{
  "id": 5691292,
  "title": "I Tested Q4_K_M vs MXFP4 on the Same Laptop — The Supposedly-Faster New Format Lost",
  "url": "https://urgent.news/2026/09/05/i-tested-q4-k-m-vs-mxfp4-on-the-same-laptop-the-supposedly-faster-new",
  "topic": "ai",
  "section": "AI",
  "published": "2026-09-05T01:47:32.000Z",
  "source": {
    "name": "Dev.to",
    "slug": "dev-to",
    "url": "https://dev.to/pitambarmahato/i-tested-q4km-vs-mxfp4-on-the-same-laptop-the-supposedly-faster-new-format-lost-3ej1"
  },
  "original_language": "en",
  "account": "A reporter compared the performance of two local LLMs, Alibaba's Qwen3-14B in Q4_K_M format and OpenAI's gpt-oss-20B in MXFP4 format, on the same laptop with the same hardware and prompt. The supposedly faster MXFP4 format actually performed worse, generating text at half the speed of Q4_K_M. The report suggests that Q4_K_M is still the optimal choice for speed on M2 or M3 Macs, while MXFP4 may become competitive on newer M4-class Macs.",
  "summary": "I tested two local LLMs in two different quantization formats on the same laptop, on the same prompt, three trials each. The result is the opposite of what the marketing says: the supposedly-faster new format lost by 1.8x. Q4_K_M (the older integer-based format) hit 4.7 tokens/second and finished a 200-token generation in 44 seconds. MXFP4 (OpenAI's newer microscaling FP format) hit 2.6…",
  "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."
}