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OmniVBench: A Benchmark and Large-Scale Dataset for Omni Reference-to-Video Generation

To address the limitations of existing evaluation protocols in reference-to-video (R2V) generation, researchers have introduced OmniVBench and the Omni-R2V Dataset. Current benchmarks often fail to assess whether models …

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APort Vault: Benchmarking AI Agent Payment Authorization with the Open Agent Passport

The APort Vault benchmark evaluates payment authorization security in tool-using AI agents by replaying 4,371 human-authored attacks against a live payment agent. The study utilized 14 different models from eight labs, c…

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Refinement Is Inherently Editable: Training-Free Prompt-to-Prompt Image Editing with Generative Refinement Network

Researchers have introduced RefineEdit, a training-free, prompt-to-prompt image editing framework that leverages the inherent editability of Generative Refinement Networks (GRN). Unlike traditional diffusion-based editor…

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CUDA: enable sparse fa for qwen4 by am17an · Pull Request #28770 · ggml-org/llama.cpp

A new pull request (#28770) for ggml-org/llama.cpp introduces CUDA‑enabled sparse flash attention for the Qwen4 model, aiming to improve inference speed. The change was highlighted by u/jacek2023 on the r/LocalLLaMA subr…

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I tested 9 LLMs on the exact same web-dev prompt for ~8 hours — RTX 3060 12GB results (Rate the best!)

The author tested nine local LLMs using an identical web‑development prompt on an RTX 3060 12GB GPU with 16 GB RAM running CachyOS via llama.cpp, spending roughly eight hours on the benchmark. The goal was to identify wh…

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Abliterated Qwen 3.8 flash can do anything

The user deployed an abliterated Qwen 3.8 Flash model on a Strix Halo machine, enhancing speed and token prefill. By employing a Fable‑based trick to abliterate the model, they achieved zero refusal and cracked a patron‑…

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focus-llama: a llama.cpp fork implementing Declarative Attention (arXiv:2609.02737)

Focus‑llama is a fork of llama.cpp that implements Declarative Attention, allowing the model to signal which context chunks it should attend to via special tags like <focus magic_chunks="N">. The engine reacts to t…

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we made a 27b model for creative writing. performs as good as claude fable 5, at a 40x cheaper price, open weights.

A Swiss and South African lab released hemmingway-1, a 27b open-weights model optimized for creative writing, roleplay, and dialogue, matching Claude fable 5's performance at 40x lower cost. It benchmarks at 1330 on eq-b…

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Qwen-Image-2.1: Compact, efficient, and unified image creation

Qwen-Image-2.1 presents a compact and efficient unified model for image creation. It aims to streamline generation processes while maintaining performance.

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Please stop with the FP4 inference engines for the love of god

The author complains that many new FP4‑optimized inference engines are advertised as fast but only work with NVFP4/MXFP4 formats, often resulting in hallucinated outputs. They argue that these niche solutions offer minim…

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Finally got Qwen 3.8 Next running on my v100 6gpu setup (TP2 PP3)

The author reports finally getting Qwen 3.8 Next to run on a six‑GPU V100 configuration after days of troubleshooting hardware and engine issues. They shared the setup journey, benchmark numbers, and thermal test results…

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Anybody tried NVIDIA PAIR

A Reddit user in r/LocalLLM asked whether anyone has tried NVIDIA PAIR, a tool for automatically routing requests to idle systems. They are seeking real‑world insights into how it performs in practice.

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