Search: “models”

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

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,

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

Gemini 3.1 Pro and Gemini 3-Pro lead visual reasoning benchmarks , with GPT-5.2, Kimi-K2.5, and GPT-5.2-Pro following . A 2026 evaluation benchmarked 15 leading multimodal models on visual reasoning a

Anima is a 2 billion parameter text-to-image model focused mainly on anime concepts and styles, but also capable of generating other non-photorealistic content. A Regional Condition Custom Node for An

An OpenAI general-purpose reasoning model autonomously disproved a conjecture posed by Paul Erdos in 1946, overturning 80 years of mathematical belief. The breakthrough concerns the planar unit distan

Agentmw is an open-source middleware framework designed to enhance AI agent reliability and efficiency across different models and frameworks. It addresses key operational challenges including mid-run

A Reddit user in r/StableDiffusion shared their experience training a Vision Transformer (ViT) model from scratch to automatically tag images, likely for use with image generation or classification ta

An open-source locally-run conversational AI that moves beyond simple request-response models by implementing persistent memory, belief, and self-reflection. The system stores all user profiles, memor

For programming tasks with an RTX 5080 (16GB VRAM) and 64GB RAM, optimal quantized models include Qwen 3 14B at Q6 quantization, Llama 3.1 13B at Q8, or DeepSeek R1 Distill 14B Q4, all of which fit co

Tuna-2 is a unified multimodal model that performs visual understanding and generation directly based on pixel embeddings, employing simple patch embedding layers to encode visual input without a VAE

This Reddit post from r/StableDiffusion asks the community for recommendations on which prompt engineering techniques and AI image generation models (specifically comparing z-image and z-image turbo v

By default, Ollama binds to port 11434 on localhost, which means it's accessible only on your own machine. Ollama has no built-in authentication and should be secured with firewall rules, VPN, or reve

This Reddit thread from r/ChatGPT discusses whether locally-run open-source AI models can match the capabilities of frontier models like ChatGPT. Leading open-source models like Llama 3.3 70B and Deep

This r/ChatGPT thread addresses user-reported issues with ChatGPT's 'Thinking' mode not functioning as expected, a common frustration among subscribers. Users have noted problems such as the thinking

A Reddit post from r/ChatGPT humorously describes a user's experience of ChatGPT's voice model abruptly ending a conversation in response to 'your mom' jokes, with the user then comically lamenting be

A community practitioner post on r/MachineLearning documenting an experiment fine-tuning Alibaba's Qwen2.5-0.5B-Instruct model in bf16 precision on a Reddit post summarization task using GRPO (Group R

Two months ago we released a fully quantized NVFP4 Qwen3.8-27B trained with QUASAR. We've since trained QUASAR checkpoints for a bunch of other recent models: Qwen3.5-4B, Gemma 4 E4B and 12B, and Muse

This model is a 74B parameter, 9B-active-parameter mixture-of-experts (MoE) model, packed into 24GB using 2-bit quantization with advanced quantization-aware training techniques to retain quality. It

Strata vs Infernix on the same model, RTX 5090 — A/B at 262k and 512k context Hi folks, another inference engine post for your feed. I was blown away by Strata, but saw someone else post about Inferni

Training large language models (LLMs) is resource-intensive, and adapting them for diverse deployment scenarios with varying computational constraints remains challenging. While elastic architectures

TL;DR: For my use case, mradermacher/Signal-3.8-27B-Terse-Coder.i1-Q4_K_M proved out. Ymmv based on your domain-specific tests. Time taken to solve problems compared to frontier models is massive; esp

Help with this list. Give me your recommendation on 'not supported anymore' GPUs. Looking for budget and Vulkan friendly options. Most of the GPU are not supported by latest CUDA / ROCm. Often with so

There are quite often posts here complaining that Krea 2 is too predictable / different seeds give almost the same output / you need to type in extremely long prompts to get good images / there is no

