Search: “nvidia”

I used Claude Code to help write this pipeline - Gemma4 to turn an idea into a short story, then IndexTTS 2.5 running on an NVIDIA 3080 to use voices from LibreVox and VTCK voices to pin as character

Hi everyone, I'm currently working on optimizing an LLM setup at my company and I'm trying to identify where the actual performance bottleneck is. Our current setup is roughly: LLM: NVIDIA Nemotron mo

Released today: version 1.3 of energygraph Zero build dependencies, lightweight tool for live views of the power-consumption. Version 1.3 adds support for dGPUs from nvidia, intel, amd. Depending on v

Component Validated configuration Motherboard ASRock Rack SPC621D8U-2T/OVH CPU Xeon Gold 6330 (Get gold/platinum if interested in Optane Pmem gimmicks) GPU fabric Two Broadcom/PLX PEX88096 islands, ei

There are already plenty of different extensions for voice input, but all I found required having a second server running. I wanted something super simplistic: launching local STT server just for my p

High-performance inference of NVIDIA's Parakeet TDT 0.6B V2 English transcription model, in the browser. Check out the live demo: https://parakeet.narcotic.sh/ A fully custom, dependancy-free implemen

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

Ran DeepSeek V4-Flash-0731 — the full official checkpoint, not a re-quant — on commodity used hardware. Sharing because I couldn't find anyone else publishing Ampere results for this engine. Why bothe

TensorSharp supports DSpark on Deepseek v4 Flash 0731 now. Here is the benchmark result on 4x Nvidia A40 GPUs, cuda 12.8 with/without DSpark: Model: DeepSeek-V4-Flash-0731-UD-Q8_K_XL from https://hugg

’Tis the season of AI open letters and manifestos, apparently. Mark Zuckerberg has now entered the debate over the future of AI with a WSJ op-ed published today - and frankly, his position is much mor

I've been building Krasis, an MoE-focused runtime for streaming big models through limited VRAM on NVIDIA consumer/workstation GPUs, and I think this is the most interesting result so far: Ornith-1.0-

Hello, I've been learning how to use local LLMs for a year or so on my workstation, using a RTX3090. Current setup : - i5 12400 - 64gb RAM - RTX 3090 - OS : Fedora KDE workstation I'm using LMStudio t

RTX 4070, 32gb system ram, Linux. NVIDIA-SMI 610.43.03, KMD Version: 610.43.03, CUDA UMD Version: 13.3 Systemd service modifications: [Service] Environment='OLLAMA_HOST=0.0.0.0:11434' Environment='OLL

A developer documented their experience building a fully-local paper Retrieval-Augmented Generation (RAG) system using two NVIDIA GTX 1080 Ti GPUs and one RTX 3090, sharing three significant challenge

Cosmos3-Super-Image2Video is an omnimodal world model capable of generating video from combinations of text and image inputs . The model is designed to run on workstation-grade compute like the NVIDIA

This Reddit post discusses a technical setup for running Ollama with three NVIDIA RTX 3060 GPUs (each with 12GB VRAM) on a Machinist motherboard paired with a Xeon processor and 32GB of system RAM. Th

A discussion about difficulties getting Ollama to fully utilize dual NVIDIA RTX 3090 GPUs when running various language models including 8B and 70B parameter models. Users report that despite Ollama r

The AMD Ryzen AI Max+ 395 'Strix Halo' APU outperforms the NVIDIA RTX 5080 by up to 3x in AI benchmarks, particularly for language models, with 128GB of accessible VRAM compared to the RTX 5080's 16GB

Ollama's MLX engine runs on NVIDIA GPUs via CUDA v13 on Windows and Linux. Users have reported that Ollama crashes on RTX 3060 with cuda_v13 in versions 0.13.0 through 0.15.6, while deleting the cuda_

Production low-latency autocomplete implementations employ diverse strategies including inference server optimization (tools like vLLM, llama.cpp, NVIDIA Triton), deployment choices (cloud APIs, on-pr

LTX Desktop 1.0.5 is an open-source desktop app for generating videos with LTX models on Windows/Linux NVIDIA GPUs locally or via API . The version 1.0.5 release includes bug fixes such as LTX API ins

