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

Description and use

StewMind 1.7B enables local agent execution without API costs, reducing latency to ~0.01 s and keeping data on device.

Problem

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.

Outcome

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.

Workflow

• 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.

Evidence

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.

Source

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).

Source

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"}}

Source