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Hi folks, I'm a long-time lurker and big fan of this subreddit and a massive self-hosting fan (also outside of AI). I doubt many people will disagree with me here because I see the same arguments bein

https://preview.redd.it/xs01ds930nsh1.png?width=4800&format=png&auto=webp&s=939762bcf3fbd93e137d4f97e927dda38aaf30fd Back in July I shared LokalBot here. It's a free, open-source Mac app that records

Image-to-3D models redraw your picture, and fine detail - text, logos, faces - comes back garbled or scuffed. My local pipeline that fixes it. (repo link at the end of the post) The latest update adds

Early this year when I was first looking at building up my inference capability you could get the 16GB Tesla P100s for between 60 and 80. Asked claude about it, told me absolutely not worth it. No ten

Good day data nerds! I am trying to get more into running models, learning about agentic workflows, and creating my own tools. But as you do (right?) I had to fine tune my current setup. With the way

Hi! I'm the author of MoEspresso, which is my way of putting my own ideas about inference engines to the test. A lot of the fun has been trying different design choices, measuring what happens, and fi

For those who have V100 cards, I wanted to point you to 1Cat-vLLM, a vLLM fork that enables optimized serving for these cards. Showing stats for Qwen3.6-35b comparing a Strix Halo with a hughly optimi

FYI the engine's default kernel rules were measured on smaller chips (16/20-core M5s and a 32-core M4 Max), so a 40-core M5 Max runs guesses. Splash's repo includes a developer tool, “make tune-kernel

I'm about to buy a Mac Studio mainly for running LLMs locally and I'm stuck between two configs: M5 Ultra (30/64) with 96GB: 1.2 TB/s bandwidth, roughly 1.7x faster generation and much faster prefill

Hey everyone, Jovan from UkisAI here! Today, we are introducing Swift, a family of efficient reasoning LLMs based on Qwen, trained by penalizing tokens related to pathological overthinking patterns an

So this jev thingy is getting kind of big... tbh it seems overhyped by a large margin, but here we are. Not that its bad, just feels like we usually ignored larger things... Anyway to the point of thi

Hey all, Henry from Cactus Compute here, I kinda wanted to share our latest model and get feedback from the family :) Needle 3 is a small foundation model for automation: you give it the functions you

I've built and open-sourced ParaRNN, a PyTorch/Triton library that parallelizes the training of non-linear recurrent architectures across time using Newton-Raphson iterations mapped to associative pre

Since the Qwen3.5 0.8B model is an interesting one for small specialized fine tunes, I was curious how fast it can run on CPUs. Why CPUs? Mainly because I want to use it as a local dictation cleanup m

I recently ported VDN-H3 (Video DeltaNet for MiniMax H3) to Vpipe and tested it on an M5 Pro 24GB. The benefit scales with both sequence length and resolution: at 832×480, VDN-H3 starts to pull ahead

I built a denser GGUF format for ternary models: Q2_B3 / “B3S” If you're running a ternary model like BitNet-b1.58 or Ternary-Bonsai, the weights are already restricted to -1, 0, or +1 times a block s

Quality: 81.1 → 87.7 (+8%) Speed: 35 → 29 tok/s (−16%) Runtime: 8m51s → 44m39s (5x longer) Output tokens: 18K → 78K (🤯) Noticeably better quality, but you're paying for it with tokens and time. Full b

Mac Studio, 96GB unified memory (M3 Ultra). I want the largest usable Qwen3.8-Flash-Next setup, and I'd rather not burn 100GB of bandwidth on the wrong download. Here's my math. Please tell me which p

Hey guys, FastVideo team here. We saw how important speed and quality is for everyone. And we've been working to create our own step distill checkpoints and LORAs for MINIMAX h3. Here's is our v1 rele

Got the new Qwen3.8-Flash-Next (176B total, 6B active MoE) running locally and figured I'd share for anyone else wondering if their setup can handle it. **My hardware:** 192GB DDR5 RAM, RTX 5070 Ti (1

I made a Discord for people who are genuinely into AI and want a decent place to talk about it. It’s still new, but the idea is to build a large community without arbitrary bans, hidden moderation dec

Hi folks, I have a 7800x3d + 32GB RAM + Rtx4090 and > 200TB of storage. I downloaded the Qwen 3.7 35B hauhaucs but it has been a disappointment so far because training data is too outdated (networking

