Search: “papers”

I am one of the authors of FLEET - an algorithm that enhances Best-of-N generation by attributing external rewards to particular tokens and then uses MCTS to adjust logits during the next run. I find

Hey guys, Last time I tested Qwen3.8-Flash-Next on its own. This time I put three Qwen3.8 checkpoints through the same 10 tests on the same RTX PRO 6000: RadixArk/Qwen3.8-27B-NVFP4 (dense) orcarouter/

Hi! This is a new benchmark that I created together with other researchers at Meta, Stanford, Harvard, UW. Most benchmarks these days seem to test models to just fix a bug that I as a user already enc

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

Hybrid search, reranking, query decomposition, and query expansion are often treated as must-haves for good RAG. We wanted to see how much each actually helped, so we tested them. Same model, same emb

I just bought the GPUs after deliberating and debating for over two years. With costs not coming down any time soon and me just wanting to get this massive todo-box ticked, I decided to just YOLO it;

We did a study: does post training actually make LLMs funnier? We used open models that publish every stage of post training, so we could compare a base model with the future models it became: Tulu 3

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

I've been experimenting with ways to run MoE models that don't fit comfortably in RAM, and I ended up making Overspill, a disk tier for FreeToken. The basic idea came from looking at how Colibri handl

Distributed Training and Inference both involves having a fundamental understanding of how distributed systems work in general Distributed Parallelism Tensor Parallelism Pipeline Parallelism Model Par

We hosted Kev 4B (Jared Palmer's Apache-2.0 fine-tune of Qwen3.5-4B) and ran it side by side with Jev on the same endpoint to see how it compares. We built a fresh set of 362 items published after bot

Since my last post, I've been thinking about different options for dynamic performance degradation, trying to squeeze as much high-quality inference out of my GPU as I can. Over the weekend I read thi

Here's my *first* implementation of KVA projectors on QFN (just the uncensored model for now) the highlights are basically as follows for using the projectors at each different layer: Starting at laye

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

Someone recommended that I try the ByteShape Qwen 3.8 27B IQ3-XXS GGUF after seeing my previous testing of the GSQ quant. So I did. And the result was… surprisingly bad. For context, I'm running: RTX

What if you don’t need a new model to get Jev-style decisions? I built hearim(헤아림. hea-a-rim. not Here, I am.. lol), an open-source gateway that turns ordinary local or hosted LLMs into a Jev-compatib

Typesafe's new model, Jev is all over the internet, this sub etc as a new classifier model. Then an AI dev posted here how they'd done something very similar, and made a new model, Laya. https://www.r

After seeing u/Nandakishor_ml’s post introducing Laya, I wanted to see how fast it could run in a standalone C++ implementation. Credit to u/Nandakishor_ml for the architecture, training and open-sour

TypeSafe announced Jev on Tuesday: you give it data plus typed questions (yes/no, pick-one, 0–N scale) and it returns a probability for every option, crazy fast. I signed up and then refreshed my inbo

I'm trying to find out whether back-and-forth between two different LLMs improves task success beyond strong alternatives under a controlled resource budget — and I'd rather hear that it's already set

GoBench evaluates LLMs on 9x9 Go games against a ladder of KataGo opponents, from random to superhuman. It measures general reasoning ability, strongly correlates with ARC-AGI 2 (r=0.83 correlation),

GitHub: https://github.com/pfekin/LARA I've been working on LARA (Lightweight Additive Residual Adaptation), a research project on making post-training modular for frozen language models. I've also de

It's late at night in the lab, I've been working on a basic script for a virology project, and holy hell the safeguards have been pissing me off. Mirroring detectEVE data over rsync to my laptop by ma

I have a full model, it's ready to train. It's ~9b parameters. 9.4b to be more exact. That includes a 1/2/3 Engram table, Moonshot's AttnRes modeling, and RoPE / NoPE layering at 3:1 as more or less v

https://github.com/Sayitobar/chat_llm_cookbook This is my personal project that took several months. I wanted to see whether a 2B small local model could simulate a six-person group chat trained & ran

Hey everyone, If you run local models via Ollama in production or personal projects, you've probably run into the hallucination problem: how do you know when a model is hallucinating without burning e

Original Source from DeepSeek WeChat Official Account: https://mp.weixin.qq.com/s/qg0NU3NNUbp1co2PdkAPAg Today we're officially releasing the DeepSeek V4.1 Flash model. It is the smallest model in our

Surveillance plagiarism - Hosted AI company pumps their stock price by training upon researchers' AI sessions, so that their internal model can solve problems with seemingly less human guidance, but r

hope that helps my script uses the GPUs most discussed on the LocalLLaMA, LowEndLocalAI, and LocalLLM subs. At first, I tried to include more, but it became unreadable. Prices were collected by ChatGP

I’m currently running llama.cpp on two RTX 2060 12GB cards, so 24GB total VRAM. With Qwen3.8 27B IQ4_XS at 131k context I’m getting around 45 tok/s, which is actually pretty good for this setup. I fou

I was reading up on the recent controversy around Tristan Buckmaster, Levent Alpöge, OpenAI, and the Navier–Stokes result, and it got me thinking about something broader than this particular dispute.

Our research team has been exploring an alternative approach to achieving interactivity and better responsiveness with LLM systems. One of the team members wrote up a post about it: https://research.y

Back to reading about LLMs as agents on your phone doing GUI tasks! This time I read about MobileWorld: Benchmarking Autonomous Mobile Agents in Agent-User Interactive and MCP-Augmented Environments a

I used an LLM to iteratively evolve an optimization algorithm rather than solve the packing directly. Starting from a simple seed solver, the LLM proposes algorithmic changes guided by a scoreboard of

Hiya, NInfer is amazng for Qwen, but lacking for real-world-use. As adoption of issues/pr's was not really what I needed, I created a fork and hit it for this week with 3 concurrent claude code sessio

I was running into a lot of posts that praised both the Fixed template and the Sharp template in comparison to the stock one, so I put them to the test. It's not as extensive as it should be for a pap

Two weeks, one rule, and hundreds of entries from nearly 50 countries. Here's who took the four titles, and a look at everyone who made the final ten! Entries opened August 20 and closed September 1.

I keep seeing demos of AI agents building scenes in Blender through BlenderMCP, so I tried it myself. I ran both models locally for this and picked the GLM 5.3 family(Q4 quant) because videos of it do

Hello! I was looking into quantizing models and i saw how Hy4 was shrunk from 1.5 TB to 200GB with high retention in benchmarks (98% i think). I was wondering if: a) it would be worth it to attempt th

Hey guys I have been working on a open source LLM development repo. Anyone can train any amount of parameter against any arch (GQA, MLA, Dense...) When I tried to implement MLA I read the technical re

Proof is in the method honestly. Closed model labs need to constantly reinvent the wheel to keep lead. Open source has a bunch of independent labs practically working somewhat together. Eventually whe

Ever since Qwen 3.8 Flash Next dropped, there's a misconception going around that N-gram tables will let people run 1T+ parameter models on a single server with 980B parameters offloaded to SSD. I'm h

We're releasing a fully quantized NVFP4 version of Qwen3.8-27B. The checkpoint was trained using quantization-aware distillation (QAD) with QUASAR, our new QAT algorithm. We used the original BF16 mod

So I've been going down a rabbit hole trying to run local LLMs without dropping 800+ on a Mac or GPU. RAM prices are insane right now and I realized that used phones have decent unified memory for dir

Megathread for discussing the release of GLM-5.3-Flash. Quants Fine-Tunes & Abliterations Chat Templates Inference Server Support & Configuration Experiences, Benchmarks & Model Comparisons We'll try