Search: “models”

TabPFN-3 is a pre-trained tabular foundation model that supports datasets up to 1,000,000 rows × 200 features , representing a significant scaling improvement for the TabPFN family. The model delivers

Models like Qwen3 and Llama 3.2 are commonly used for n8n RAG workflows , with selection depending on use case requirements. Running Ollama models locally requires at least 16 GB of RAM on your device

Google DeepMind released MedGemma, a collection of medical vision-language foundation models based on Gemma 3 in 4B and 27B parameter sizes, demonstrating advanced medical understanding and reasoning

The `'Failed to recognize model type!'` error in ForgeNeo (stable-diffusion-webui-forge) is a `ValueError` raised by the backend loader (`backend/loader.py`) when the application cannot identify th...

This r/StableDiffusion thread discusses the community debate around choosing between FLUX.2 [klein] 9B and Qwen Image Edit 2511 as an image editing model, two strong open-source contenders in the spac

I was unable to retrieve the content of the specified Reddit URL directly, as my web search tool does not fetch raw URLs or Reddit threads directly, and I've exhausted my search attempts for this t...

Users are running Google's Gemma 4 models locally via Ollama and accessing them on their phones through Open WebUI, reporting a positive experience. Since Ollama doesn't run natively on iOS or And...

I just heard of this model. Seems to be a competitor to DeepSeek V4 Flash. About the same size and active parameters. Anyone tested it compared to V4 Flash? Link: https://huggingface.co/upstage/Solar-

Ollama allons you to import model but have you ever tried doing so ? Like running model imported from hugging face or you own model ? Any use case you wanna share ? Very curious about that submitted b

TL;DR: I am building a Windows-first local AI setup for people who want to try local LLMs without spending days choosing models, setting up Ollama, Docker, WSL, Open WebUI, agents, and tool permission

GGUFs here: https://huggingface.co/ReadyArt/gemma-4-31B-it-scotoma-2-GGUF Disclaimer: By slop, we are specifically talking about specific tics with the model(sentence structures), but this doesn't inc

A few people asked for this after the bandwidth thread, so here it is on its own instead of buried in a comment. The dense rule was simple: every token reads every weight, so tokens/sec ≈ bandwidth ÷

I maintain Tagvico, an open-source companion for Paperless-ngx. I added Ollama because document text is exactly the kind of data many people do not want to send to a hosted model. The surprising failu

Ollama automatically unloads inactive models from memory based on inactivity parameters, with models being removed after a specified duration of non-use . By default, Ollama unloads a model after 5 mi

Cosmos3-Super-Text2Image is a 64 billion parameter omnimodal world model capable of generating high-quality images from text inputs as part of NVIDIA's Cosmos 3 foundation model platform. The model is

This Reddit post from r/ollama asks about story-writing language models that can run on a 5080 GPU with 16GB of VRAM . The discussion likely covers recommended open-source or quantized models suitable

A guide on disabling thinking mode in Ollama models using the CLI by running models with the `--think=false` flag or using `/set nothink` followed by a prompt. The post likely discusses how to configu

The Ollama Cloud Subscription includes a feature described as 'Run cloud models at a time,' which refers to how many AI models a user can have simultaneously loaded and running in the cloud at any giv

This Reddit post from r/MachineLearning discusses the concept of decomposing machine learning models into a graph database representation, treating a model's components — such as layers, weights, and

This r/ollama thread discusses community advice on configuring a locally-run AI model (via Ollama) to automatically generate Word documents or reports, covering topics such as model selection, scripti

This Reddit post discusses using the Ostris AI-Toolkit to train a LoRA (Low-Rank Adaptation) model targeting the 'Anima' Stable Diffusion model. The Ostris AI Toolkit is a powerful framework that allo

I was unable to retrieve the specific Reddit thread at the provided URL, and the search results did not return content from that exact post. The search results returned related but distinct issues ...

