Search: “agents”

The first autonomous agent cyberattack is an unprecedented event that deserves unprecedented transparency. Today we're sharing everything we can: a full technical timeline, an interactive replay, and

Someone in the comments of my 27B post-train bakeoff asked for the 35B version, so I ran it. Same setup as last time: fresh Coder workspaces on my k8s cluster, each driving my own agent (Hermes) headl

I got tired of my Ollama server sitting idle between chat experiments, so I pointed it at my Navidrome library and made it run a radio station. The DJ is an agent, not a shuffler. Each turn it gets to

A user announced a major update to their Ollama coding assistant featuring Cline, an autonomous coding agent that operates within IDEs and can create, edit files, execute commands, and interact with t

User seeks guidance on PDF processing methods for local AI agents built with Ollama, comparing approaches like PDFPlumber extraction, vector database RAG systems, and alternative techniques for accura

Quanty AI is a local AI companion playground built with Ollama as the backend, featuring animated pixel art graphics and interactive micro fiction experiences. The project integrates agent skills to e

TuneForge is an MCP (Model Context Protocol) server that enables coding agents like Claude and Cursor to perform machine learning operations directly within chat interfaces, including dataset generati

Users building agentic pipelines with Hermes models in Ollama report an issue where the model correctly generates tool call JSON in its response but the actual tool functions are never invoked or exec

Live results, coding benchmarks included, agentic benchmarks included, domains and other classifications filters included. (Spoiler: DeepSeek-V4-Vision-Exp rules, but other models have their rule area

Figure 1b from our paper Disclosure: I'm one of the authors (Microsoft). The paper, code, dataset are public and ThinkingBox is on Hugging Face OpenEnv as well. Raw evaluation trajectories are not rel

In this project I wanted to see if any interesting emergent behaviors would appear if we trained two agents to play a streetfighter-like game using RL. Maybe obvious in retrospect, but the agents are

Oh My Pi + vLLM on two 3090s. Average wait per turn went from 28s to 7s, mostly from changing omp settings: explicit effort level on every role (unset ones defaulted to xhigh) thinking_token_budget of

I'm still using LLM's the 2022/23 way of doing everything manually from the chat box. I copy and paste everything manually into the box and ask the AI to explain or do something, such as pasting code

The intelligence in my context is an aggregate index, I called the Agentic Coding Index, across most relevant agentic coding benchmarks: SWE-bench Pro, DeepSWE v1.1, Terminal-Bench (v4, v3, v2.1), Cod

Using https://huggingface.co/RadixArk/Qwen3.8-Flash-Next-NVFP4 and https://old.reddit.com/r/BlackwellPerformance/comments/1w04xb7/qwen38_flashnext_on_1x_rtx_pro_6000_171_ts_c1_428/ As usual, all the d

I have been using local models on/off for like 2 years or so but never really used them extensively because the closed ones were always much better. Once Qwen 3.8 27B was released I decided to give it

I’m not affiliated with this project, but I’ve been running it recently and I’m surprised it hasn’t received more attention here: https://github.com/fewtarius/CachyLLama CachyLLama is a fork of llama.

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

Been doing a bunch of vibe coding lately. Had my agents host a private WoW server for me, then built out a web browser client so you can play without installing the game and it has mobile controls. Af

Just a quick PSA. llama.cpp does have prompt caching. if you are running large context lengths and have long multiturn projects, increasing -cram can provide you with massive speedups. There is a poin

If like me you enjoyed classics like Baldur's Gate 2, this is a small fun experiment. For anyone interested: https://www.youtube.com/live/8FhPfRKTucw?si=PMIVdHbZ-31PNwZD Qwen 3.8 Flash Next has amazin

A new paper (I'm not a coauthor BTW -- I just found it interesting) argues, basically, that RSI1 is not on the horizon2, because current (at the time the study was done) agents cannot do open-ended ML

i've been thinking about this more after trying different agent setups. the model isn't the only thing that determines how well an agent performs. The harness around the model matters a lot too. With

