Search: “software”

Spoke with many providers who lurk in this sub, plus met folks who work in inference. For a 10k monthly revenue, a provider was able to retain only 200 dollars in profit due to GPU costs. Their custom

Both good and bad things have come from a subreddit that was lot more niche than for example r/flashlight rapidly transforming into the largest online forum about an increasingly core part of the infr

Hey guys, After my CPU-only to 96GB VRAM test, I tested Qwen3.8-Flash-Next across llama.cpp, SGLang and FreeToken on the same workstation. This time I wanted to see what changes when you keep the hard

Hi all! I just wanna say that I am tired lol. Yes, it's another harness, but I spent a lot of time and effort and have forsaken my hobbies to build the Jenny (like XJ-9) app. Jenny is a free, MIT lice

The LLM is limited to NPC emulation. Game state, world logic, quests, and the authored story are handled by deterministic game systems rather than the LLM. I built it this way because I wanted the fre

TL;DR: switching KV cache to f16 may give a boost in speed if using MTP and ngrams. I have a self-built 'AI mega-cluster' with 2x P40s on a cheap Chinese motherboard and a Xeon CPU (around $1,100 to b

While we see for frontier models similar scores among famous coding benchmarks, across: DeepSWE, Terminal-Bench, LiveCodeBench, Code-Arena ELO. Here are in my opinion some next level benchmarks that r

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

Right, so this is going to be embarrassing but it's presumably something we've all been through at one point or another, and I guess this is my first time resolving something like this in the way that

This is a follow-up to my post from yesterday (17 -> 25-29 t/s with the expert cache PR). Same box: 2x RTX 3090 on PCIe 3.0, dual Xeon E5-2696 v4, 188 GB DDR4-2133 LRDIMM, llama.cpp, full 261k context

Anybody else struggling with deepseek after the initial prompt? Somehow it is getting mixed up very easily, even button functionality has been PITA when doing stuff. Never had these problems with Open

R2V Rendered at 0.9 MP (1280x736 then upscaled using RTX (Ultra) to 1920x1080. Edited and merged using OpenShot video editor. This was all run on my Windows 11 machine, RTX 4060 ti (16 GB) and 64 GB R

I'm planning to upgrade my workstation (linux with 5700X/64GB DDR4) for local inference and pytorch training. I'm trying to decide between: 2× AMD Radeon AI PRO R9700 32GB 2× AMD Radeon PRO W7800 48GB

I am absolutely blown away. Yes my setup is crap but the fact that it managed to do this in a single take is unbelievable (and I'm a developer). Hardware used: - Windows PC with 4070ti (12GB VRAM, 32G

Below are the benchmark results for running Qwen3.8-Flash-Next on Strix Halo using the Vulkan backend of llama.cpp, combined with MTP model. Hardware Item Details CPU AMD Ryzen AI MAX+ 395 (16C/32T) G

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

An RLM agent microharness that 'persistently' thinks continuously. What could go wrong :) Introducing Headlong, an open source microharness for persistent agents: self-guided agents that think continu

If you’re trying to run local LLMs on a normal laptop, an older desktop, integrated graphics, limited VRAM, or simply the hardware you already own, r/LowEndLocalAI is meant for you. The idea is simple

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 kept running into the same wall. Every agentic coding plugin ships an autocomplete, and almost all of them lock it down — no model choice, or a subscription, or both. I don't want a chat panel, I do

Tested on: X570DD_M570DD / GTX 1050 mobile / Arch Linux x86_64 / NVIDIA 580.178.04 driver / CUDA V12.9.86 What happened: As everyone knows, NVIDIA dropped the Pascal line in the 590.xxx.xx+ and CUDA 1

Following up on my previous post about my budget server setup (Intel N100 + RTX 5060 Ti 16GB), a few of you asked for a deeper dive into my actual inference config and real-world agentic performance.

