x) - i would averagely be at 95% on a sunday.. and it would renew at Monday. Now we are att

https://www.reuters.com/technology/us-accuses-chinese-ai-firms-industrial-scale-theft-ai-technology-2026-09-08/ https://www.nbcnews.com/tech/tech-news/us-accuses-china-ai-developers-deepseek-alibaba-c

This is from the https://huggingface.co/IFM/K2-Horizon-0.9B benchmark image Tried searching for it but couldn't find it, I am guessing is https://huggingface.co/openbmb/MiniCPM5-1B but the numbers do

Hi, I'm wondering what settings you are using in order to run Qwen3.8-Flash-Next on your devices? I'm especially interested in setups with 96GB VRAM. I'm not quite sure if llama.cpp does offload the e

I only just found ollama, but I ran into a problem described in this conversation from years back: https://www.reddit.com/r/ollama/s/YZ88XkHmIS Has nothing changed? The storage seems a mess. I had to

Who is the marketing genius at LM Studio that decided that going ALL IN on pushing their new Bionic Agent product meant they are going to make it a giant pain in the ass to find and download actual LM

I'm able to run qwen3.8 27b in two ways on my system: split between my 3060 12gb and 9070xt running at 20t/s or running off the 780m iGPU and 5400mhz DDR5 at 5t/s. Personally I feel like the 5t/s is s

We’ve been building PipesHub for a while now, and I’d love to get more teams to try it and tell us where it breaks. The problem we kept running into was pretty simple: Building an AI app over company

Found this post:https://www.reddit.com/r/ClaudeAI/s/At9QNEbawK of someone fully developing a game through AI writing code, generating 3D models, etc. (he is using Meshy to create the 3D models). I was

Most of the new ~30B (and now ~10B, thankfully for my GPU) models we see score really high on benchmarks, but I feel like they don't push back on dumb ideas enough. I think most people don't being lik

What is Astra actually supposed to be better at, Because if the answer is “everything,” then I genuinely do not understand what kind of testing was done for writing-heavy use cases. My biggest issue i

Confirmed by my weekly Hermes analytics. Estimated at roughly 50% cut in weekly and session limits. Which cloud inference plans are you all migrating to? (I understand that local inference is preferre

hey guys. so I should start with, I'm not s programmer at all. but I'm having a great time letting qwen3.8 27b donit for me. 😃 so far I've just been doing Linux scripts and things for my PC. but my ki

Translation: 'Internal beta testing for an intermediate version of DeepSeek V4.1 Flash is now open; you are welcome to try it out. It adopts a new model architecture featuring native multimodal suppor

I've been making a lot of comments about optimal setup for Strix Halo (gfx1150) and from my observation, 90% of our community is using offcial llama.cpp for it, which is NOT optimized for Strix Halo a

A few weeks ago, I saw this post where the author trained a SIREN MLP to implicitly memorize Bad Apple as a coordinate function: (t, y, x) to pixel. That got me curious about a slightly different form

hope that helps my script uses the GPUs most discussed on the LocalLLaMA, LowEndLocalAI, and LocalLLM subs. At first, I tried to include more, but it became unreadable. Prices were collected by ChatGP

I'm the CTO of a mid-size nonprofit, and I run a local Qwen stack as a coding subagent for that work — partly on principle (a fair amount of what I handle shouldn't leave the building), partly because

I kept picking local models badly. Parameter count, quantization, VRAM. I could read all of it and still not know whether a model would be any good on my machine. So I stopped guessing and wrote somet

Hello LocalLLaMA Fam! I built this project because I, like many of us here, enjoy local AI and have a nice setup, but still find myself reaching for Cloud-based AI due to their convenience. My models

I found a lot of room on the table for these cards so I decided to make a specialized build to squeeze all I could. first The results: qwen 3.8 next Q3_K_XL: 920tk/s pp8192 (2 cards, ram offload), 24/

I'm testing a new approach for reducing the cost of image-based LLM inference. I evaluated it on the MOMA Graph benchmark, using 1,315 questions. Compared with using GPT-4o to process the original ima

Ling-3.0-flash-VL inherits the language, reasoning, and long-context capabilities of Ling-3.0-flash, while extending them with native image and video understanding. The model has 124B total parameters

I’ve been thinking about an alternative way of doing low-level AI perception, and I’m curious whether anyone here is already working on something similar. The basic idea is to use waves and physical s

I’m currently running llama.cpp on two RTX 2060 12GB cards, so 24GB total VRAM. With Qwen3.8 27B IQ4_XS at 131k context I’m getting around 45 tok/s, which is actually pretty good for this setup. I fou

Hold right Ctrl, speak, release. faster-whisper (large-v3-turbo) transcribes on your own GPU, then qwen2.5:3b-instruct through Ollama cleans the text up: filler words out, punctuation in, spoken self-

Hey so a few months ago I got into local LLMs and didn’t really like the tools out there at the time, so I decided to build my own version of a Claude/Codex GUI for local models. I’ve been working on

So I've been messinga round with embedding models for a bit, and I think they are interesting enough to experiment with. They are useful for rag, especially in a localllm sense because you can ground

I was thinking about using WebUI but I have a big problem with ollama serve command. Basically I made a python script that uses Ollama API and it works damn well if I don't serve the Ollama server man

Hi everyone, This is probably a simple problem, but I can't get my head around it. I am running ollama 0.33.3 on Linux Mint Cinnamon 21.3 with separate partitions for root and home. The standard insta

I was reading up on the recent controversy around Tristan Buckmaster, Levent Alpöge, OpenAI, and the Navier–Stokes result, and it got me thinking about something broader than this particular dispute.

Privacy have been concern of many of us to have their own hardware to run llms, and here's another reason why: two mathematicians spent a year cracking one of the hardest problems in math and fed ever

The question I think people are least prepared to ask is: What happens when an AI companion becomes better at understanding you than any human in your life—and has an economic incentive to keep you em

I was inspired by Bijan Bowen video - Subway FPS https://youtu.be/6kjXzTVmT58?t=1035 Wondered how far I can push Qwen 3.8 27b so I used a plan made by Fable 5.1 DESIGN.md which has 267 KB! ( 26K of de

Up front: I'm one of the people building the page-perception layer used here. We started by testing small local models. The result turned out to be more interesting than the original test. 12 small mo

Hey guys, After my CPU-only to 96GB VRAM test, I tested Qwen3.8-Flash-Next across llama.cpp, SGLang and FreeToken on the same workstation. This time I wanted to see what changes when you keep the hard

An update to my previous post on running Flash-Next with the expert cache and MTP. I found another useful improvement on the same dual-3090 setup: replacing the CUDA top-k fallback used by my build. O

I don't think anyone posted about this here, but Qwen released a finetuned version of 3.5 4 for driving. The full Bf16 checkpoint is 9B. This is a very interesting development of Chinese AI labs tackl

Ok I know I'm likely to get steamrolled here but I also have a sense of optimism and hope I can get some sort of answer that will be beneficial. We all know since the new price structure, usage has sh

Gemma 4 12B runs on an RTX PRO 4500 Blackwell. Gemma 4 E2B run on a Jetson Orin NX 16GB; similar performance is expected on a Jetson Orin Nano Super 8GB. Both systems use a reSpeaker Flex 4-mic array