{
  "id": 16736587,
  "title": "OpenAI's GPT-6.1 Sol Is Brilliant. I Still Won't Put It Inside My Agents.",
  "url": "https://urgent.news/2026/10/27/openais-gpt-6-1-sol-is-brilliant-i-still-wont-put-it-inside-my-agents",
  "topic": "ai",
  "section": "AI",
  "published": "2026-10-27T10:55:54.000Z",
  "source": {
    "name": "Dev.to",
    "slug": "dev-to",
    "url": "https://dev.to/emmanuel_erogian/openais-gpt-61-sol-is-brilliant-i-still-wont-put-it-inside-my-agents-i2o"
  },
  "original_language": "en",
  "account": "OpenAI released GPT-6.1 Sol on September 29, 2026. It is an impressive model, but the author has decided not to use it in their agents. In 2026, the costs and limitations of using OpenAI's models have changed, prompting the author to develop their own agent brain, StewMind 1.7B. StewMind is a Nigerian-built model fine-tuned for running agents locally. The author benchmarks StewMind against GPT-6.1 Sol and finds that StewMind performs well on agentic tasks such as tool routing, planning, memory operations, and intent routing. StewMind runs offline, privately, and costs nothing per 1 million tokens. While GPT-6.1 Sol excels at deep reasoning, StewMind is better suited for reflex-based tasks, making it a suitable choice for agents. The author encourages others to use StewMind, as small language models are the future of agentic AI, especially in regions where cloud costs are a concern.",
  "summary": "OpenAI just shipped GPT-6.1 Sol (Sept 29, 2026). It's genuinely brilliant. And I still won't use it inside my agents. Don't get me wrong — for deep reasoning, GPT-6.1 is untouchable by any 1.7B model, including mine. But here's what changed in 2026: API prices went UP on 10 of 14 model tiers , rate limits got tighter, and every agentic loop I ship burns tokens on every step — routing, tool calls,…",
  "key_points": [
    "OpenAI released GPT-6.1 Sol on September 29, 2026",
    "Author prefers StewMind 1.7B over GPT-6.1 Sol for agents",
    "StewMind is a locally-run, offline, and free model for agentic tasks"
  ],
  "editors_take": "Prioritizing small, local models over massive cloud-based reasoning engines signals a shift toward cost-effective, private, and reflex-oriented intelligence for specialized agentic tasks.",
  "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."
}