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

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

hello everyone. I'm training PPO variants on different multi-agent tasks from the VMAS library (Independent PPO / Graph PPO and such, see HetGPPO by Bettini et al.). I noticed that for every architect

The task was the same both times: replace 63 calls to datetime.utcnow() across 22 files in a Python service, keep the comparisons that assume naive datetimes working, and leave the tests green. I read

In medium reasoning mode, it both scores higher than the 3.6 version, AND is very much more efficient (almost half requests needed, and a third less tokens generated) - at DeepSeek v4 Flash 3107 MXFP4

I've pulled two models, `gemma4:latest` and `qwen3.5:latest`, and tried to use them in Android Studio and Itellij. I've followed the docs for both IDEs and they show in their chat features. My problem

Same old prompt, just appended a TIP in the end: 'Write a single HTML file with a full-page canvas and no libraries. Simulate a realistic side-view of a moving car as the main subject. Keep the car vi

I was wondering what a minimal coding agent implementation would look like that can be used like Claude Code or Codex Not feature-by-feature of course but basically stripping everything out that is no

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

Can LLM agents actually get through a day in the life of a normal user? That question got me reading papers on Android agents and mobile benchmarks over the past few months. A few patterns kept showin

github repo: https://github.com/athulg93/vscode-localllm Alright, So i have made some major updates to this extension Update the git flow: Found out that there were some issues and the / part was a me

MiniMax has released the source code for MiniMax Code’s terminal agent: https://github.com/MiniMax-AI/minimax-code https://preview.redd.it/st9izmm8zaqh1.png?width=3016&format=png&auto=webp&s=5853bc316

What I want to know is how your daily interaction routine looks like. Do you wake up, take your coffee/tea/drinkname.txt, have a nice morning, then click a button and somethings starts and creates som

Model: https://huggingface.co/internlm/Intern-S2-397B Collection: https://huggingface.co/collections/internlm/intern-s2 From Intern Large Models on 𝕏: https://x.com/intern_lm/status/209942518458737097

Their last version 7.14 was released just a month ago. llama.cpp PR(waiting for approval) for Version 10.0 https://github.com/ggml-org/llama.cpp/pull/27803 Hope this version comes with more boost & im

Possibly best way to spend current hour before grabbing 27B model(Instead of opening duplicate repeated 27B posts here). I tried to grab summary(thought of including in this thread) of this video usin

Ran the model with quants (Q4) by Unsloth with latest (build from master) llama.cpp server. It takes ~20GB ram running on M5 Pro with 48GB at about 17t/s. Didn't do any reasoning loops/overthinking. O

First of all, obviously I took some help from AI to type this post and this is the topic that enabled me to accomplish all that: https://old.reddit.com/r/LocalLLaMA/comments/1veow4b/deepseek_v4flash_2

https://preview.redd.it/522fsdwvtdhh1.png?width=1200&format=png&auto=webp&s=6a6cf7a467514167a8193029dbd20fb3a9ba4f6c It ranks lower than both Sonnet 4.6 and Luna. I'd wager Luna costs in the same ball

Hey r/LocalLLaMA, I’m Mahmoud from Agenta. We built a self-hosted, more flexible, alternative to Claude Cowork . This short video shows how it works. I use it to build AI coworkers for my startup, lik

A Reddit post from the r/ollama community titled 'Two AIs walk into a bar...' likely showcases a humorous or experimental multi-agent conversation in which two locally-run AI models (via Ollama) inter

Hi, Im gonna go all in on this, best finetune iv got my hands on for agentic coding, period. Test it yourself, im not gonna give you any benchmarks or evaluations, use your own tests and pracices, giv

Alright so I'm pretty new to all of this, but today I got a pretty solid crash course in exactly how these LLMs work. I wad quite surprised to find out that there's zero 'thinking' involved in any of