When the Free Tier Stops Being Cheap: A Load-Based Exit Test for Agent Backends

A developer published a load-based exit test for teams running agent backends on free-tier endpoints, arguing that free capacity fails quietly as latency, retries, and queue debt rather than through outright outages. The post, prepared as part of MonkeyCode's product outreach, provides a Python probe script measuring p50/p95 latency and error rate against a configurable budget, plus a decision table for deciding when to migrate off a free tier. The author notes the harness was not executed against MonkeyCode for the article and advises reading current quota terms before planning around any free allowance.

A team moves its nightly agent job onto a free endpoint. Week one looks perfect. Week four, the queue drains ten minutes late and the on-call engineer has no data. The endpoint did not break. The workload changed shape around it. Free tiers rarely fail loudly; they fail as latency, retries, and quiet queue debt. This post is a stop rule, not a sales pitch. It gives you one probe, one decision table, and a set of exit criteria you can wire into CI. Free capacity absorbs small workloads well. It degrades along a curve as concurrency and retries stack up. Three effects dominate that curve: None of these raise an alert by default. You only see them if you measure the tail, not the mean. MonkeyCode is an open-source coding agent project. The operator states that it provides free model access and a free server option, with a free token allowance listed in the terms in effect on 2026-09-15. Quotas and hardware change often, so read the current terms page before you plan around any number. Disclosure: This article was prepared as part of MonkeyCode's product outreach. Free access answers a cost question. It does not answer a fitness question. The rest of this post measures fitness. You need four measurements before any migration decision: The script below is a template harness. It has not been executed against MonkeyCode for this article. Adapt the body shape to your provider, then run it in your own environment. bash /usr/bin/env python3 """free tier probe.py - measure tail latency and error rate on a JSON endpoint.""" import argparse, asyncio, json, os, time import httpx PROMPT = "Reply with exactly one word: pong" async def one call client, endpoint, headers, model, timeout s : body = { "model": model, "messages": {"role": "user", "content": PROMPT} , "max tokens": 4, } t0 = time.perf counter try: resp = await client.post endpoint, headers=headers, json=body, timeout=timeout s return {"ok": resp.status code == 200, "status": resp.status code, "ms": time.perf counter - t0 1000} except Exception as exc: return {"ok": False, "status": type exc . name , "ms": time.perf counter - t0 1000} def percentile values, q : if not values: return float "nan" ordered = sorted values idx = min len ordered - 1, int round q len ordered - 1 return ordered idx async def run endpoint, api key, model, total, concurrency, timeout s : headers = {"Authorization": f"Bearer {api key}", "Content-Type": "application/json"} limits = httpx.Limits max connections=concurrency async with httpx.AsyncClient limits=limits as client: sem = asyncio.Semaphore concurrency async def guarded : async with sem: return await one call client, endpoint, headers, model, timeout s started = time.perf counter results = await asyncio.gather guarded for in range total wall s = time.perf counter - started return results, wall s def summarize results, wall s, p95 budget ms, error budget : lat = r "ms" for r in results errors = r for r in results if not r "ok" report = { "requests": len results , "wall seconds": round wall s, 2 , "p50 ms": round percentile lat, 0.50 , 1 , "p95 ms": round percentile lat, 0.95 , 1 , "max ms": round max lat , 1 , "error rate": round len errors / len results , 4 , } report "verdict" = "pass" if report "p95 ms" <= p95 budget ms and report "error rate" <= error budget else "exit" return report def main : ap = argparse.ArgumentParser ap.add argument "--endpoint", required=True ap.add argument "--model", required=True ap.add argument "--requests", type=int, default=200 ap.add argument "--concurrency", type=int, default=8 ap.add argument "--timeout", type=float, default=30.0 ap.add argument "--p95-budget-ms", type=float, default=6000.0 ap.add argument "--error-budget", type=float, default=0.02 args = ap.parse args api key = os.environ "FREE TIER KEY" results, wall s = asyncio.run run args.endpoint, args.api key if False else api key, args.model, args.requests, args.concurrency, args.timeout report = summarize results, wall s, args.p95 budget ms, args.error budget print json.dumps report, indent=2 raise SystemExit 0 if report "verdict" == "pass" else 1 if name == " main ": main Run it with a key in the environment, never in the file: export FREE TIER KEY=... do not commit this python free tier probe.py \ --endpoint https://<free-endpoint /v1/chat/completions \ --model <free-model-id \ --requests 200 --concurrency 8 \ --p95-budget-ms 6000 --error-budget 0.02 echo $? 0 = keep it here, 1 = start the exit plan The exit code is the point. A probe that only prints a table gets ignored. A probe that fails CI forces a decision. Measure cold start separately. Wait at least thirty minutes idle, then time a single call. Record it next to the warm p50. | Workload shape | Free tier fit | Reason | |---|---|---| | Local dev chat, one user | Good | Low concurrency hides tail latency | | Idempotent lint or test agent | Conditional | Safe only with capped retries | | Nightly batch inside a wide window | Conditional | Drain time must fit the window | | Interactive path with a latency SLO | No | No capacity guarantee to cite | | 10x burst fan-out | No | Retries multiply during bursts | | Contractual uptime obligations | No | You need a vendor commitment | Conditional means the probe decides. "No" means no probe will save it. Write these down while the system is calm. Numbers below are policy examples, not product facts. Set your own. Criterion five is the honest one. Free compute stops being free when it consumes senior time. Any two of these means the exit plan should already exist. Most teams need two of these, not all five. For everyone else, the probe is cheap and the answer arrives in an hour. Free access is a legitimate place to start an agent backend. It is a poor place to hide an unmeasured one. Run the probe against your free endpoint this week. If it passes, keep the workload there and revisit next quarter. If it fails, you now have a dated report to justify the next step, and a soft place to try the free server option before you commit to anything larger.