OpenAI's GPT-6.1 Sol Is Brilliant. I Still Won't Put It Inside My Agents.

Описание и применение

Модель StewMind 1.7B позволяет запускать агенты локально без API‑заплат, снижая задержки до ~0,01 с и обеспечивая конфиденциальность данных.

Задача

High API costs, tighter rate limits, and token usage on every agent step make using GPT‑6.1 Sol expensive and unreliable for agent workloads.

Результат

Agents run locally with zero API cost, ~0.01s routing latency, and no data leaving the device, while still leveraging GPT‑6.1 Sol for deep reasoning when required.

Рабочий процесс

• 1. Train StewMind 1.7B on 100,000 agentic workflow samples.
• 2. Deploy the model locally using a GGUF format in Ollama or llama.cpp.
• 3. Invoke the model for tool routing, memory ops, and intent routing within the agent loop.
• 4. Optionally call GPT‑6.1 Sol for deep reasoning when needed.

Доказательства

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, memory ops, retries.

Источник

StewMind 1.7B (local) – Cost per 1M tokens $0.00 — forever; Agent routing call ~0.01s, on your CPU; Data privacy Never leaves the device; Works offline Yes; Ownership Yours (Apache-2.0, weights included).

Источник

Tool routing — input: "Send 5000 naira to my brother today"; reply with JSON only. She answered: {"tool":"payment","args":{"amount":5000,"recipient":"brother","currency":"naira","date":"today"}}

Источник