Search: “evaluation”

A small update to Sir Shortoken. Sir Shortoken already had Quick, Balanced, Deep, Bullets, and Aggressive Bullets. I wanted something between Bullets and normal prose. So I added LELP-S+ (Less English

TL;DR: On a Qwen3.6-35B-A3B Q6 setup sized for 64K context on a 24GB RTX 3090, spilling eight MoE expert layers to CPU freed enough VRAM to increase -b from 512 to 1024 and -ub from 128 to 512. Prompt

Seen a ton of posts today about the DeepSeek API price hike. Half the feed is doom-posting, the other half is explaining basic GPU economics. Honestly, I get the cost side. Sub-cent tokens were never

Hello everyone Yesterday I gave a report on Gemini bugs and the techniques I learned on Gemini so far with the Engineering Prompt and interestingly today I got a very interesting and controversial ans

I have been working on this tool for months and there are a lot of new functionalities and tests that are going to be released in the next few weeks! The goal of the tool is to allow community members

Hey y'all. I'll be concise. TL;DR: DS V4-Flash-0731 @ UD-IQ2_M running fully in VRAM on 3xMI50s (90.9 GB model, 96 GB VRAM). Actual speed on llama-server is: - Text Generation: ~15-16 tokens/second st

TL;DR: I spent 9 days developing a new quantization method for MLX models and measured 18 variants against each other on a single M5 Max MacBook Pro (128 GB). The result is the best-measuring MLX quan

https://preview.redd.it/1a39x4zivqgh1.png?width=1550&format=png&auto=webp&s=de591c039cc18782a6b5d8e402fdc1594be05132 start C:llmllamam5uildinllama-server.exe --model 'H:UD-Q3_K_XLDeepSeek-V4-Flash-073

TLDR: There is no one prompting trick that will result in Krea 2 Turbo giving you exactly the style you want and across the whole image. Instead, if you are trying to achieve styles without the use of

'Anthropic’s AI Claude escaped testing environment and hacked organizations' 'Company says it discovered unauthorized access during ‘proactive review’ after rival OpenAI revealed rogue agent… its AI C

It's an encoder-only transformer that consumes past(blood glucose + carbs + insulin) and future(carbs + insulin) and predicts future blood glucose for the next 2 hours. Announced meals and boluses/bas

Okay, hear me out. Why is it that every time a new model comes out, all the tests I see are 'make a car game,' 'make a website,' or something equally generic, usually from a prompt that's barely a lin

We developed a leaderboard ranking frontier model security. There's no shortage of model capability rankings, but we didn't find anything comparable for model security. Yet security is becoming increa

Hey everyone, ​I recently finished pre-training BetterGPT-150M, a small, lightweight causal language model with ~152 million parameters.Trained on 15B tokens. Dataset & Training: Trained across stable

Hey fellow llamas. we have something new for Strix Halo owners we thought would be useful to share. i'll keep it short: We were able to fit DeepSeek V4 Flash plus its speculative draft on a single Ryz

TL;DR: Most RL post-training algorithms optimize the current batch and move on. But after an update, did the new policy actually become better? We introduce Policy Improvement Reinforcement Learning (

You patch security holes by intentionally finding them. If the models refuse to do it, how can companies protect themselves against rogue AIs, whether they are Chinese or OpenAI/Anthropic themselves?

Test Prompts: 1.1. Algorithm & Logic (10 pts): 'Write a function in Python that finds the contiguous subarray with the largest sum (Kadane's algorithm). Include time and space complexity annotations.'

