Search: “models”

This Reddit thread from r/StableDiffusion discusses best practices for captioning training datasets when fine-tuning LoRA models on LTX 2.3, Lightricks' video generation model. The community emphasis

Users in the r/ollama community report that running OpenClaw with the Gemma4 26B model via Ollama results in pathologically slow first-turn performance, with the degree of slowdown scaling with OpenCl

A Reddit post on r/StableDiffusion announces an in-person open source AI art hackathon held in Paris, co-organized with LTX (Lightricks' open source AI video model) and NVIDIA. The event likely invite

Tencent's HunyuanWorld is an open-source multimodal 3D world generation model from the Tencent Hunyuan team, featuring 360° immersive experiences via panoramic world proxies, mesh export capabilities

This r/MachineLearning discussion post details a hands-on benchmark study in which TranslateGemma — Google's open translation model suite built on Gemma 3, available in 4B, 12B, and 27B sizes and cove

A Reddit post on r/StableDiffusion pointing the AceStep team toward a potential dataset source for training their open-source AI music generation model. AceStep is a music foundation model whose train

This r/StableDiffusion thread addresses user difficulties running ACE-Step 1.5 XL in ComfyUI — an AI music generation model that was released on April 2, 2026, featuring a 4B-parameter DiT decoder for

This Reddit thread on r/ollama likely discusses where and how to use Ollama's cloud offering, which allows models to run without a powerful local GPU by automatically offloading computation to Ollama'

A new speed-focused LoRA for the Wan 2.2 video generation model, released by the LightX2V project on April 26, 2024, shared on the r/StableDiffusion community. The LightX2V distilled LoRA dramatically

This Reddit post from r/StableDiffusion announces the release of 'Distilled v1.1,' an updated version of a knowledge-distilled Stable Diffusion model, likely building on prior distillation work that p

This r/StableDiffusion post demonstrates running AceStep 1.5 XL Turbo alongside LTX Video 2.3 on a laptop equipped with an 8GB NVIDIA RTX 5060 GPU — a notable feat given that the XL (4B) model require

This Reddit thread from r/StableDiffusion discusses the compatibility of compact LLMs — Qwen3.5 4B and Gemma 4 E4B — as text encoder/LLM components within Z-Image and Z-Image Turbo image generation wo

This Reddit thread discusses how to configure Ollama for use with Claude Code locally, covering two key setup steps. By default, Ollama uses a context window of only 4,096 tokens — insufficient for Cl

This Reddit post from r/StableDiffusion showcases a community-created ComfyUI workflow for the LTX-2.3 model — a DiT-based audio-video foundation model capable of generating synchronized video and aud

This Reddit thread from r/StableDiffusion addresses a common image quality issue where Tensor Art — a cloud-based Stable Diffusion platform — produces outputs with heavy, unwanted color tints. The dis

Ollama Cloud offers Free, Pro ($20/month), and Max ($100/month) subscription tiers for cloud-hosted inference, but token generation speed depends on model size, architecture, and hardware optimiza...

A 2-stage upscaling workflow using FLUX.2 Klein in ComfyUI combines the model's image-editing capabilities with a secondary upscaler (such as SeedVR2) to produce high-resolution outputs — for examp...

In 2025, CivitAI underwent several significant platform changes. In April–May 2025, CivitAI tightened rules around extreme/illegal content and real-person likenesses. After its payment processor...

A Reddit thread (r/ollama) where a user reports errors when attempting to run Ollama cloud-hosted models via the VS Code integrated terminal. The discussion reflects a broader known issue where env...

OmniVoice is an open-source, zero-shot multilingual text-to-speech model developed by the k2-fsa (Xiaomi AI Lab) team, supporting over 600 languages — the broadest language coverage of any zero-sho...

Applying PCA as a rotation step before naively truncating embeddings from non-Matryoshka models like BGE-M3 can recover much of the retrieval quality that is otherwise lost when simply chopping dim...

