Search: “agents”

v4.5.0: Added native desktop control, agent execution budgets, concurrency limits, loop protection, and safer local embedding fallback. v4.6.0: Rebuilt agents around durable parent-led orchestration.

Some of you may be aware that a few weeks ago, LM Studio announced a new agent, Bionic. This is pretty much an agentic harness for both local models and paid cloud models. But most aren't aware that L

LLaDA2.2-flash is an agent-oriented diffusion language model in the LLaDA2 series. By introducing Levenshtein Editing (with DELETE and INSERT control tokens) to diffusion language modeling, it represe

AgentZ is a locally-run, SOC (Security Operations Center) level AI agent built on top of Ollama, designed to assist with cybersecurity tasks such as threat analysis, alert triage, and incident respons

A Reddit post from the r/ollama community demonstrating a practical experiment in which a user ingested the narrative content of *The Godfather* into a structured knowledge graph and then queried it u

Yesterday TechCrunch published a piece about a growing problem for AI agents: websites are starting to block them. Amazon blocking Meta's Muse is the obvious example. At almost exactly the same time,

I've recently been working part-time on an AutoResearch-style project. The setup is roughly: humans take recent work from top-tier ML/AI conferences, turn part of it into a well-defined task with an e

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

https://huggingface.co/Wa1k3r/Qwen3.8-27b-CODER-4q_xs-24GB-262k-Optimalcardfit Qwen3.8-27B CODER — IQ4_XS imatrix · 24 GB card fit · ~262k context · MTP draft Quantized, Abliterated, and fitted by Lex

AI Engineering from Scratch is an MIT-licensed curriculum: 523 lessons across 20 phases, from linear algebra and backprop to transformers, LLMs, agents, and production serving. The code is stdlib-firs

Meet Inco Splash, open-source inference engine, built around the model and around Apple silicon. Up to 3× the decode speed of Ollama, 2× oMLX, and almost 4× when an agent fans out into sub-agents. Req

They highlighted 3 things on countdown page: VLM, Agentic Improvements, and Think mode. What improvements do you expect? Reply here! Personally, I want to meet a sage who has attained enlightenment. T

Questions & Responses(in BOLD) below. Favorite question(s) moved to end of the thread with combined responses(removed duplicates). Be optimistic folks. I'm sure we're getting other models too apart fr

A Reddit post in r/ollama showcasing a newly built LLM-powered penetration testing tool, likely leveraging Ollama to run open-source language models locally for security testing workflows. The tool is

**mcpstrike** is a tool shared on the r/ollama subreddit that integrates a locally-run LLM (via Ollama) with an MCP (Model Context Protocol) server to autonomously execute penetration testing workflow

This Reddit post on r/ollama likely discusses the concept and usage of a 'Master AI Orchestrator' CLI tool — a command-line interface designed to coordinate and manage multiple AI agents or models, de

This was fun. The base images are made with Kroma, the videos with Minimax h3 and the text-to-speech with Microsoft Vibevoice. The text message screen recording thing is made by an LLM agent (GLM 5.3)

I’m hitting rate limits on Together AI. For context, I’ve been working on an agentic repository indexing and benchmark generation tool, and I’m running multiple agents in parallel across models like L

I tried both these models on a few small agentic tasks with tools (i.e. 'What's the weather like today?', etc.). They're both pretty solid at using web search to find answers despite being small model

Our agent workflow is currently executing a group of 10 vllm api calls within a asyncio.gather we made them share the same prompt until the end where the queries/instruction prompts differ. These call

Here's a metric dashboard giving an idea of the last few days. Been testing with a variety of different agentic coding use-cases, mostly using a pi harness. qwen3.8-flash-next has seriously exceeded m

EDIT: About that, I tried it out, and it's garbage so far. I did some basic tests through AIHubMix (do not use that platform btw, it's trash), and my agent did some comparison. I guess it figures, it

