Search: “nvidia”

For anyone interested, here are the llama-bench results on 3 bit K_XL quantization. I think this could be pushed further but no luck so far. CURRENT RESULTS: full moe offloading Prefill suffers 116 --

It's more accurate to say that many highly engaged online gamers are hostile to AI, not that 'gamers' as a whole are. Gaming is a huge community with hundreds of millions of people, and opinions vary

Has anyone figured out how to enable speculative decoding with deepseek v4 flash 0731 on llamacpp? I’m on the right release for llamacpp (b10228 or earlier) and running am17an’s draft model with unslo

Where to even begin on this one...I guess I should start by acknowledging the risk vs reward for vendors other than nvidia, so: Yes I understand that nvidia are dominant currently on speed (llm and im

Nvidia reportedly halts GeForce RTX 5090 production in favor of AI data center and professional GPUs — impending supply drought expected to drive up prices, RTX 5080 24GB rumored as new gaming flagshi

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

I wanted to see whether NInfer could run Qwen3.8-27B on an RTX PRO 4000 Blackwell 24GB. Hardware/software: NVIDIA RTX PRO 4000 Blackwell, 24GB 145W power limit CUDA 13.3 NVIDIA driver 610.x Ubuntu LXC

So here's the thing, almost everyone use NVIDIA to run their LLMs, we also do the same, a lot of people we've met use like RTX PRO 6000 or even H100, B300 It seems like everyone eyes is looking at NVI

This is the Qwen3.8-27B setup I actually use every day on one RTX 5090. I wanted to write it down with enough detail that another 5090 owner can reproduce it instead of guessing which memory knobs I u

I've been out of these forums for awhile but I figured I would provide a formal update on how this has been going now that it has some operation time under its belt, just to put the information out th

Turns out a regular ethernet cable between 2 nodes can run laguna UD-Q2_K_XL (39.7GB) using a direct point to point network. Interestingly on `nvidia-smi dmon -s pucvmet -d 2`, the inter/intra gpu tra

I've been struggling with the ollama update process. I have both nvidia and amd GPUs in my system. I have two instances of ollama running on different ports for this to work around issues. AMD 7800xt

Hey everyone, I’m new to running AI models locally and I’d like some advice. My laptop specs are: HP OMEN 15 CPU: Intel i5-8300H RAM: 16 GB GPU: NVIDIA GTX 1050 Ti 4 GB VRAM OS: Windows I’m planning t

Da un po mi sono ritrovato in garage un hp z840 da 64gb ddr5 montate (ora) e 2 processori con una gpu un po scarsina una nvidia quadro k680 (da aggiornare) avrei bisogno di un consiglio: quale modello

I have a 5070 Ti and two 5060 Ti (all 16Gb cards). I planned to add another 5070 Ti giving me two pairs of 32Gb each but the NVidia prices have just jumped by 25% where I am and I've found a 3090 Foun

Sori-1B is a 1B-parameter audio-language model built by a single SNU researcher whose core claim to fame is that its decoder is trained entirely from scratch on audio-paired text — no text-only pretra

tldr: went from 16~ t/s to 27~ t/s generation. got my usable context up from 220k to the full 262k without sacrificing anything. prefill also increased from 376 to 573 command I ended up with, fwiw: l

The earlier post on this subreddit by 20+ companies signing the petition including Microsoft, Meta, Nvidia, YC (https://www.microsoft.com/en-us/corporate-responsibility/topics/open-weight/) etc plus t

Setting a GPU power limit using nvidia-smi reduces heat output by approximately 20% with only a 5-8% inference speed loss. Undervolting the GPU can reduce power consumption by 5-15% with zero performa

This Reddit thread from r/ollama discusses community recommendations for purchasing or renting GPU servers to run Ollama and local LLMs. It likely covers options ranging from dedicated GPU server prov

TurboOCR is a high-performance OCR project that combines PaddleOCR with NVIDIA TensorRT, implemented in C++ and CUDA, achieving throughput of 270–1,200 images per second using FP16 half-precision infe

Hi guys! I got a problem with one of my V100 SXM2 Modules. In 'nvidia-smi' its shows with 'Pwr:Usage/Cap' as 'N/A / N/A'. When I try to use it i get the following error in dmesg: NVRM: Xid (PCI:0000:0

In my attempt to combat powerty; as electricity cost a ton these days and it is hot as hell, I consolidated 2 machines into one, so my 2 crappy machines now are one, and that means a bit less power an

I’ve been experimenting with neural rendering outside a game engine and built a native Windows video player around it. It prepares a neural-rendered version of a video, caches it, and lets you switch