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

The NVIDIA Tesla K80 is a legacy GPU that can run modern LLMs through Ollama with community-maintained patches, since official Ollama dropped support for CUDA Compute Capability 3.7 hardware. Each K80

This post compares two high-end graphics cards—the AMD Radeon RX 7900 XTX and NVIDIA GeForce RTX 4070 Ti Super—across multiple demanding workloads including gaming, AI image generation with Comfy UI,

This r/StableDiffusion post addresses a common issue where users running Stable Diffusion on an NVIDIA GTX 1660 Ti GPU receive only black images as output instead of generated content. The problem is

This Reddit post from r/ollama discusses a user's experience running Cline (an AI coding agent) with Ollama on a high-end local hardware setup consisting of an NVIDIA RTX 4090 with 24GB VRAM and an In

A Reddit user shared a community-made patch to enable proper FP16 support for the Ernie Image model in ComfyUI, targeting NVIDIA 20-series (Turing) GPUs. 20-series cards do not support bfloat16 , and

Lyra 2.0 is an NVIDIA research project that extends the original Lyra framework for generative 3D world creation, using a self-distillation approach to distill the implicit 3D knowledge in video diffu

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

A bug was identified in NVIDIA's cuBLAS library where `cublasSgemmStridedBatched` dispatches the same suboptimal `cutlass_80_simt_sgemm_128x32_8x5` kernel for every batched FP32 workload from 256×...

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://preview.redd.it/3ekngxk224vh1.png?width=1080&format=png&auto=webp&s=9bfe5c92033e17d5b2fb4529f1320c99455a138b I built a GPU compiler and wrote an article about it, focusing on concepts shared b

It's been 4 years since c.ai first hallucination model, and yet, we're nowhere good enough at LLMs in terms of spontaneity/interesting hallucination features. Fortunately, last year brought new archit

DISCLAIMER: the post and the model card was made with the assist of AI. Hiya, I’m releasing Recursive BitNet N-Gram 102M, a small experiment combining ternary weights, shared transformer layers, and h

Alright, I learend a few valuable lessons since I posted about a week ago, and I've made more strides with the DDR4x Ascend 96GB 310P cards I purchased, so here we go, meet the new friendly and less v

Hi folks, LIVE PROJECT PAGE TLDR: Moral of the story. You need better CPU to do actual agentic coding doing real work... I've been on a mission to make my RTX5090 go brrr for past 2 months so much so

I forked Strata and worked with Opus 5.5 with some heavy changes to it to make it work on an IBM AC922 I have access to. The IBM AC922 is a 2018 era beast with two POWER9 20 core SMT4 CPUs that are co

​ From the first LLaMA 33B I knew I wanted that magic-like intelligence locally, mine, so nobody could take it away when I needed it. I bought a 3090 for my home PC. Then LLaMA 65B appeared and I was

About a month ago I was having FOMO and was going to spend coin I don't really have on new graphics cards. Instead of doing that though I decided to spend the money on a new motherboard+cpu and try to

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

Illinois folks (like myself), write your governor, please. And if you live elsewhere, please pay attention to your local/state politics. https://wgntv.com/politics-3/pritzker-establishes-ai-cabinet-to

I gave Jev, Laya, a finetuned ModernCE-base-nli and a finetuned Qwen3.5-4B the controls to Doom. Thanks to TypeSafe AI for Jev access. The video lines up the starts of four separate games with the sam

Don't get me wrong, not hating on Qwen 2.1 but it DOES have all the hallmarks of GPT's weird 'texture' all over it. Is this just a distilled model of one of the GPT Image models? Similar how many LLMs

Been building this for a few months, mostly for myself, and it just got a proper release so figured I'd post it. It's a native GGUF inference runtime with OpenAI/Anthropic-compatible APIs and a chat U

Basically the title. Training models take time and if a model was already in the process of pre-training/RL then it can't be re-cooked with any new architectural improvement that has been discovered i

I wish I could spend $15k on my own homelab hardware, but no this is for work lol. Like the title says, we're looking to run DSV4 Flash (and similar tier models) locally at good speeds, both for token