For the last few days, I've been using two computers to run multiple agents. My 4x3090 machine is running Qwen 3.8 27B with parallel=2, so I can run two agents at the same time. My pi instances are ru

Since my last post, I've been thinking about different options for dynamic performance degradation, trying to squeeze as much high-quality inference out of my GPU as I can. Over the weekend I read thi

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

bonsai claim 98.2% intelligent retained, but their own documents show Ternary Bonsai 2 27B reaches 52.8 and 60.8, respectively, compared with 69.7 and 80.6 for Qwen3.5-27B, retaining roughly three qua

Alright, I posted that I had my agent test a bunch of different workflows for over 12 hours and got the 'Bro just wasted 12 hours of credits'. It was obvious the proof should come from the visual data

Smaller models still struggle with browser tasks that require open-ended research or deep reasoning. But many practical browser-automation workflows are much more procedural: extracting structured dat

An AQuA research loop let one LLM write an intraday trading feature and a second LLM review it for causality. The feature divided the volume seen so far by the day's final total volume. At prediction

I'm just thinking, ever since microsoft announced bitnet, this sub (and myself) has been hoping for massive ternary models. In the last month alone, prismML dropped 27B ternary (though I've read commu

I built a spotlight search for windows. It has an embedding model and a MoE models to go with it. The MoE It's 2 Qwen 3.5 4B models, I fine tuned one for coding work and another for agentic work, and

A bit of backstory : i got lucky in August and was able to grab a CMP 170 HX 8GB for around 500 on alibaba. I tried later to get a second one for around 1k but my order got cancelled and prices went t

Seems like a bit of a long shot, but since it’s so mystifying I figured I might as well ask: I have been trying to get Qwen 3.6 35B to function as a local implementation agent in my subagent driven de

I built a free tool that lets your coding agent make videos like this one. You give your agent the link to the repo and say what the video should be about. It writes the words, draws the scenes, and y

A while back I posted here about a CLI agent I'm building that parses tool calls out of a model's plain-text output instead of trusting native function-calling to work. Finally ran the actual numbers.

Top 3 papers on HF Daily Paper are all unusually delightful and interesting reads for anyone on the leading edge of local LLMs, agent harness optimization, etc, felt like sharing. DeepSeek-V4.1-Flash:

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

Hello everyone. I felt current LLM benchmark harnesses hand you headline numbers but offer no tooling to see how models actually answered each question (they dump everything to a JSONL or Parquet file

I used Claude Code to help write this pipeline - Gemma4 to turn an idea into a short story, then IndexTTS 2.5 running on an NVIDIA 3080 to use voices from LibreVox and VTCK voices to pin as character

A few days ago I posted asking what people considered the best local model for an 8 GB VRAM GPU. At the time, my personal sweet spot was Qwen3.6-35B-A3B, for agentic coding with Pi.dev. Well… Thanks t

Sharing my harness for running local LLMs that I built using Qwen 3.x 27B (> 90% locally built) under my supervision - not vibe-coded. Its free, no telemetry, and open-source (AGPL). Works on Windows,

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

Building a local AI agent hierarchy on a budget — RAG, quantization, and testing whether fact-grounding pushes small models toward real creativity I don't have a CS background, a GPU, or much of a bud

I have deleted tons and tons of older models to make space since I can't afford storage anymore. Easily 10TB... Anyways, I have been considering deleting DeepSeekV3.2 but decide to run it one more tim

I'm curious what other people are using for local LLM coding / agentic coding with only 8 GB of VRAM. My current setup is: Intel Core i7-11800H RTX 3070 Laptop, 8 GB VRAM 32 GB DDR4 RAM openSUSE Tumbl

https://preview.redd.it/wkg27e152qjh1.png?width=853&format=png&auto=webp&s=2e3f8b11ea6393041f501e95c5835f9bea0245dd So ive been trying different harnesses and coding agents with the new qwen 3.8 , and