{
  "id": 16012918,
  "title": "Hands-On: Qwen3.8-Flash-Next and a Glimpse into Qwen4's Design Philosophy — llama.cpp Support Status and A100 Benchmarks",
  "url": "https://urgent.news/2026/10/22/hands-on-qwen3-8-flash-next-and-a-glimpse-into-qwen4s-design",
  "topic": "ai",
  "section": "AI",
  "published": "2026-10-22T07:11:51.000Z",
  "source": {
    "name": "Dev.to",
    "slug": "dev-to",
    "url": "https://dev.to/oooocean66/hands-on-qwen38-flash-next-and-a-glimpse-into-qwen4s-design-philosophy-llamacpp-support-2p2c"
  },
  "original_language": "en",
  "account": "On August 26, 2026, the Qwen team announced the release of a new model, Qwen3.8-Flash-Next, scheduled for August 27. The announcement generated excitement within the community, as the Qwen3.8 series had already demonstrated impressive performance, with Qwen3.8-Flash-Next being described as a next-generation architecture leading up to Qwen4. To gain a deeper understanding, I delved into researching hybrid attention structures and began exploring this new model immediately. This article will first examine the architecture of Qwen3.8-Flash-Next, followed by its support status in llama.cpp and hands-on benchmarks on an NVIDIA A100 80GB.",
  "summary": "Out of nowhere, on August 26, 2026, the Qwen team posted an announcement on ModelScope and Hugging Face: a new model, Qwen3.8-Flash-Next, would be released at 00:00 on August 27. The community was still buzzing over how strong the Qwen3.8 series already was, and the accompanying note describing it as a \"next-generation architecture heading toward Qwen4\" only added to the excitement. What exactly…",
  "key_points": [],
  "editors_take": null,
  "illustration": null,
  "coverage": {
    "outlets": 1,
    "also_reported_by": []
  },
  "ai_generated": true,
  "disclaimer": "Summaries, key points and the editor’s take are written by software from other outlets’ reporting and may contain errors — always check the linked original."
}