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  "path": "/t/a-comprehensive-look-at-gpt-5-4-mini-and-nano-openai-s-small-models-with-big-ambitions/174372#post_2",
  "publishedAt": "2026-03-19T05:22:50.000Z",
  "site": "https://discuss.huggingface.co",
  "tags": [
    "OpenAI",
    "OpenAI Developers"
  ],
  "textContent": "Even by GPT itself:\n\n* * *\n\nYes. For **API use** , I’d switch to **Mini first** and keep **flagship as fallback**.\n\nWhy: Mini is priced at **$0.75 / $4.50** per 1M input/output tokens, supports a **400k context window** plus tool use and computer use, and OpenAI positions it for **high-volume coding, computer use, and agent workflows**. (OpenAI)\n\nThe gap to flagship is real but usually not big enough to justify paying about **3.3x more** on every call. OpenAI’s published scores are **57.7 vs 54.4** on SWE-bench Pro and **75.0 vs 72.1** on OSWorld-Verified for flagship vs mini. (OpenAI)\n\nI’d keep **flagship** for:\n\n  * terminal-heavy work\n  * very long-context jobs\n  * high-stakes outputs\n\n\n\nThat is where the gap gets more meaningful. On **Terminal-Bench 2.0** , flagship scores **75.1** vs **60.0** for mini, and OpenAI describes `gpt-5.4` as the default for your most important work. (OpenAI)\n\nSo the simplest answer is:\n\n**Mini = economic default**\n**Flagship = risk-management default**\n\nFor most coding assistants, agent loops, and routine product traffic, I’d start with **Mini**. For hard shell work, giant prompts, or costly mistakes, I’d route to **flagship**. (OpenAI Developers)",
  "title": "A Comprehensive Look at GPT-5.4 Mini and Nano: OpenAI’s ‘Small’ Models with ‘Big’ Ambitions"
}