Yesterday I downloaded Qwen3.8 as MLX from the Ollama library from the commandline on a MAC. Simple 'Ollama Pull xxx' This is the answer I get when I ask it what model it is... I swear to god this is

When Qwen3.8-27B dropped on Thursday the obvious question came up for us : does a 27B dense model actually fit on the 24GB Mac Mini machines? Ran it properly over the weekend on an M4 Pro (24GB unifie

LFM2.5-VL-3B is a multimodal variant of LFM2.5, a family of hybrid models designed for on-device deployment. It builds on LFM2-VL-3B with further mid- and post-training. LFM2.5-VL-3B can process both

I'm a retired platform engineer, coding mainly in Rust, and involved with a ML study group. I developed a ML programming language (alternative to Python, Colab) to help me learn (and teach) ML concept

Hey LocalLlaMa, Henry from Cactus here! We previously released Cactus Needle, a 14MB agentic LLM for tool call, device use, and structured extraction for phones, wearables, smart homes, small robots a

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

DeepSeek V4 Flash: Preview → 2026-07-31 Benchmark Preview 0731 Δ Terminal Bench* 56.9 82.7 +25.8 Toolathlon 51.8 70.3 +18.5 NL2Repo — 54.2 new Cybergym — 76.7 new DeepSWE — 54.4 new Agent Last Exam —

I've always found it a little strange that AI is everywhere, but the codecs we use in practice are the traditional hand-engineered systems like h.264, h.265, av1. Alexnet started the wave of neural ne

I got tired of my Ollama server sitting idle between chat experiments, so I pointed it at my Navidrome library and made it run a radio station. The DJ is an agent, not a shuffler. Each turn it gets to

https://reddit.com/link/1v5rvuq/video/bgmwc754i9fh1/player My goal was to create a benchmark to measure the spatial awareness and memory of models. Eventually, I came up with the simple idea of a maze

I've been considering Ollama's Cloud Max plan to replace my GLM Max plan but couldn't find good documentation on how their limits actually translate into GLM 5.2 usage. I know it's by GPU time but tha

The Ministral-3:3b model requires Ollama 0.13.1, which is in pre-release , and users encountering errors when running it face various issues including memory allocation problems and GPU/CPU offloading

This Reddit thread from r/ChatGPT discusses whether locally-run open-source AI models can match the capabilities of frontier models like ChatGPT. Leading open-source models like Llama 3.3 70B and Deep

This Reddit post shares the community discovery that multiple Z-Image ControlNet models can be chained together in workflows (such as ComfyUI) by connecting the conditioning outputs of successive Appl

This Reddit post examines the true total cost of running OpenClaw, an open-source AI agent framework, across different deployment models. While OpenClaw itself is free and open-source, hosting costs r

This Reddit thread from r/ChatGPT explores the community debate around whether AI-generated content will remain reliably detectable in the future, given the rapid advancement of large language models.

Follow-up to last week's post about streaming MoE experts from disk in a browser tab. That ran on hand-written engines for two models. This week the same disk tier sits under llama.cpp's own WebGPU ba

I built a desktop app harness that keeps local meeting notes and can use them to autocomplete my typing as well as complement my dictation with additional context via reading my screen or using the pr

I’ve wanted this for a long time: a Krea-2 model that gives you a magazine page in one shot. Flash-lit gravure sets, film grain, multi-photo layouts on white paper, big headlines, covers and back cove

I wanted to track grocery spending per item without sending my receipts to anyone, so I built an Android app around a small vision model that reads a photo of a receipt into JSON: store, date, total,

No more excuses for GPU-poor folks not to start LLMing! Full 27B-class reasoning in ternary transformer weights, for llama.cpp (CUDA, Metal, CPU) ~9.3x smaller than FP16 (ideal) | 98.2% of FP16 intell

DigUp is a free Mac app that runs Google DeepMind’s new EmbeddingGemma 2 locally over your own files. The model puts text, images, audio and video in one space, so you describe what you remember and l

Disclosure first: I'm one of the maintainers, this is my project. If you've pointed Open WebUI or a script at a local server, you know the failure modes: the server restarts and every conversation is

I've been optimizing long-running agents: rewriting their prompts, tools, skills and subagents, and keeping the changes that score better. I've been working on some version of this problem for over a