There is a lot of buzz around running 100B parameter models on cheap local hardware using ternary (1.58-bit) quantization like Microsoft's BitNet architecture. The theoretical hardware shortcuts are i

I'm a software engineer who mainly builds softwaes/applications, and I'm starting to work on machine learning projects. Since ML workloads often require GPUs, I know services like Google Colab and Kag

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

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

In the past few months I’ve experimenting heavily and tortured my old 2016 Desktop PC to run the biggest Local LLM I can fit. I documented the whole process and research and I’ve published a repositor

Fara1.5-27B is a multimodal computer use agent (CUA) for web browsers, from Microsoft Research AI Frontiers. It observes the browser through screenshots and acts on the user's behalf by emitting struc

Hi everyone, We've open-sourced Tri-Net v2, the official implementation accompanying our recently published Scientific Reports (Nature Portfolio) paper: 'Tri-Net: Unified Deep Learning for Skin Lesion

I worked on this project (https://github.com/workofart/harness-training) for the past few months to reframe 'Agent-driven Self-improving Harness' to 'Harness Training'. The idea is simple, the harness

LLMs handle speech well once you run speech-to-text. They don't hear the rest: a bird outside, a glass breaking two rooms away, a smoke alarm two floors down. I've been working on an experimental open

A developer created a Windows GUI tool for managing and benchmarking different llama.cpp builds, addressing the needs of AMD GPU users who work with multiple compute backends like Vulkan, ROCm, and HI

User seeks guidance on PDF processing methods for local AI agents built with Ollama, comparing approaches like PDFPlumber extraction, vector database RAG systems, and alternative techniques for accura

Research demonstrates that LLM-based agents can generate functionally correct patches that pass all tests while still containing security vulnerabilities, challenging the assumption that test-passing

A comprehensive comparison study of 62 different samplers and 16 schedulers used in WAN 2.1 image generation, with systematic quality ratings to help users understand which combinations produce the be

Physics-informed neural networks (PINNs) are machine learning models that incorporate physical laws and equations as constraints during training to solve differential equations. This post likely discu

NVIDIA's Pixel Diffusion Decoder (PiD) is an open-source decoder that replaces VAE decoders in image generation pipelines without retraining, producing sharper fine details and textures through a lear

CANTANTE addresses the challenge of optimizing LLM-based multi-agent systems where system-level performance scores are available but individual agent parameters cannot be directly optimized. The frame

Continual Harness proposes an approach to online adaptation for foundation agents that moves beyond traditional gradient-based retraining by introducing a dual-agent architecture (Teacher/Student) wit

A user posted an actual Claude Monet Water Lilies painting while claiming it was AI-generated and asking critics to explain its inferiority to real Monet work. The detailed critiques were specific and

claudely is a tool that enables users to run Claude Code against local LLM providers such as LM Studio, Ollama, or llama.cpp while preserving their existing Claude configuration. The tool allows devel

Sentinel is a local-first AI coding desktop application built with Rust and Tauri that automatically routes coding tasks to appropriate models based on task complexity. Instead of swapping between mul

This post discusses a user's experience using ChatGPT to generate images of a fictional galaxy for their sci-fi serial based on custom lore they provided, comparing the results across multiple generat

I'd need to search for this specific Reddit discussion to provide an accurate summary of what was actually discussed. Let me retrieve that information. This Reddit post discusses using AI vision model

The Klein 9B Distilled is a distilled image generation model enabling sub-second image generation with text-to-image and image-to-image editing capabilities in a single unified model, designed for rea

This discussion likely covers model selection guidance for users creating storytelling visuals with Stable Diffusion, addressing factors like stylistic output and consistency . The r/StableDiffusion c

Z-Image Turbo is a text-to-image model from Alibaba's Tongyi-MAI team that combines the prompt adherence of Flux.1 with the versatility of Stable Diffusion XL . It is a distilled version optimized for

A user created a workflow to test multiple Stable Diffusion schedulers and samplers simultaneously, addressing common questions about which are optimal . The post likely demonstrates a comparative tes

Kimi K2.6 is an open-source model featuring advanced coding, long-horizon execution, and agent swarm capabilities that is now available via Ollama Cloud . The model excels in coding and agentic tools

A benchmarking post testing 63 different samplers combined with the linear_quadratic noise scheduler for LTX-2.3 (Lightricks' audio-video generation model) . The linear_quadratic scheduler was origina