For users running Ollama on an NVIDIA RTX 4060 Ti with 8GB VRAM and 16GB system RAM, the community consensus recommends 7B–8B parameter models (such as Llama 3.1 8B, Mistral 7B, or Qwen 8B) using Q...

https://huggingface.co/swiss-ai/Apertus-v1.5-70B https://huggingface.co/swiss-ai/Apertus-v1.5-8B Apertus 1.5 is a family of 8B and 70B parameter language models designed to advance the state of multil

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

Users on the r/ollama subreddit reported that the **Gemma 4 E4B** model in Ollama offloads layers to RAM even when GPU VRAM is only partially utilized. This behavior is linked to how Ollama and lla...

Needs a lot of requests compared to Qwen (almost twice) and Gemma (almost x3). Final score is fine, even though it is 'not a coding model' https://wonderrico.github.io/local_llm_benchmark/benchmark-ma

[Fully open source under GPL3, made from the ground up for use with local models, no subscriptions, no corporate backing] When i first started this, it was meant to be a fully lightweight, extremely m

152 generations, deterministic grading (exact number/string/JSON/regex), no LLM judge on my 16GB laptop. task type | deepseek-r1:1.5b (1.1GB) | llama3.2:3b (2.0GB) | gemma:2b | codellama 7b arithmetic

I tested Ling-3.0-flash with hard bugs and it fixed bugs that qwen3.6-27b could not. This models speed faster than deepseek v4 flash but almost the same level as (old) deepseek v4 flash. Note: hard bu

It's an encoder-only transformer that consumes past(blood glucose + carbs + insulin) and future(carbs + insulin) and predicts future blood glucose for the next 2 hours. Announced meals and boluses/bas

I can run the mediums, but sometimes I want a faster option that's smarter than Qwen 27B/35B. On my hardware I get like 500 to 800 tok/s prefill and 16 to 22 tok/s gen on ~120B class models, which is

I've been seeing a lot of news about the latest gemma 4 and qwen 3.6 being really good and the current go-to models but those are out of reach for my GPU at the moment. With 4GB VRAM and 40 GB RAM, I

https://preview.redd.it/qoogv5m1skfh1.png?width=688&format=png&auto=webp&s=3f06fb28ceec3cd3ab95bcebd0c71374332aac9b Built a simple desktop GUI (Tkinter) that supports multiple local TTS engines (curre

3 year lurker, now i finally got my server up and running. dont know which model to choose. llama.cpp or vllm, what makes more sense? mainly single user with maybe 2-3 more additional users in family,

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

A researcher released an open-source softmax-free attention model at GPT-2 Medium scale (354M parameters trained on 11.5B tokens) that uses structural sparsity and tile-skipping kernels to reduce VRAM

A discussion on r/ollama exploring which high-performance LLM models can be effectively run locally on standard laptop hardware , likely covering model size comparisons, hardware requirements, and per

Ollama exposes an Anthropic-compatible Messages endpoint , allowing developers to run powerful open-source AI models locally with no API costs and pair them with Claude Code for a capable local AI cod

This call for papers announces a workshop focused on the growing need for efficient and effective techniques for editing trained models, especially large generative models. The workshop solicits paper

This post provides a detailed review and practical guide for setting up and testing Ollama with DeepSeek models specifically on Ryzen APU systems. It likely covers performance benchmarks, configuratio

NVIDIA Nemotron 3 Nano Omni is a multimodal large language model that unifies video, audio, image, and text understanding for enterprise Q&A, summarization, transcription, and document intelligence, w

Anthropic's Claude Code desktop app is strictly optimized for Anthropic's models , creating a 'walled garden' effect that restricts users to Claude exclusively. The redesigned Claude Code desktop app

A Reddit post from r/ollama in which a user shares their experience running a 31B parameter model locally using Ollama, reflecting on the surprisingly demanding hardware and infrastructure requirement

This r/ollama thread is a community discussion where users share their preferred cloud-based AI models for coding tasks and compare their reasoning capabilities. The conversation likely highlights pop

A Reddit user exploring Ollama Cloud noted that, at the time of their post, only the Kimi model supported image (vision/multimodal) inputs among the available cloud models. Kimi K2.5 is a native multi