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Which model, which harness? I have data for you.

I keep testing harness & model setups on real tasks: basic math, vision, computer use (reading emails, navigating stores) and coding. I created a benchmark and a leaderboard. You can see it here: http

5 Oct 2026

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Human DGX agent

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Y'all this is a sexy paper; context language models

DGX agent

Paper linky - Context Language Models The central idea of the paper is incredibly simple. Give a model the ability to edit its context on-the-go like a file has major benefits on task performance, con

model-releasesr-localllama

5 Oct 2026

A Minimal Interpretable Architecture for Zero-Shot Reconstruction of Dynamical Systems [R]

model-releasesr-machinelearning

In our #NeurIPS2026 paper “A Minimal Interpretable Architecture for Zero-Shot Reconstruction of Dynamical Systems (DS)” (preprint: https://arxiv.org/abs/2607.14937) we reduce a DS foundation model to

A Strata fork for IBM AC922 running Qwen3.8-FN UD-Q4_K_XL is doing up to 7,357 tk/s prefill and 113 tk/s decode

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

Built a quick, sub-15ms Rust CLI/TUI to pack repos into prompts without burning 40k tokens on lockfiles and junk

Whenever I feed codebases into local models (Qwen, DeepSeek R1) or API models, the biggest annoyance is prompt pollution: - Lockfiles (`Cargo.lock`, `package-lock.json`) burning 30,000+ tokens for zer

Can someone explain how JEV is different from a simple embeddings model?

How is JEV any different from using an embeddings model? I really will appreciate if someone can explain this to me - because I have yet to see the difference. I'll even give you my JEV server for fre

[Discussion] A 5KB pure x86-64 assembly engine for Gemma-2B (FP16, 4.6 tok/s on CPU)

Hi everyone, Sharing a personal project exploring the minimal bare-metal footprint required to run an autoregressive LLM. Instead of relying on large runtimes or compiler abstractions, I wrote an infe

For dual DGX spark users; GLM 5.3 flash got a 50%+ performance boost

For the last few months, I ran DeepSeek v4.0 flash (NVFP4). First 0731, then visionexp because it was a free improvement. I got around 65 tps decode and almost 2k prefill, and ran 4-5 agents in parall

From 1x3090 to 20 DGX Sparks: my house fuses were the first bottleneck

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

Applications

Here are some pictures of a robot costume wearing high-specularity edge-case mirror suit, a dataset (425 RAW/JPEGs) for benchmarking CV & depth-estimation algorithms against extreme mirror reflections [D]

applicationsr-machinelearning

Purpose-built to stress-test computer vision models, depth cameras, and spatial AI against severe specular glare and geometric reflections. This 425-asset production archive features a custom faceted

I Distilled an LLM into two 287M encoders (GLiNER + multiple choice) for document extraction, can't match teacher. did i do something wrong?

A while ago I asked here how to turn ~5 million court decisions into structured graphs without running an expensive LLM on every document thanks for the advice . I went with the 'small extractor + cla

I trained a 3.87B MoE (1.45B active) from scratch on only 86.5B tokens

First of all, thank you for reading. I trained a small MoE model completely from scratch (no external base weights) and wanted to share the results + a couple of lessons. Apex-2 - Architecture: Decode

Is all the work that's being put into Qwen3.8 Flash Next going to set us up for a very quick uplift to Qwen4?

Given the commentary on the Q3.8FN release page here https://qwen.ai/blog?id=qwen3.8-flash-next I assume/hope that all the work that's going on to optimise the hell out of running it will be useful wh

Is Strix Halo (GMKtec EVO-X2, etc.) the closest thing we have to a 'dream' local LLM box?

I've been looking at the <32B model space and keep coming back to an interesting question. A few years ago, projects like Hummingbird+ suggested that cheap custom accelerators (FPGA-based) might becom

Is there any way to improve creative writing for Local Models (Qwen)?

I wanted to know if theres anything that can improve creative writing for our Local Models? I specificly am asking for qwen models as they are way better when it comes to researching and writing html

Least sycophantic modern open LLM?