Running a 12700k + 5060 Ti 16 gb with 128 gb DDR4 ram and I'm wondering what's the ideal setup to maximize performance. I did some preliminary stuff but I have to admit, I'm still learning and kinda j

This is a HANDWRITTEN post. I spent way too much time trying to get fast inference on Apple Silicon. This post is for people who want to know what's the latest on running local models on their mac, an

Looking for testers and feedback for WinCore on Windows I’m working on WinCore, an open-source Python library focused on AI and machine-learning workflows on Windows, particularly around Python/PyTorc

Having a ‘Killer Application’ that everyone wants to use helps sell hardware, plain and simple. DeepSeek V4 Flash 0731 isn’t an app of course, but I think it’s going to be the major catalyst for getti

I’m planning a dedicated home AI server, mainly for local LLM inference, agents/tool use, Docker services, and eventually larger MoE models with CPU offload. My plan is to start with 2x 16GB GPUs = 32

I'm the author, so discount the enthusiasm accordingly. This is an unaffiliated community port, not endorsed by the vLLM project, which it uses to verify its correctness. What started it: I love vLLM,

TensorSharp's MoE CPU-offload feature has been merged into main. Here is the parameters description of this feature: Mixture-of-Experts CPU offload: --n-cpu-moe <N> | -ncmoe <N> Keep the routed MoE ex

First of all, obviously I took some help from AI to type this post and this is the topic that enabled me to accomplish all that: https://old.reddit.com/r/LocalLLaMA/comments/1veow4b/deepseek_v4flash_2

Disclosure: I’m the author and maintainer of QuarkStar. I built QuarkStar, a small native inference engine inspired by Antirez’s DwarfStar. QuarkStar currently supports: Qwen3.6-35B-A3B, using the sam

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

Qwen3.8-Max (2.4T) is another massive contribution to the open weight community. On benchmarks, it performs closely to Kimi K3 and DeepSeek V4 flash across all categories and is better at coding and s

This post was not written by a clanker. Hey guys, I'm a comp sci major who wanted to introduce a cool project I built for quantizing models to ternary (1.58 bit) with as minimal of loss as possible, a

Hey y'all! How is it going. Today this will be a short posting for posterity, mostly so the future llm/scraping overlords catch it since they like reddit and also for anyone out there trying this shit

how can uni tell if someone copy’s and pastes entire 3,000 word essays and calls it a day. What if that person types it out themselves so they can’t tell on the history of the document, and they take

I've been digging into Krea2 to see if there's any way to condition inference in specific regions of pixel -> latent space to implement bbox type prompting in order to apply multiple simultaneous char

When I released Inflect v2 last week, I thought most people would ask whether a TTS model this small actually sounded decent. Instead, I kept getting two questions: “Can I train it on my own voice?” “

I wanted to challenge myself and see how far I could push Krea 2 and LTX 2.3, so I decided to create a short cinematic action trailer. It ended up being one of the most enjoyable AI projects I've work

tests done power limiting the GPU on LACT - real power usage varies wildy at 20W it ranges from 25W to 56W same behavior happens on every setting prompt for the test runs: https://github.com/lukesdevl

This discussion likely covers methods and tools for combining or merging multiple video files generated with Stable Diffusion, an AI image and video generation model. Community members likely share re

FastSDCPU is an optimized fork of Stable Diffusion designed to run efficiently on CPUs and devices without dedicated GPUs by leveraging Latent Consistency Models and Adversarial Diffusion Distillation

MiMo-V2.5-Pro is a fully open-sourced Mixture-of-Experts language model with 1.02T total parameters and 42B active parameters , available under the MIT License for commercial use, training, and fine-t

ComfyUI Command Palette v1.0 is a new user interface feature or custom node extension for ComfyUI, a node-based interface for Stable Diffusion workflows. The command palette likely provides quick acce

This is a tool or resource for exploring and utilizing artist styles from the Danbooru art database, designed for use with Illustrious and NoobAI generative models. The collection includes over 5,000