Search: “r-localllama”

At Bitwize, we've been building Logue, a native macOS app for AI meeting notes and writing, and we just open-sourced it (MIT). We're sharing it here because the whole point is that it runs 100% on-dev

I am seeing more and more videos as posts about how OpenAI is in complete financial ruin, Anthropic isn't much better. Their expenses go with the revenue they make etc etc. Meta made big investments i

Qwen3.6-27b is fantastic! It makes me wonder if there's a hard ceiling to smaller sized models. Do you guys think the ceiling of intelligence for smaller models will be constrained by factors like par

3 year lurker, now i finally got my server up and running. dont know which model to choose. llama.cpp or vllm, what makes more sense? mainly single user with maybe 2-3 more additional users in family,

Hi everyone, I have a system which I have been using for gaming, R7 5700X, 48GB DDR4, RTX3090 24GB. But I want to use it for Local AI to reduce my reliance on cloud AI providers (mainly usage limits -

Cuda and Vulkan Benchmark: TensorSharp vs. llama.cpp I would like to share my latest open source local Unsloth (GGUF) LLM inference engine and applications. It supports many models from Unsloth, like

If you run local agentic coding harnesses (Aider, Claude Code, etc.), prompt evaluation usually eats up most of your execution time. Every turn re-evaluates thousands of identical prefix tokens_system

I understand that the laguna model is either still buggy or potentially benchmaxxed. So I’d like to know for people who really tested, are DS flash or Hy3 really better in your usecase? submitted by /

Hi everyone! Over the past five months I've been working on DKV (DifferentialKV), an open-source project exploring KV-cache compression for long-context local LLM inference. The goal is to reduce KV-c

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

I’m building the ultimate AI tool vault, but every great collection has a few missing pieces. Note: I will react to every comment AI's currently installed: Qwen3.5-0.8B-UD-Q4_K_XL.gguf(classification)

I’ve spent the past month trying to find the point where an extremely small TTS model stops feeling like a size experiment and starts feeling genuinely useful. Today I’m releasing Inflect v2, with two

I am a long time iOS app developer. In the last year I have been using Cursor+Claude/others to assist with app development. I am concerned that the current low pricing will disappear eventually. I am

Just noticed this exists, 1M context MOE with 48B par seems just like what Ive been looking for - it runs pretty damn fast too compared to Qwen 3.6 35B. after some testing it seems capable of producin

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

After a long and grueling effort spearheaded by ngxson, llama.cpp now fully supports MCP for all protocols. Over-the-web HTTP servers were already supported in the client (since they don't require any

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

https://preview.redd.it/a24z80gr6afh1.png?width=1181&format=png&auto=webp&s=4a844ebe2319eb6230dbdc63c9caf492bed5ff47 So, this came up on: https://www.microsoft.com/en-us/corporate-responsibility/topic

I've spent the last year or so playing around with open source MLX and GGUF models on iPhone hardware. Given the limitations in memory, GPU/CPU/ANE, and in turn the context window I've been trying to

Hi Guys, I'm an old coder and DBA that has been in the field for almost 40 years. More and more the jobs I was doing for work are being taken over by AI and the need for my type of work is diminishing

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

https://preview.redd.it/wbq8ullnbafh1.png?width=1409&format=png&auto=webp&s=e6d2fe2b1c87c724bc64003c25f917dcee53260f I finally got round to tweaking this, with a bit of help from GLM5.2. The trick to

Since a lot more people are trying to build their own multi-GPU machines, I thought I should help to prevent a common mistake people make with building multi-GPU machines. Which is using an Intel cons

Please be honest. I would love to hear about guys really dedicated to local AI and who really reject subscriptions (especially to openai and anthropic). What do you use your model for? submitted by /u

audio.cpp again :) Release 0.4 is out. The headline this time is new high-quality TTS coverage plus GGUF becoming a first-class across the project. What’s new: Added Higgs Audio v3 TTS 4B, Fish Audio

https://preview.redd.it/b7ybs7nqx5fh1.png?width=3440&format=png&auto=webp&s=e6aaaa15cbe59debaae1ebb7fcd708167e86dc35 Hey r/LocalLLaMA ! We are back and we have something really amazing today. Our big

I’m not affiliated with this project, but I’ve been running it recently and I’m surprised it hasn’t received more attention here: https://github.com/fewtarius/CachyLLama CachyLLama is a fork of llama.

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

In a previous post (https://www.reddit.com/r/LocalLLaMA/comments/1utefpr/running_qwen3_30b_a3b_at_50_toks_on_rtx_5060_ti/) there seemed to be great demand for bringing in Qwen3.5 35B. Some Gated Delta

Introducing FLUX 3. One multi-modal model for Image, Video, Audio and Action-Prediction. Creations are truer to life in every kind of style. Blog Post : https://bfl.ai/blog/flux-3 submitted by /u/pmtt

If you want to get the most out of MTP. You have to run some tests / benchmarks to do so. Turning it on with defaults will get improvements, but for many models and card combinations, you are leaving

So I've taken some time to actually test laguna on a few of my own projects. I wanted to share as I feel most peoples comments at this point have just been about getting it running or saying it doesnt

From Anton Lozhkov on 𝕏: https://x.com/anton_lozhkov/status/2080254608639701222 Two ways in: stack-v3-train - near-deduplicated, quality-filtered, PII-redacted, contents inline. Point load_dataset at

Like, reading things like Anthropic 'donated' to some people with the condition of lobbying against Chinese LLMs.. it's that right? It feels nothing like freedom but at the same time it's said 'out lo

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

The Open Letter was initiated by Microsoft and published today: “Open Weights and American AI Leadership”. It argues against broad or premature restrictions on open-weight models and explicitly says p

Model quantization has become essential for efficient large language model deployment, yet existing approaches involve clear trade-offs: methods such as GPTQ and AWQ achieve practical compression but

I've been building a C99 inference engine from scratch (no Python, no BLAS, just gcc and make) that runs BitNet's ternary models on CPU. A few weeks ago I got obsessed with the matmul kernel - wrote a

https://huggingface.co/swiss-ai/Apertus-v1.5-70B https://huggingface.co/swiss-ai/Apertus-v1.5-8B Apertus 1.5 is a family of 8B and 70B parameter language models designed to advance the state of multil

Even if China was distilling from US models (assuming all accusations are true), nothing about it makes it illegal. It is like saying you distilled knowledge from your professor in colleges and now he

From my understanding, most current LLMs are trained on trillions and trillions of tokens of mostly AI-generated data. Are there any recent models that are trained purely (or as close as possible) on

mii-llm, an open source AI lab, released Zagreus-0.4B-por, a compact bilingual Portuguese–English language model pretrained entirely from scratch. The model has approximately 400 million parameters an

Just saw this on huggingface: https://huggingface.co/ProCreations/grug-27b The benchmarks claim that it's quite a bit better than qwen3.6 27B original and that they reduced the amount of necessary tok

As an AI community of LLM experts, are we really going to stay silent while US officials make absurd claims to push anti-consumer laws? Not only does the release timeline between Fable and K3 make hig

AI9Stars has released G9v3-3B an open weights language model designed to deliver strong reasoning capabilities within a lightweight 3 billion parameter size. It is released under the Apache 2.0 licens

At the moment MLX (and Llama.cpp for Macs) run 16bit activations everywhere. Despite this, the M5 generation silicon actually does support INT8 activations - it actually allows w4a8 d_type. It's just