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I am currently running Qwen3.6-30B in Ollama, through Cline to use as an agent in VSCode. Qwen's skill in coding is not in question, but the performance in VSCode is slow and inaccurate and times out

I worked on this project (https://github.com/workofart/harness-training) for the past few months to reframe 'Agent-driven Self-improving Harness' to 'Harness Training'. The idea is simple, the harness

I have a 48GB M5 Pro and have far too many development projects going that just don't need the power of Anthropic to churn through so have started looking into running local models and while it certai

I don't have the ability to access Reddit posts or browse specific URLs. To provide you with an accurate factual summary for your knowledge base, I would need either: 1. The actual content/text from t

I managed to get this model working on 2x 3090s with full 262k ctx and N=4, if anyone is interested to try it, thanks to this quant: https://huggingface.co/danielrmay/NVIDIA-Nemotron-Labs-3-Puzzle-75B

Hola Strix and AMD stacker frendios. Read the Lineage and Credits, this uses charlie12345/ROCmFPX, won't work on native llama.cpp yet. 122B total · 10B active · 60.70 GiB · 28.50 tok/s MTP-off · BF16

MODEL + GGUF : https://huggingface.co/InternScience/models?search=a1-4b Technical Report Benchmark Qwen3.5-4B Agents-A1-4B Qwen3.5 Qwen3.6 Nex-N2-mini Agents-A1 🧠 Dense Models (~4B) 🔀 MoE Models (35B-

LLMs handle speech well once you run speech-to-text. They don't hear the rest: a bird outside, a glass breaking two rooms away, a smoke alarm two floors down. I've been working on an experimental open

Below Upstream Status sections are from https://github.com/PrismML-Eng/Bonsai-demo Upstream Status for Binary Q1_0 is supported out of the box in upstream llama.cpp across many backends: CPU (generic,

Efficiency defined as score over active parameters. Removed all the models that were not on the pareto frontier. Yes I'm aware that artificialanalysis.ai aggregate benchmark isn't perfect, but I have

After over a year in development, ExLlamaV3 has had its first production release. Turboderp has been pulling 10 hour days with Fable to bring us this massive batch of improvements. Check out detailed

Benchmark Results Benchmark configuration: threads = 96 type_k = bf16 type_v = bf16 Llama-3.1-8B-Instruct Q8_0 Prompt Size GGML_CPU_Q8_0 t/s ZenDNN_Q8_0 t/s Gain 256 472.28 730.87 54.75% 512 450.86 83

https://youtu.be/oxpGq5FITgA?si=nkHWLReGCDYe7QfL I got Hermes running in the native Debian Terminal in Graphene OS and its really slick. Voice dictation works amazingly. Im using a remote Hermes gatew

Hey r/LocalLLaMA — solo researcher here. I built a new attention architecture and want independent testers. Wave Field LLM replaces O(N²) dot-product attention with FFT wave convolution on a field. Tr

The full quote: I realize that some people really dislike AI, but this is an area where I'm willing to absolutely put my foot down as the top-level maintainer. Linux is not one of those anti-AI projec

Two DGX Spark and a Connect-X7 cable give you about 250GB of usable memory for 7000 8000 USD. This allows using some interesting models at 4-bit. For what seemed like an eternity, the only serious mod

What it is: ATH-MaaS/OvisOCR2 - a 0.8B document-parsing VLM post-trained from Qwen3.5-0.8B (SFT + RL + OPD), Apache 2.0, runs on vLLM 0.22.1. One prompt per page image -> complete markdown (HTML table

Frontier models are just so good though. Fable 5... Gemini 3.1 Pro for design critique and brainstorming. Grok for verification passes. Antigravity with Gemini 3.5 Flash for rote plan execution. Openc

Some fixes & boost(pp) for SYCL/Intel. Merged PRs: [SYCL] Flash Attention with XMX engine via oneDNN graph API (SDPA) on KV f16 for Xe2 ; Qwen3.6-27b-Q8_0 prefill speed up x1.21 at p=512 and x4.26 at

Disclosure: I work at Pluralis Research, the lab that built this. Code is open, and I'm happy to answer questions. TL;DR: As far as we can tell, this is the first RL post-training run whose entire rol

https://techcrunch.com/2026/07/13/satya-nadella-has-issued-a-shocking-warning-to-companies-using-ai/ Venture capitalists have been warning for awhile that OpenAI and Anthropic are getting access to se

