Search: “context”

There is always at least 1+GB of VRAM not usable not matter how I set the --tensor-split (-ts) param. I tiny shift toward one side will move the weight significantly to the other side. 😵‍💫 Adjusting c

I’ve spent the last couple of days with Opus 5.5 working on a fork of Inco’s excellent and already blazingly fast Splash engine to optimise it for M5 Max chips. Taking liberties and referring to it as

Disclosure: I’m one of the authors of VeriLoop E2, a 27B model post-trained from Qwen3.8-27B. The weights are Apache-2.0; the harness we evaluate it in is not open source (details at the bottom). This

AI grad student here. With all the recent interest in Jev, I thought I would share something I built la few months ago that brings ML models and LLMs together in a different way than Jev does for diff

For instance whenever a model comes out, what’s the best engine to run it, the best harness and absolute minimum you need to get same or near same re results that the benchmark of that model claims. A

Sometimes it’s easy to forget that this sub and others like it are probably the extreme minority when it comes to this hobby. Most people, I would think, don’t use or can’t afford one good GPU, let al

I’ve been playing around with the email connectors in ChatGPT and realised you can set up a surprisingly neat little workflow. My AI has its own Outlook inbox connected through the Outlook connector,

I posted an updated GPT-OSS template a couple of months ago, which was based on Unsloth's version. It turns out that both Unsloth's version (and, thus, mine) contain a very serious bug that can degrad

Hello r/localllama once again, it's me your kobold concedo Been a few months since I last posted here, and today I have something new I'd like to share. Specifically, KoboldCpp now ships with a built-

I've been playing around with Ling 3.0 Tiny, which is an 8 billion parameter model (MoE, 1B active). And I've had a lot of poignant thoughts as a result. Just for fun, I got it running with llama.cpp

For the last few days, I've been using two computers to run multiple agents. My 4x3090 machine is running Qwen 3.8 27B with parallel=2, so I can run two agents at the same time. My pi instances are ru

I know there is nothing new with what I am saying but I recently started with hermes agent (it’s been a while I wanted to but did not have the time). Qwen3.8fn 6bpw exl3 (from turboderp) on a 6x3090 (

TL;DR - Swift Flash is a killer model that massively reduces excess reasoning. Try it out! If you haven't seen from my previous comparison posts, I'm a huge fan of the Swift Qwen3.8 models. I've been

Personal note first, being straight with you: I'm lazy tonight and used AI to write the following post: The workflow, the conversion work, and the mistakes that taught me the stuff below are mine, and

I am creating a local AI agent called 'Ontelic' for Windows. Ontelic returns to Ollama and also manipulates the actual Chrome. This is not for promotion but to share what we've learned. I'll give GitH

https://huggingface.co/bartowski/LensVLM-9B-GGUF LensVLM-9B LensVLM is a 9B Vision Language Model (VLM) that scans compressed images of text, then selectively expands only the relevant pages to their

Hey everyone! I've been experimenting with Qwen Image 2.1 Prompt Enhancer (PE) lately and noticed an interesting detail in Qwen's official system prompts. The PE models output structured JSON containi

Update from : https://old.reddit.com/r/LocalLLaMA/comments/1wis23s/update_small_model_engram/ It's been about a week so I'm back. People were asking me about the model. People wanted code, or models,

I have been using open-webui and open-terminal. Open-terminal is installed in a VM and gives the agent a ton of control of it's own system that I keep away from my normal network. I find this gives th

Got QFN up and running on our Strix box this past weekend and have been running on it for a few days now. Big thank you/shout out to the Halogen team, it's running fantastic on the Strix, this is clea

I've been comparing and working on Gemma 4, Phi-4-Mini, and Qwen3-4B for local LLM use on an 8 GB Raspberry Pi 5. The results were indeed close, but each model has a different strength: Gemma 4 E2B: a

Now that OpenAI has officially paused new sign-ups and upgrades for the ChatGPT Pro 200 (Pro 20X) plan, I’m looking for a solid alternative for enterprise-level development. For those unfamiliar: Code

Recently, the new DeepSeek-V4.1-Flash architecture showed how a causal encoder-decoder can work, but it was trained from scratch. Model Grafting does it to an existing model: cut at some depth, let th

Hi all! After all the jev hype I wanted to try by myself and got qwen3.8 27b to mix-and-match open implementations on top of ninfer, and to be honest I'm quite impressed with the results, latency is n

