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Zyphra released ZYFA, open-source FP8 and BF16 prefill attention kernels for AMD Instinct MI355X. On real model activations, its FP8 kernels run 1.16-1.76x faster than AMD’s AITER, with 62-78% lower error at head dimension 128. The post Zyphra ZYFA: FP8 FlashAttention for AMD MI355X, Up to 1.76x Faster appeared first on MarkTechPost.
Data Mining & Modeling
Opera has introduced a new web standard called WebAI, designed to allow users to run AI models directly in their browsers without relying on cloud services. This standard is compatible with multiple models; Opera demonstrated it using Google’s open-source Gemma model and also supports Apple’s on-device foundation models. By not being tied to any specific model and targeting open-weight AI systems, WebAI represents a continuation of Opera’s earlier efforts to enable large language models to run locally within the browser. Currently, WebAI is available as a preview feature in Opera One, Opera’s flagship browser, though users must manually enable it.
Baidu has released Unlimited OCR 2, an MIT-licensed 3B OCR model that parses hundred-page documents in one request. Its SR-SWA attention keeps per-step decoding cost nearly flat, scoring 77.1 on MarathonDocBench The post Baidu Open-Sources Unlimited OCR 2 for Hundred-Page Document Parsing appeared first on MarkTechPost.
On October 24, 2026, researchers published the paper arXiv:2610.30162v1 on arXiv, introducing FusionEval—the first unified benchmark specifically designed to evaluate fusion methods for large language models. It covers vulnerable aspects such as reasoning chain length and tool invocation, and supports comparisons between fine-tuning-based and zero-shot fusion approaches.
Why it matters：This benchmark fills the gap left by existing evaluations, which inadequately cover long-chain reasoning and tool usage; it clearly distinguishes between average performance and worst-case capability retention, provides a reproducible expert pool (based on Qwen3/Llama), multi-dimensional metrics (including GPU memory and runtime), and open-source code, offering strong practical guidance.
GITHUB HUGGING FACE MODELSCOPE DEMO DISCORD Introduction After months of efforts, we are pleased to announce the evolution from Qwen1.5 to Qwen2. This time, we bring to you: Pretrained and instruction-tuned models of 5 sizes, including Qwen2-0.5B, Qwen2-1.5B, Qwen2-7B, Qwen2-57B-A14B, and Qwen2-72B; Having been trained on data in 27 additional languages besides English and Chinese; State-of-the-art performance in a large number of benchmark evaluations; Significantly improved performance in coding and mathematics; Extended context length support up to 128K tokens with Qwen2-7B-Instruct and Qwen2-72B-Instruct.
