Search: “models”

onPanda is designed for geeks, power users, curious minds, and engineers. Its UI is built for deep exploration and efficient data annotation. - The core loop is simple: hover over a token → click an a

I was wondering if there are any good coder models for 8GB VRAM RTX 5060. My specifications: 8GB RTX 5060 8GB DDR4 RAM 256 GB SSD I know the configuration is a bottleneck for sure. Though I don't have

Hey r/LocalLLaMA, Prism-LM recently released its Bonsai 2 QAT models based on Qwen3.8, and they quickly gained traction. In our evaluation, the models strike a strong balance between throughput and qu

I spent the first week of September building a personal assistant over Gemma 4 in Ollama on a 16 GB M1 Pro: Node backend, React web UI, Expo phone client, two-model routing, cross-session memory, RAG

The model is derived from Qwen3.8-27B, a 27B hybrid-attention causal language model (architecture unchanged), but uses ternary weights to shrink model size down to <6GB in size. According to the model

Hey guys, really wondering now why we got (SOTA or at least good enough) open weights on nearly every use case, like LLMs, T2I (Krea2), music (Yue2), video generation (Minimax H3), but not image edit?

can you draw a picture of a flower in gimp? So I ran through this setup to install the MCP server suite from GITHUB, it's pretty easy to follow the install - and installs the libraries necessary to co

From the email 'Early access to new models During the program, approved users can try two next-generation Xiaomi MiMo models for a limited time: MiMo-X-Pro-Preview and MiMo-X-Flash-Preview. The MiMo-X

Model available here: Qwen3.8-27B-Uncensored-Genesis-V1-MTP-GGUF This model is a practical realisation of things described in this paper, but adapted by me for machine learning: https://arxiv.org/pdf/

Hiya, NInfer is amazng for Qwen, but lacking for real-world-use. As adoption of issues/pr's was not really what I needed, I created a fork and hit it for this week with 3 concurrent claude code sessio

I've been running Qwen3-0.6B on the M5Stack LLM-8850 card (Axera AX8850 NPU, 24 TOPS, 8GB LPDDR4x) hosted by a Raspberry Pi 5 — as a llama.cpp backend. The problem: the vendor stack requires convertin

Granite-4.2-30B is the flagship reasoning model in the Granite 4.2 family. It delivers the strongest performance across reasoning-intensive tasks by leveraging built-in <think>...</think> chain-of-tho

I made a Discord for people who are genuinely into AI and want a decent place to talk about it. It’s still new, but the idea is to build a large community without arbitrary bans, hidden moderation dec

MobileMoE is a family of on-device Mixture-of-Experts (MoE) language models with sub-billion active parameters, designed to push the quality–efficiency Pareto frontier for on-device LLMs, including th

Benchmarks: Benchmark U1 Preview Full Qwen-Image-Bench 47.14 55.20 (PE) 60.18 (PE) ImgEdit 3.9 4.37 4.59 GEdit-Bench-EN 7.47 8.14 8.26 Instead of just scaling up, they train task-specialized expert mo

Thoughts About Scaling Law Scaling, but not only of parameters. Every model release now ends with the same question: how many parameters? It isn't a question that can be answered on its own. Parameter

I'm always testing an image prompt with a picture of a historic place in my hometown – a small but well known 250,000 people town in Germany. I'll just ask the model, in which City this photo has been

Minimax H3 can be used as an image-editing model if we generate a single frame. Here are some collages based on AI-generated references with workflows. Each edit takes about 8 secs on a RTX 5090. The

I'm working on a local perplexity/AI search comprised of a custom harness and a further trained model. LFM 2.6 is almost to spec with no additional training, it is very good. submitted by /u/thebadsli

https://preview.redd.it/kihat320ashh1.png?width=1672&format=png&auto=webp&s=a7ccc40ba3fb229ac7ebf57e8e6a314e0ee45646 Hi r/StableDiffusion! u/New-Requirement1419 -> dacongya (Head of H3 Researcher) u/A

I love to see these impressive models coming out that compete with the giants from companies like Z.ai, Moonshot, Alibaba, etc. A win for the open source/weight community is always welcome. While I am

I love the progress happening on open models but I feel like it is kind of getting clear that hardware to run good sized models is completely unaffordable for me right now. I know that you all love Qw

