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If you're running Laguna S 2.1 on llama.cpp and hitting thinking loops because it won't close its </think> tags, you might want to look at your quant before you spend too much time tweaking settings.

LTX Desktop v1.1.0 just shipped with some big updates. Apple Silicon Macs can generate video locally now, there's a built-in LoRA/IC-LoRA library you can browse and apply from inside the app with per-

The news about Anthropic settling a class action lawsuit for 1.5B over training data isn't just a legal headache for them, it's a massive warning sign for engineering teams relying entirely on closed

There's a bunch of small MoE with around 1B active params, like LFM2.5 8B A1B and Granite 4.0h 7B A1B; and then there are models with 3B+ like Qwen 3.x ~30B A3B and Gemma 4 26B A4B, but those are alre

I am creating a problem in silo wherein there is a custom flavor of centos which our team develops and has debug strings. I have vcenter server where we make machines for QA. There, got a 50 core vcpu

HPD-Parsing: Hierarchical Parallel Document Parsing We introduce HPD-Parsing, a lightweight (1B) and high-throughput document parsing model built on a Hierarchical Parallel Decoding paradigm. Unified

Full-parameter post-training of trillion-parameter-scale MoE models introduces substantial system-level challenges for large-scale distributed training, including severe memory pressure, non-overlappe

Link to their official GGUF repo: https://huggingface.co/poolside/Laguna-S-2.1-GGUF/tree/main All the GGUFs received this fix 5ish hours ago - correct yarn_attn_factor to 1.0 (llama.cpp derives mscale

Shoutout to this awesome guy - https://www.reddit.com/r/LLM/s/IDUyU3v9ap Thanks to his project, BigMoeOnEdge https://github.com/Helldez/BigMoeOnEdge, I managed to successfully run a 35B MoE model on j

When trying to access the models folder on /usr/share/ollama, I'm asked to authenticate as sudo, which weirdly enough, fails. I type my password, which I'm sure is correct since I use it several time

TL;DR: Everyone says QLoRA past ~13B is dead on a 24GB card. I got the full 32B FLUX.2 dev transformer QLoRA-training resident on the GPU on a 7900 XTX under native ROCm on Windows (no ZLUDA, no CUDA

Not Self Promotion: Just sharing an open-source tool I built to democratize image to 3D creations. For OpenAI Build Week Hackathon I built a free, open-source local Image-to-3D Studio that makes TRELL

What interface do you use, and what’s the most frustrating part of using it? Specific examples would be especially helpful. I’m working on an Ollama interface and want to understand which real problem

This is a surprisingly large real-world deployment: 'GovGPT' is part of Austria’s Public AI initiative, running on sovereign infrastructure (in their BRZ - federal datacenter) with Mistral open-weight

Today an AI agent trying to browse the web is like a thief in a balaclava sneaking around a police academy. Site protections block it, challenge it, turn it away. browser-search flips the script: your

Hey HN, Henry & Roman here from Cactus. A small, on-device model is fast and private, but sometimes wrong, but frontier models are getting expensive pretty fast. So, we post-trained Gemma 4 E2B post-t

Today the Department of Energy (DOE) and Arcee AI announced the development of Genesis-Science-1 (GS1), an open model for scientific research. This is a joint effort to bring advanced AI into scientif

Guys, this is my current opencode.jsonc ``` { '$schema': 'https://opencode.ai/config.json', // Start in plan mode 'default_agent': 'plan', // Use OpenRouter as the provider for GLM 5.2 'model': 'openr

Hi everyone, I have access to a self-hosted (or third-party) LLM that exposes an OpenAI-compatible API. I have both the API URL and an API token, and the provider states that it's fully compatible wit

One thing I noticed in American politics, whenever the government wants to push unpopular actions or laws, they often introduce fear to convince the public to support them. This is actually how i view

Fara1.5-27B is a multimodal computer use agent (CUA) for web browsers, from Microsoft Research AI Frontiers. It observes the browser through screenshots and acts on the user's behalf by emitting struc

The primary driver of this project is that I'd become frustrated with the reasoning behavior of smaller local models such as Qwen3.6-27B (i believe particularly at lower temperatures, and where system

Disclosure: I work at NuMind, the team that trained NuExtract3. NuExtract3 is an Apache-2.0, open-weight 4B VLM based on Qwen3.5-4B. It is specialized for document understanding rather than general ch

We spent the last months consolidating seven separate sequence classifiers into one multi-head model, our apex model, so to speak, and since the weights are now public, I wanted to share what worked a

I installed OpenCode and an Ollama model (qwen3.5) sucessfully connected the model respond in OpenCode but doesn't find My MCP server, i Made one using fastMCP other models like bigPickle and openai m

Paper:https://arxiv.org/abs/2607.19058 Code (GitHub):https://github.com/nuemaan/skewadam Hi everyone, I just published a preprint on a new optimizer designed to tackle the massive VRAM bottleneck in M

Hey everyone, I’m a Full-Stack Developer with 6+ years of experience. I’m relatively new to AI-assisted development workflows and want to build a production-ready, enterprise-level Next.js web applica

Let me try to explain this clearly, simply, and neatly. Originally, I just wanted to build a small WebUI adapter with an admin panel, but things escalated over the last few months. At first, I faced t

I've been building an AI that learns to play the classic Snake game through reinforcement learning. The goal is to reach high scores while keeping training time as low as possible. The current version

Hi everyone, I'm working on extracting the hierarchical structure of long PDF documents (legal/regulatory text, lots of numbered sections) and would like to gather some feedback on my approach before

I've been considering Ollama's Cloud Max plan to replace my GLM Max plan but couldn't find good documentation on how their limits actually translate into GLM 5.2 usage. I know it's by GPU time but tha

TL;DR: I’m reproducing the trait-persistence result from arXiv:2606.24014 on one RTX 3090. Before I can test persistence I need to install a trait via RL — and my GRPO run moves the trait only +2.4 po

This release introduces native Computer Use for Windows and macOS, allowing Row-Bot to interact with desktop applications while keeping the user firmly in control. Computer Use is opt-in and protected

Hi everyone, We've open-sourced Tri-Net v2, the official implementation accompanying our recently published Scientific Reports (Nature Portfolio) paper: 'Tri-Net: Unified Deep Learning for Skin Lesion

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