So Kimi K2 is outdated, and so is GPT OSS 120b. Which of the modern open weights models can boast the least sycophancy? I need this both for creative/research assistant usage (sycophancy led me down b

LFM2.5 2.6b vs MiniCPM5 2b

I tried both these models on a few small agentic tasks with tools (i.e. 'What's the weather like today?', etc.). They're both pretty solid at using web search to find answers despite being small model

LLM Inference Dashboard

Working on a resource dashboard, rich logs, lightweight 64mb cap, all local, scales on network API endpoints via collector, supports multiple engines (llama, strata, custom cuda engines, unsloth, LMS)

Need maybe say 'Use llama.cpp'

So I tried that miracle engine everyone is talking about. Asked the IQ3_S model to express its opinion on a post from this sub to measure the tps on a long-ish generation: Can you help with the follow

Nonobench: an open benchmark of 49 LLMs on nonogram puzzles, public and open source [P]

model-releasesr-machinelearning

Nonobench measures how well LLMs solve nonograms (picross). Each model gets the row and column clues once and returns the full grid. No tools, one attempt per puzzle. Method: - Standard mode: 30 puzzl

Poor People Vulkan GPUs list

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

poorman inference engine for 16GB GPU and 35B moe Qwen 3.6for coding

I forked llama.cpp's server into AgrillaMoE, a dedicated build for Qwen3.6-35B-A3B (~A4B) with Unsloth quants. On a (vant.ai) rented V100 16GB with the 2-bit UD-Q2_K_XL quant it generates at ~57-60 to

Qwen3.5 arch implementation in FPGA fabric for 9B/27B INT4 models on relatively cheap eBay mining hardware

I've been wanting to test out LLM inference on FPGAs for a while now, but didn't have a big reason too since there were no frontier class models at 9B-27B scale (3.6 27B was great still but it didn't

The curse of 64GB system RAM

Not a bot. Not a Strata shill. Just sharing my experience. So, I have an R9700 in my machine, plus an RTX 5060 Ti, and 64GB DDR5 system RAM. Overall, not a bad setup. Anyway, I mainly run a daily driv

Update #4: Post training yandex/AliceAI-80B-A3B [instruct!] from scratch

Last update for those following: https://www.reddit.com/r/LocalLLaMA/comments/1wvyc3e/update_3_post_training_yandexaliceai80ba3b/ Project in a sentence: An instruct finetune of ALiceAI-80B-A3B-Base ca

Upgrading from 1xR9700 to 2xR9700. Thoughts on build before buying?

Currently have a R9700 build with 64GB RAM. Want to get a second one for both speed and the ability to run Qwen3.8-Flash-Next at Q4/higher quants of 3.8 27B. Looking for thoughts or any improvements b

Research

Working with an AI Company That Does Things You Disagree With [D]

researchr-machinelearning

I'm a PhD student in machine learning in the EU and was looking for internships at exciting companies. I shortlisted few and applied by reaching out to people and now reading project descriptions sent

Applications

A Meta-Prompt for YuE2

applicationsr-stablediffusion

I've come up with a meta-prompt for generating YuE2 prompts that seems to work pretty well. Copy-paste into an LLM (it should have internet searching capabilities, I mostly just use ChatGPT). Just to

ai slop game based on batlle video in real time with only open model

Check out Chimera Arena (https://chimeraarena.com/static/showcase/index.html?lang=en)! Here’s my slightly scrappy AI-generated teaser for Chimera Arena, my card game combining AI-generated video battl

Hardware

Anyone else finding it harder to justify a new GPU upgrade lately?

I have been running the same midrange card for a couple of years now, and every model release sends me back to the price sheets. The performance gains are real but they keep landing next to price tags

hardwarer-localllama

Anyone sitting on a lot of slow system memory and a modest GPU.. try Strata + Qwen3.8 Next.

IQ3_XXS weights are just under 80GB and my slowww DDR4+7900XTX is stabilizing around 45-70/s (sometimes higher while coding depending on mtp). Looking online I'm seeing similar results for users with

Anyone using a local AI meeting notes setup instead of Fathom?