I apologize that this question has been asked in various flavors over time, but I couldn't find anything in the posts before that matches the options I have. I have a PC and a mac, both available in m

Nvidia Cosmos 3 is an open physical AI foundation model built on a mixture-of-transformers architecture that combines vision reasoning, world generation, and action prediction for reasoning, simulatio

Pixal3D is a Tencent image-to-3D model that generates high-fidelity 3D assets from a single image by explicitly lifting pixel features into 3D through back-projection to establish direct pixel-to-3D c

Pixal3D is a locally runnable AI model developed by TencentARC that generates high-fidelity 3D assets from single 2D images. The tool leverages advanced techniques to convert 2D image inputs into deta

A seasoned developer seeking advice on selecting an Apple product to locally host large language models in the 27-36 billion parameter range, discussing the trade-offs and specifications of different

A developer describes building a persistent-state AI system using Ollama with three models (a 4B router model, a 9B primary model, and a 9B 'subconscious' model) running on dual RTX 3060 GPUs, demonst

This Reddit thread addresses a common challenge for non-developers trying to run a local agentic coding assistant on a MacBook Air M5: while tools like Ollama, VS Code, and OpenCode are the right piec

This r/StableDiffusion post likely discussed the anticipated release of an upcoming LTX video generation model from Lightricks, previewing improvements over existing versions before a formal announcem

ERNIE-Image is an open-weight text-to-image generation model developed by Baidu, built on a single-stream Diffusion Transformer (DiT) paired with a lightweight Prompt Enhancer that expands brief user

This Reddit post from r/ollama discusses how to run Unsloth's quantized GGUF versions of Qwen3.5 — Alibaba's model family including variants such as 35B-A3B, 27B, 122B-A10B, and smaller models like 0.

This Reddit thread from r/StableDiffusion discusses community recommendations for choosing the best base model on which to train a LoRA (Low-Rank Adaptation) capturing M.C. Escher's distinctive tessel

£299.99 Lenovo IdeaCentre Mini (Snapdragon X1-26-100, 32GB, CPU only): - Qwen3.6 35B A3B coder: reads ~118 tok/s, writes 24.5, ~30 with MTP - Qwen3-Next 80B A3B: 17-18 tok/s writes with MTP How I got

tl;dr: new qwen finetune that simultaneously pushes the frontiers of small model capability and reasoning efficiency. Hey everyone, We publish two post-trained versions of Qwen 3.8 27B called Sabi-Noe

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

gguf's: https://huggingface.co/openbmb/MiniCPM-V-4.7-35B-A3B-gguf 'MiniCPM-V 4.7 is the latest model in the MiniCPM-V series, available in a 35B-A3B variant, with 35B-A3B being the first MoE model in

I wanted to track grocery spending per item without sending my receipts to anyone, so I built an Android app around a small vision model that reads a photo of a receipt into JSON: store, date, total,

Standard distillation usually means burning weeks of compute and billions of tokens hoping the student model eventually mimics the teacher. We wanted to see what happens if you skip backprop entirely

I’ve been building this for a long fucking time, and tonight I finally released Memoria 1.0.0. I built it because I actually wanted to use it. I wanted a real memory layer for local LLM applications t

On my two DGX Sparks, Swift 1.5 (UkisAI's reasoning-efficient fine-tune of Qwen3.8-Flash-Next) running on veloGB10 (https://github.com/sf-stav/veloGB10, sf-stav's Rust/CUDA engine built only for GB10)

Hybrid search, reranking, query decomposition, and query expansion are often treated as must-haves for good RAG. We wanted to see how much each actually helped, so we tested them. Same model, same emb

Apple Foundation Model 3 through Private Cloud Compute is directly available in macOS 27.2 through familiar AI clients. For Mac users running local models such as Qwen 3.x or Gemma 4, AFM 3 PCC is a c

I’m building a Polish General purpose legal Model that drafts documents, answers questions using legal sources, and has enough coding ability to handle some automation. The workflow is very tool-heavy

We have released Qwen3.8-Flash-Next quantized with GSQ and RCO, together with a second, capability-targeted build in which half of the model's experts have been removed. Flash-Next is a sparse mixture

I know most people here probably don't care as much about sonnet 5.5 as they did opus 5.5, because their 100 and 200 plans already give them plenty of weekly usage for opus. But keep in mind: free use