Repost because reddit keeps thinking this is piracy or illegal. It is neither. A lot of people are skeptical Nvidia will keep huggingface intact now that they will buy huggingface. There's a lot of do

A lot of people are skeptical Nvidia will keep huggingface intact now that they will buy huggingface. There's a lot of doom and gloom about not having any alternatives, removing nsfw models, saying th

New/Old benchmark that provides a lot of answers for local LLM. I present to you a new test that I developed somewhat by accident: https://huggingface.co/cHunter789/Qwen3.8-27B-i1-IQ4_KS_KT-GGUF/tree/

seems to be about as good as a vega 56 with 16Gb of VRAM, is it worth it? (don’t want to deal with NVIDIA drivers on Linux, already have an rx6650xt and might simply use vulkan for llamacpp inference)

# Running DeepSeek-V4-Flash-0731 (155 GB MoE) on a DGX Spark with vLLM-Moet 2-bit quantization I used Deepseek-v4-Flash-0731 cloud API settig up vllm-moet to run deepseek-v4-flash with MTP locally on

Setup as follows: Proxmox -> Debian -> Docker -> Ollama. Other containers work. Compose file contains gpu device. Does it need nvidia runtime or any other options? If someone could provide an example

Everything runs through WebGPU, in-browser or in electron/tauri apps. It's fully portable and supports either Nvidia and Apple Silicon (Metal). The actual kernels are optimized for the specific hardwa

torch-nvenc-compress is a Python library that leverages GPU NVENC (NVIDIA's hardware video encoding) to optimize PCIe bandwidth utilization by compressing data during transfer. The project implements

This is a r/ollama community support thread where a user is struggling to configure Ollama and Open WebUI together in Docker containers with NVIDIA CUDA/GPU acceleration enabled. Common issues in this

I've been reading about all these modders using AI to reverse-engineer games and software. I've been trying out photocraft and gridcraft and have just watched a GTA5 mod featuring Sonic. It's pretty d

https://preview.redd.it/p6i9qifyy8vh1.png?width=2069&format=png&auto=webp&s=2b1e3c7c4fc95f12f0f7d417a4d21410aebfbd35 The 3090 Founders edition has a reputation for hot VRAM. Since LLM token generation

I am an independent researcher. Due to budget constraints, I shifted my 21B MoE pre-training—which I had originally planned to run on 64 H100s—to a single NVIDIA GH200 ($2.29 per hour), and I have com

Benchmarking an LLM here with a NVIDIA RTX 5070 12 GB VRAM here I had been working on a llama.cpp based expert streaming setup for Qwen3.8-Flash-Next 177B (UD-IQ3_XXS) on Windows. Benchmark is about 1

I am trying to import two large datasets to enable statistical analysis. After importing the second dataset, Ollama tells me it has no record of that dataset. Intel i9-11900KF Nvidia 3080Ti 12GB Ubunt

I have been building a somewhat unusual local inference machine around two Huawei Atlas 300I Duo cards. They are relatively inexpensive, passive, dual-accelerator PCIe cards with 96 GB of device memor

I'm part of the Lokutor team that built this. Model: NVIDIA Conformer-CTC Small (13M params, int8). It runs on an ESP32-S3 with 8 MB PSRAM, no GPU or NPU. LibriSpeech WER is 3.7 / 8.2, versus 6.3 / 15

Kijai put his magic to good use to improve your MiniMax H3 workflows. The video VAE now encodes up to ~2.2x faster and decodes ~1.4-2.7x faster on Nvidia GPU. Checkout the blog post how to use it: htt

TL;DR: I run a mismatched Tesla V100-PCIE pair—one 16 GB card and one 32 GB card, 48 GB total—in a Proxmox/LXC-based local-inference lab. The practical winner so far is a recent CUDA build of llama.cp

With the recent Nvidia Huggingface acquisition and frontier AI labs screaming about safety and putting guardrails everywhere, I think it's important that we have local models that aren't affected by a

Hey everyone — I’m building TensorSharp, an open-source LLM inference engine. Here are the latest DeepSeek V4.1 Flash GGUF results using its native ggml_cuda backend. Setup: 8× NVIDIA A40, layer split

Hi! Today I'm releasing MageTrail, a Danbooru/E621 proof of concept Full-Finetune of Microsoft's MageFlow 4B T2I model, using a diversity maximized condensed 41k images dataset (originally made by Lod

https://huggingface.co/XHToken/Spark-X2.5-4B-GGUF https://huggingface.co/XHToken/Spark-X2.5-1.7B-GGUF from XHToken: We are introducing Spark-X2.5-4B and Spark-X2.5-1.7B, two compact, general-purpose l