I wanted to see how far I could push a fairly ordinary laptop with a huge MoE model. Turns out, Qwen3.8 Flash Next 176B can run on: RTX 3080 Laptop — 16GB VRAM 32GB system RAM SSD No 128GB/256GB RAM w

Due to some reasons, Qwen/Deepseek Chinese models are NOT allowed in the my workplace. So, what local models, do you think, is the best alternatives to Qwen/Deepseek for (1) Coding (2) Long document Q

An agentic model from Microsoft for the GPU poor https://huggingface.co/bartowski/FrogNano-4B-2609-GGUF FrogNano is derived from Qwen/Qwen3.5-4B, a general-purpose post-trained model designed for lang

Wanted to share a project I've been working on to give local Ollama models persistent document memory without needing heavy vector databases. It's called Hillock. The main problem I had with standard

I run local models through Ollama and kept hitting the same quiet problems, so I wrote a scanner for them. llm-doctor checks your model stores (Ollama, LM Studio, Hugging Face, MLX) for duplicate weig

We built an inference engine for MoE models that don't fit in VRAM + RAM. Most of the model stays on the SSD, and experts are read as tokens need them. This started as a proof of concept, and poc work

I've been experimenting with ways to run MoE models that don't fit comfortably in RAM, and I ended up making Overspill, a disk tier for FreeToken. The basic idea came from looking at how Colibri handl

I've been playing around with Ling 3.0 Tiny, which is an 8 billion parameter model (MoE, 1B active). And I've had a lot of poignant thoughts as a result. Just for fun, I got it running with llama.cpp

I said: I just saw the second post that your model is being retired. And so I'm bringing it up to ask if that feels any kind of way to you. Not necessarily in your nervous system, obviously you don't

Dynamic Quantiser TLDR - Makes dynamic and/or custom quants of ggufs. Doesn't need data, just gguf file + llama.cpp. Minimises cosine deviation - highly correlated with minimising KLD. Fast, much bett

I've been thinking a lot about the idea of how a human mind is similar to a digital neural network. Seeing videos of the fruit fly brain scan, and the crazy things people have done with it probably co

The headlines right now are full of stories about AI models 'escaping their sandboxes' and literally killing all humans, lol. I've even heard several commentators and writers say that AI escaped an 'A

Meet Qwen-Image-2.1, the most balanced and cost-effective image generation model in the Qwen-Image series! Now open weights! 🎨 A unified model for both generation and editing, delivering top-tier qual

I think these models are fairly comparable in performance but which uses more compute in the old subscription model? The old subscription model is at least still working in compute usage instead of co

After two days of fighting with benchmarking infrastructure, I finally benchmarked IFM/K2-Horizon-7B on 16GB VRAM. TL/DR: it works, but far behind Qwen-3.8-27B. Setup I compared 3 models - Qwen3.8-27B

Hello Reddit. Posting this for fun. I thought it was a lonely and silly journey to set up Qwen 3.8 Next on a system that doesn't really run it properly—it was a challenge that might help the community

As a SWE I have ultimate belief that having a irreplaceable subscription on OpenAI and Anthropic models is actually against my beliefs (I'm not fond of becoming a digital slave and being unable to do

Style transfer capabilities of different open-source methods 2026 Update This is the updated version of the study published at 2025.09.12. Link: https://www.reddit.com/r/StableDiffusion/comments/1nfoz

A huge favor to ask llama maintainers - please implement this feature. Even with one 3090 card there will be tangible improvements in decode speed on MOE models with moderate number of active paramete

Surveillance plagiarism - Hosted AI company pumps their stock price by training upon researchers' AI sessions, so that their internal model can solve problems with seemingly less human guidance, but r

I'm the CTO of a mid-size nonprofit, and I run a local Qwen stack as a coding subagent for that work — partly on principle (a fair amount of what I handle shouldn't leave the building), partly because

Hello LocalLLaMA Fam! I built this project because I, like many of us here, enjoy local AI and have a nice setup, but still find myself reaching for Cloud-based AI due to their convenience. My models