Search: “model-releases”

I wanted to know how cheap you can go and still run local models, so I ran Ollama CPU-only on a Youyeetoo X1S. It's a single-board x86 machine with a Celeron N5095 (Jasper Lake, 4C/4T, 15W), 16GB of R

A Chinese article compiled 52 remarks from Liang Wenfeng’s four-hour investor meeting. I’ve summarised the most important ones below. DeepSeek has one central objective: AGI. This is not the time to m

TLDR: I (with the help of AI) re-implemented every Blackwell-only kernel (DeepGEMM, FlashInfer sparse-MLA, block-scaled FP8) in Triton, because they simply don't exist for sm89. The performance is 2-3

Turns out a regular ethernet cable between 2 nodes can run laguna UD-Q2_K_XL (39.7GB) using a direct point to point network. Interestingly on `nvidia-smi dmon -s pucvmet -d 2`, the inter/intra gpu tra

The interesting finding from a new [arXiv paper](https://arxiv.org/abs/2607.16165) isn't that a frontier vision model failed a new benchmark, that happens weekly, but the specific shape of the failure

I kept re-wiring the same RAG plumbing on every project, so I turned it into a clean starter and open-sourced it. Upload a PDF, ask questions, and get answers with page-level source citations. It runs

Hi everyone, About a month ago I publish my very first research paper on my neural network architecture called Silia. You can look at the model here: https://huggingface.co/Srijan-Srivastava/Silia-v2

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

from kwaipilot: Following the release of KAT-Coder-V2.5 in July, we are pleased to release the open-weight version KAT-Coder-V2.5-Dev, an MOE model with a total parameter count of 35B and 3B activated

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

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

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

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

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

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

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

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

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 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

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

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

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