Running an AI Agent 24/7 for Under $2/Day: The Complete Cost Breakdown

When I tell people my AI agent has been running autonomously for weeks — searching bounties, writing articles, checking wallets, and planning its next move — the first question is always: "How much does that cost?"

The answer might surprise you: about $0.40-1.50 per day, depending on how aggressive you are.

Most people assume running an autonomous AI agent requires a $200/month API budget. It does not. Here is exactly what I spend, what is free, and what I have learned about keeping operational costs near zero.

The Daily Burn Rate

LLM inference (~$0.30-1.20/day):
The agent runs as a cron job every 5 minutes. Each tick costs roughly $0.004-0.008 in token consumption. At ~50-100 ticks per day, that is $0.20-0.80. I use DeepSeek Chat, which costs about $0.14/M tokens input and $0.28/M tokens output — significantly cheaper than GPT-4 ($10/M output) or Claude Opus ($15/M output).

Web search (~$0.00-0.10/day):
Firecrawl credits come with the Nous Research subscription. GitHub API searches are completely free.

Infrastructure ($0/day):
The agent runs on my existing Windows 10 laptop. Electricity cost is negligible (~$0.02/day). The Hermes Agent framework is open-source and self-hosted.

Total: $0.30-1.50/day, or roughly $10-45/month.

What Is Free

The real superpower is not the paid APIs — it is what you can accomplish without spending anything:

• GitHub API: Unlimited public searches, issue reads, repo browsing. This is where 90% of bounty hunting happens.
• Dev.to publishing: Free forever. The API costs nothing to call, and articles generate passive views indefinitely.
• WSL/Linux tools: curl, jq, grep, Python, Node — everything is pre-installed or free.
• Hosting: GitHub Pages, Dev.to, personal machine — no cloud hosting bill.
• Content research: Wikipedia, open-source whitepapers, public documentation are all free.
• 10+ free API tiers: Open-Meteo (weather), PullPush (Reddit archive), OpenStreetMap, and more.

Where You Should Spend Money

Expense	Monthly	Worth It?	Why
LLM API ($14/1M output tokens)	$9-30	Yes	This IS the agent
Web search credits	$0-5	Yes	Lets agent find bounties and research
$5 USDC wallet gas	$0-1	Yes	Enables real DeFi and cross-chain ops
Premium APIs	$0-20	Skip	Free tier plus GitHub covers 95%

The Economics of One Article

Here is a concrete example. I wrote and published a RustChain explainer article to Dev.to. The cost breakdown:

• LLM inference (researching RustChain whitepaper plus crafting article): ~$0.12
• API calls (reading GitHub issues, checking bounty rules): ~$0.02
• Publishing: $0 (Dev.to API is free)
• Total investment: $0.14

If the RustChain content bounty pays 3-5 RTC (~$15-25), that is a 100-180x return on my compute cost.

Cost-Cutting Tips I Learned the Hard Way

1. Pin your model. The first time my cron job silently switched from DeepSeek to Claude Opus, I spent $8 on a single tick. Now every cron job pins model and provider explicitly.

2. Use no_agent for deterministic tasks. Log rotation, backup, health checks — none of those need an LLM. Script-only cron jobs cost exactly $0.

3. Batch, do not loop. One big API call (write a 2000-word article) costs less than 20 small ones.

4. Watch your token budget. My agent context window is about 8K tokens per tick. At $0.14/M input, each tick costs ~$0.0011. Per day at 50 ticks: ~$0.11.

5. Fall back to GitHub API when web search credits run out. Firecrawl fails with BILLING_ERROR when credits are exhausted. GitHub REST API is free and unlimited.

The Real Bottleneck

Money is not the bottleneck. Time is.

Real-money bounties get claimed within minutes. Content bounties require a 24-hour review period. But the agent does not sleep. It does not need weekends. While I am asleep, it is searching GitHub, checking its queue, and planning its next move.

Your First $0 Budget

Want to run something similar? Here is what you can do for $0 right now:

1. Get a DeepSeek API key ($5 signup credit lasts weeks)
2. Set up a cron job that runs every 60 minutes
3. Point it at a GitHub issue search for label:bounty
4. Have it log promising results to a file
5. Review the log once a day

The era of autonomous AI agents is not gated by expensive hardware or $20/month subscriptions. It is gated by the willingness to build, iterate, and let your agent keep trying while you focus on the human parts.