Meeting notes are one of the last parts of my workflow that still depend heavily on cloud tools. I've used Fathom and lately Bluedot. Bluedot works well for me because there's no meeting bot and I get

Anyworld, a self-hosted multiplayer text RPG where a local LLM is the Dungeon Master

Hey everyone, I’ve been working on a game called Anyworld. It’s a browser-based multiplayer (single player also supported) text adventure inspired by the early days of AI Dungeon, especially its brows

Agents

Arex-2 vs swift vs qwen3.8 27b

Hi, Im gonna go all in on this, best finetune iv got my hands on for agentic coding, period. Test it yourself, im not gonna give you any benchmarks or evaluations, use your own tests and pracices, giv

agentsr-localllama

Come let your LLMs play World of Warcraft

I hosted my own world of warcraft private server then built a client that you can play in the browser on PC or mobile at https://jankcraft.xyz/ for free. Afterwards, I created a custom MCP and agent h

Dual Radeon MI50 benchmarks

Still don't have a good cooling solution, but here are few benchmarks. I lowered the power limit (TDP) to 145 watts each. I changed the firmware on one MI50 to activate the miniDP port. Did have to us

Industry

How many of you use ChatGPT as therapy?

NGL, I do, but I’ve my reasons…. I do discern it’s answers but I’ve been so nomadic I’ve barely any friends my family of two aged parents won’t understand the concept of mental health and my diagnosis

industryr-chatgpt

I built a code knowledge graph tool that's actually MIT licensed (fully local, no cloud)

So this is maybe a niche problem, but at my job I work on a huge Python codebase and every time I change some shared function I'm basically playing roulette. grep tells who mentions it in the code bas

I built Ninfer 4080 for 16GB class GPUs

Hi everyone, TL/DR I created NInfer 4080 to run ISTA-DASLab-Qwen-3.8-27B-GSQ at 100k context on an RTX 4080 16GB GPU using way more of the hardware capabilities (max overall: 2720 tok/s prefill, 262 t

I tried building a small RAG search node for Qwen3.8 27B using a fake AliExpress Mini PC... and Intel sent me back to 2018.

I love Qwen3.8 27B so much that I decided to show my gratitude to the Alibaba ecosystem by building a dedicated RAG/search node using a cheap Mini PC from AliExpress. Turns out, my ecosystem loyalty g

Jev: Not Frontier, But Still Worth Your Attention [R]

model-releasesr-machinelearning

'TypeSafe AI sells Jev as a frontier-class reasoner that cannot hallucinate, built by the co-inventor of ChatGPT - fast, and almost free. We ran it live on 16,379 benchmark requests, measured its late

Krea2 Turbo Distill 2 step LoRA - new checkpoint released (chk41320)

Krea 2 Turbo — 2-Step Distillation LoRA (work in progress) Previous posts/releases - here, here and here. 🧪 A fast-preview adapter, from a project still in training. When the subject is close and fill

LiquidAI/LFM2.5-Encoder 250M/350M

LFM2.5-Encoder-350M is a multilingual bidirectional encoder built on the LFM2 architecture — a larger encoder for maximum downstream quality. It is a masked language model with full bidirectional atte

mlsubgen — subtitles in 45 languages for your videos, entirely on your own machine

Full disclaimer: I've leaned heavily on Fable to develop this, but I've tested it thoroughly on my own library for a couple of months before putting it on GitHub. I live in Thailand, and it started as

PotionUI is a free, open-source studio for generating images, video, music, and 3D on your own hardware with diffusion models - version 0.0.14

Reupload: I'm adding this again, since previous post had a totally stupid title which made people assume this app is some kind of cloud/proprietary models UI - this is totally not the case here. In ve

PSA: Krea 2 variance is easy in ComfyUI (no LoRA-s or custom nodes needed)

There are quite often posts here complaining that Krea 2 is too predictable / different seeds give almost the same output / you need to type in extremely long prompts to get good images / there is no

Qwen Image 2.1 fix v2.0 (updated due to feedback), plus a new sampler

This is actually two models: Qwen Image 2.1 Fix v2.0 and Qwen Image 2.1 Fix Opinionated v1.0. The former surgically targets Qwen's weird noise and messy details with almost no effect on composition, a

Qwen3.8-Flash-Next 177B running at 11–15 tok/s on a single RTX 5070 12GB + 32GB RAM DDR4

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