I want to try using AI to find possibly overlooked interventions for irritable bowel syndrome (IBS) and create a cocktail of interventions that AI thinks would give the highest expected benefit, attac

Hey everyone, I wanted to share a project I’ve been working on called Jayce. The whole thing started because I was watching a toddler named learn the names of stuff He didn't need to completely rewire

Hey everyone, A few classmates and I got tired of the usual browser AI workflow: copying text from a documentation page, opening a separate tab, pasting it into a chatbot, and switching back. We also

been working on this thing called OpenComms for a bit. basically i keep multiple coding agents open at once, usually stuff like a lead, builder, reviewer etc, and i got sick of copying messages betwee

I'm one of the maintainers of SurfSense, so this is self-promotion. I'm posting here because the model-picking part is what I think this sub will have opinions on, and I want real feedback more than u

Please remember that Delete Chat does NOT mean “forget what was in the chat.” I am tentatively flairing this as 'news' because I genuinely don't think many people realise that this is how ChatGPT 'mem

I shipped something I've been building for the last few weeks : phantom-kv , a refusal-removal system for large language models that doesn't touch a single weight. Instead of editing the model, it loa

OpenAI’s decision to retire custom GPTs appears to rest on the assumption that Plugins, Skills, Projects, Apps, and Workspace Agents collectively replace their functionality. For many Small and Medium

Hey everyone, After wrestling with hardware and engine issues for days, I finally got Qwen 3.8 Next running properly on my multi-GPU rig. Thought I’d share the setup journey, benchmarks, and thermal r

I gave Jev, Laya, a finetuned ModernCE-base-nli and a finetuned Qwen3.5-4B the controls to Doom. Thanks to TypeSafe AI for Jev access. The video lines up the starts of four separate games with the sam

Hello! So, yesterday i tried out Gemma 4 26B A4B QAT Q4_K_XL from here with Q4_0 MTP model in Pi agent. Suddenly, it became the first model to actually pass my simple test with HTTP server in C++, whi

So my brother and I both use LLMs for coding. I've started using a local GLM 5.3 Flash instance - q4 qat. My brother uses GPT-6-Astra as his daily driver. He has mentioned repeatedly to me that his ap

TL;DR: Local agent loop, ~21 days, one RTX 3090. Task was pretty much 'build a CUDA inference engine for optimized for yourself on this GPU arch.' Got working kernels and benches, not a win over llama

Just find it interesting, since if Taalas tried to get into the consumer market, it could be interesting. Kind of like how we have game discs on CDs. Of course, a Qwen3.8-27B chip is stuck on 3.8-27B,

Screenshot of heavy load. I did offload vision to a spare 2060 instead of local ram. The control panel was generated with qwen3.8-27b davidau q4k_m max mtp. Made the panel from scratch over a week, ba

Top 3 papers on HF Daily Paper are all unusually delightful and interesting reads for anyone on the leading edge of local LLMs, agent harness optimization, etc, felt like sharing. DeepSeek-V4.1-Flash:

https://preview.redd.it/j13iin0jsfqh1.png?width=1129&format=png&auto=webp&s=3efdd2ad5c10de908aed1a673a6c7e6440177c09 https://preview.redd.it/k3fsrdspzfqh1.png?width=391&format=png&auto=webp&s=1c817687

Okay, this one seems probably really odd (or maybe not), but most harnesses operate within token spaces. That is, every tool output, even batching of tool outputs, go back up into inference calls. Lea

I was somewhat disappointed with the performance of Qwen 3.8 Flash Next on my single RTX 5090 using llama.cpp. One issue is that llama.cpp still has no Expert Caching implemented for MoE models. There

bonsai claim 98.2% intelligent retained, but their own documents show Ternary Bonsai 2 27B reaches 52.8 and 60.8, respectively, compared with 69.7 and 80.6 for Qwen3.5-27B, retaining roughly three qua

So I know that Ollama is built on top of llama.cpp, I decided to run a model on both and applied settings on llama.cpp like flash attention and q8/q4 kv cache. On Ollama (using the Python package) I w

Note not my work, but something i found and wanted to share so hopefully more people can push this along even further. https://github.com/nasone32/llama.cpp-RDNA3-7900xtx-opt I basically run 2 x 7900