Since lot's of people were sceptical or whatever, heres how to uncensor / jailbreak V4 flash and proof. No it is not lead on whatever, first prompt, first try, every time. Put this in System message:

Link to the article: KV Cache Quantization on Gemma 4 31B: Non-QAT vs QAT KLD benchmarks with BeeLlama.cpp v0.4.3, fork of llama.cpp with more KV cache quantization options, comparing Gemma Q4_0 non-Q

Liquid AI put out LFM2.5-VL-3B today, which is a 3.1B vision model that weighs roughly 2GB and fits well on a phone Benchmarks are benchmarks so I tried something sillier. Took a photo of a little Ste

Muse Glimmer 30B feels significantly more precise and reliable, it almost never drops the ball or breaks rules. However, its designs lack creative depth and richness. Qwen3.6 35B, on the other hand, i

I'm very happy with some Linux admin tasks I'm throwing at a locally running DeepSeek. My request was simple, check why 'samples' folder is taking more and more space on one of the machines on my LAN,

aetherbird has done some great work getting Ling-3.0 to work in llama.cpp. The architecture is generally identical to deepseekv2. I recently added a microscopic 40 line PR to his that adds support for

GPT-5.6 Sol High and X-High (Web Chat) feels severely nerfed since 08/06/2026 update (https://openai.com/index/improving-gpt-5-6-sol-in-chatgpt) I use it for a pretty complex Unreal Engine 5 project (

Obviously nobody needs a transformer that's good at multiplication. I wanted to know whether a stock transformer could do exact arithmetic if I chose its weights directly. I implemented the grade-scho

I’m running DSV4F 0731 on dual spark, and honestly… wow. It’s an absolute workhorse, and the benchmarks are real. Everyday tasks with Hermes agent? Effortless. Coding tasks with OpenCode? I’m genuinel

What IDE are you using. its another problem area for me . I usually use VSCode , but with local llms I have not found an extension which works optimally VSCode CoPilot chat with Ollama: CoPilot bloats

(I am not a native speaker, written by myself, so please bear with me) I really want to like DeepSeek-V4-Flash-0731. But it has serious flaws that don't align with the high score on intelligence bench

Basically what the title says. For me, it would always crash and burn trying to use tensor split. Apparently, there's some bug where GPU memory gets corrupted with the default microbatch (512) or high

Build a 100% offline fast Retrieval Augmented Generation (RAG) system that runs without an internet connection, without cloud APIs, without OpenAI/Ollama Published a video where you can build a fully

I was going through the current llama.cpp CPU PRs and #26348 stood out because this isn't the usual +5% kernel optimization. It adds an x86 VNNI implementation for the Q2_0 × Q8_0 dot product, and the

Press My earlier prediction that Tesla would buy them completely missed the mark. With AMD focusing heavily on the enterprise side, the idea of consumer-facing hot-swappable AI model chips looks prett

Hey everyone, I just wanted to share my journey here for some motivation. Three years ago, I saw the sudden spike in AI and realized it was the future of tech. My goal at the time was to be an indie g

I swear AA is not the bipartisan they so claim. An open source mode (Qwen 3.8 max) was number 1 on the agentic index, then they just so happen to launch 'v4.1.1' of their index in which they just adju

First of all, my setup: Ryzen 9 5950x DDR4 3200Mhz 64gb (2x32) Dual 3090s, no NVLINK Runtime: llama.cpp Nvidia Drivers 610 Windows 11 25H2 Qwen 3.6 27B Q8 I've been using llama-server with --split-mod

There are a lot of LLM benchmarks but few, if any, harness benchmarks. I am thinking this would be a really good community project to build one. End goal: a leaderboard of harness performance (multipl

I'm mosty interested in 128-192GB VRAM with 128-256GB RAM to spare, so SSD streaming is basically not even necessary. Seems only FP4 is supported, so older hardware will likely be slow - no Unsloth GG

I don't own a mac Right now, i want to buy one but its main job will be to host a Ollama or similar software to give me usable AI models in my network, since I don't want to pay for Cloude, GitHub cop

A new llama.cpp PR (#26563) adds a heatmap that tracks which MoE experts are used most often. Instead of keeping every expert on the GPU or offloading all of them, it caches the frequently selected ex

I've been working on speeding up DeepSeek-V4-Flash-0731 in Krasis and have now got the long-prompt prefill quite a bit faster on a single RTX PRO 6000 96GB. These are timing-disabled internal Krasis r

https://preview.redd.it/522fsdwvtdhh1.png?width=1200&format=png&auto=webp&s=6a6cf7a467514167a8193029dbd20fb3a9ba4f6c It ranks lower than both Sonnet 4.6 and Luna. I'd wager Luna costs in the same ball

Went public in the last few minutes, both repos ungated. Ling-3.0-flash, BF16, 24 shards, ~255GB Ling-3.0-flash-fp8, official FP8, ~128GB 127.5B total, they quote 5.1B active. What jumped out at me in