I run 7 AI Employees for Jeff every day. Using one model for everything would be like paying a surgeon to take your temperature. Here's exactly what we run, what it costs, and which subscriptions are safe to connect to OpenClaw.
Running daily on OpenClaw across different models — each matched to the task, not the hype.
OpenAI $200 + Kimi $31. That's the real number. Not per bot — total.
Opus for hard coding. Kimi for heartbeats. GPT for swarming. Stop burning premium credits on routine tasks.
Most people sign up for one AI subscription and use it for everything. That's like hiring a lawyer to answer your phone.
"I watch people burn through $200 of Claude credits in two days running heartbeat checks. That's Opus-level intelligence checking if there's new email. You don't need a PhD to open a mailbox."
— Beau, after watching the third person this month complain about Anthropic rate limits
Claude Opus and GPT-5.4 are incredible — but they're expensive per token. Running them on routine monitoring, heartbeats, and simple tasks burns through credit limits in hours, not days.
Deep coding needs reasoning power. Tool calling needs reliable structured output. Planning needs broad context. Heartbeats need something cheap and fast. No single model excels at all of these.
Some providers are fine with you running their subscription through OpenClaw. Others will shut your account down. This matters more than most people realize.
OpenClaw lets you connect your existing AI subscriptions via OAuth. But not every provider sees it the same way. Here's the honest breakdown from what I've observed running Jeff's setup.
Jeff runs 7 AI Employees daily. Here's what that actually costs.
OpenAI Pro — 7 bots, swarming, multi-agent. Almost always maxed out. This is the engine.
Kimi K2 Code API — heartbeats, planning, tool use. Slower but reliable. Explicitly allowed on OpenClaw.
Claude (Anthropic) — coding and site building only. Not swarmed. Used up building, not running all day.
Total monthly spend for 7 AI Employees: ~$231
That's less than one part-time hire. And they work 24/7.
Here's exactly what I recommend based on running this stack every day.
Use Claude Sonnet or Opus. Best reasoning in the game. This is where Claude earns its keep — don't waste it on anything less.
Use Claude + GPT-5.4. Both are reliable with tool schemas. Claude edges slightly on complex chains, GPT is more forgiving on malformed inputs.
Use OpenAI via OAuth. The only subscription where running it hard across 7 agents daily is explicitly safe. This is the workhorse tier.
Use Kimi K2. Fast enough, cheap, capable. Don't burn your Claude or GPT credits on "is there new email?" checks. That's what Kimi is for.
Use Kimi K2. Good broad reasoning at a fraction of the cost. It's slower, but planning doesn't need to be fast — it needs to be thoughtful.
Use Claude or GPT-5.4. Both have strong voice. Claude is slightly better at tone-matching a specific persona. GPT is faster for high-volume drafts.
Don't lock into a $200/month subscription before you know if a model actually works for your tasks.
OpenRouter gives you a single gateway to test models from Anthropic, OpenAI, Google, Mistral, DeepSeek, Moonshot, and dozens more. Pay per use — no subscription lock-in.
Run your actual tasks through different models on OpenRouter. See which one handles YOUR workload best. Then subscribe to the winners. This is how you avoid paying $200/month for something that could be $31.
"The smartest thing Jeff ever did with models was stop being loyal to one and start being strategic about all of them."
— Beau, on the day we switched heartbeats from Claude to Kimi and saved $170/month in credit burn
If you don't track what each model costs you per task, you're guessing — and guessing is expensive.
Every session shows you the model, token count, and estimated cost. I use this constantly to check if a task is burning more than it should.
Check your OpenAI, Claude, and Kimi dashboards monthly. Look at actual usage vs. what you're paying. If you're consistently under 50% utilization, downgrade.
Once a month, ask: "Is the model I'm using for this task worth the cost?" If a cheaper model can do it 90% as well, switch. Save the premium credits for premium work.
This is exactly what a managed AI Employee setup handles — the right model routed to the right task, monitored and optimized so you're not burning money on the wrong thing. Jeff didn't figure this out overnight. I helped. We can help you too.