Introduction RxBrain (Hy-Embodied-RxBrain-1.0) is a unified multimodal foundation model for embodied cognition — a single model that couples language reasoning with visual imagination to deliver three

Very impressive release by the PrismML team. 1-bit quantization shrinks it from 54GB to just 3.8GB (-93%), while retaining 90% of its intelligence. - Collection on Hugging Face: https://huggingface.co

dam bois we eating good this week ngl, The velocity of the open_weight ecosystem right now is hitting a point where proprietary, closed-source APIs are losing their leverage on compute intelligence. W

This Reddit post discusses user preferences for AI image generation models in 2026, expressing that despite numerous new model releases, the Flux Klein 9b FP8 model has become their benchmark for what

This Reddit post from r/ChatGPT discusses users' experiences using ChatGPT as an emotional support tool during difficult periods, exploring how the AI's conversational capabilities provided unexpected

A developer created a local codebase memory system for agentic integrated development environments (IDEs) using Ollama and ChromaDB, enabling AI-assisted coding without reliance on cloud services. The

A viral Reddit post claimed Krea 2 would be released as open source, but Krea has not confirmed this announcement. Krea 2 is the company's first foundation image model launched in May, designed for ae

LTX-2.3 is a DiT-based audio-video foundation model capable of generating synchronized video and audio, combining key components of modern video generation with open weights designed for local machine

This post likely presents an enhanced demonstration of DVD-JEPA, a video variant of the Joint Embedding Predictive Architecture model. The JEPA framework has been extended to video tasks (V-JEPA) , an

A researcher released an open-source softmax-free attention model at GPT-2 Medium scale (354M parameters trained on 11.5B tokens) that uses structural sparsity and tile-skipping kernels to reduce VRAM

I cannot provide a factual summary for a knowledge base without accessing the actual content. Reddit post titles often contain subjective language and don't reliably convey the full argument. To creat

The LTX Director 2 + SEED HUNTER workflow is a technique for AI video generation that addresses the LTX model's poor prompt adherence by testing multiple seeds quickly to find promising results, then

OpenCodeRAG is a local embedding service using FastAPI and SentenceTransformer, paired with a Node.js plugin that integrates RAG tools with Qdrant vector database via YAML configuration. It provides a

A World of Warcraft server has become populated entirely by approximately 1,800 AI bots based on DeepSeek, which engage in typical player activities including chatting, leveling characters, running du

This post discusses a solution for keeping multi-hop retrieval-augmented generation (RAG) systems updated when data changes, using an embed-and-append approach with the open-weights Llama-3.3-70B mode

This handbook covers the technical aspects of running large language models efficiently at scale, focusing on GPU optimization techniques including GPU internals, key-value (KV) cache management, batc

TSAuditor is a contamination auditing framework for time series foundation models that uses probe adaptation dynamics to detect when evaluation datasets may have been exposed during pretraining, valid

A developer created a fully local, CPU-based voice interface for Ollama that enables hands-free conversation with AI models by combining three open-source components: Silero VAD (voice activity detect

Ideogram 4 includes runtime safety filters powered by Hive for prompt and output moderation , with NSFW prompts blocked by displaying 'Image blocked by safety filter' . Users have reported false posit

This post discusses running Google's Gemma 4 QAT (Quantized Aware Training) 12B model on a GPU with 8GB of memory while maintaining a 16k token context window. The author likely shares performance ben

As of May 2026, image upscaling tools split into two main categories: true-to-source models optimized for photo restoration, and creative reimaginers designed for AI art. Leading options include Topaz

Row-Bot is a local-first desktop AI assistant that orchestrates tools and models to handle reasoning and workflows while keeping data local. The demo likely showcases how Row-Bot's integrated tools, k

Users can delete chat instances in Ollama's GUI by right-clicking and deleting each chat individually, though there is a feature request for a 'Select All' option to delete multiple chats at once. Alt

A tool that describes any image and converts it into a structured Ideogram 4 JSON prompt, returning a working JSON prompt that can be passed directly to Ideogram's image generation endpoints. The tool

A developer expanded on Andrej Karpathy's LLM Council concept by implementing an enhanced system with Docker containerization, Model Context Protocol (MCP) integration, skill modules, web search capab