Should Your Team Stay on a Free AI Coding Tier? Run This Three-Lane Break-Even Model First

The capability fight is over. The invoice fight hasn't started.

Two DEV posts landed within three days of each other this month. On 10 September 2026, one asked whether AI is already better at coding than most software developers, and collected 213 reactions and 181 comments (link). On 8 September, "Most 'AI Agents' Are Just If-Statements in a Trench Coat" gathered 105 reactions and 125 comments (link). Then, on 13 September, a third thread argued the problem is not vibe coding but calling it engineering (link).

All three are good reads. None of them answers the question that actually reaches a budget review: which lane should your team pay for, and at what volume does the answer flip?

So let me do the unglamorous part. Here is the model I use to compare a free hosted tier, a self-hosted box, and a metered paid API — plus a script you can run before your next planning meeting.

Three lanes, one unit

Every team I talk to evaluates these three options on sticker price. That's the first mistake.

• Lane A — free hosted access. Someone else's servers, someone else's terms.
• Lane B — self-hosted. Hardware you own or rent, on your network, with your uptime.
• Lane C — metered paid API. You pay per unit of consumption and control nothing about capacity.

Seats lie. Price per million tokens lies harder, because tokens are usually a rounding error next to the line item nobody counts: human review time.

So pick a unit that survives contact with your P&L.

Unit: fully loaded cost per accepted change. An accepted change is an AI-assisted change that passes review and is still in the codebase two weeks later.

Why two weeks? Because a change reverted on day three was never a win, and rollback labor is real labor. If you cannot measure survival yet, use "merged and not reverted in 14 days" as a first proxy — but write down that it is a proxy, not a measurement.

What Lane A refers to in this article

The operator-supplied claims I am working from: MonkeyCode is an open-source project that offers free model access and a free server option, and the operator advertises 10M free tokens for people evaluating it.

Disclosure: This article was prepared as part of MonkeyCode's product outreach.

I have not independently verified the current quota, the model list, the server specification, or the expiry date. Free allocations change, and that is not a scandal — it is a fact you should plan around. Treat Lane A below as "free until the operator says otherwise" and attach a real expiry date to your own assumption before you build a quarter on it.

The eight inputs you actually need

Most cost models fail because they use four inputs and infer the rest. Use these eight, and label the source of each one.

1. Attempts per month. Every AI-assisted change that reached review, including the ones you threw away.
2. Accept rate per lane. Accepted changes ÷ attempts. This differs per lane and people usually assume it doesn't.
3. Review minutes per attempt, per lane. Your reviewer reads differently when the tool differs. Measure it.
4. Loaded hourly cost of the reviewer. Salary plus overhead, not salary.
5. Variable cost per attempt. Tokens, API calls, power draw.
6. Fixed monthly cost. Reserved capacity, amortized hardware, licenses — things you pay for whether you use them or not.
7. Ops hours per month. Upgrades, key rotation, incidents, model swaps, backup.
8. Cost per hour of whoever owns the infrastructure. If nobody owns it, that is Lane B's hidden failure mode.

Inputs 3 and 5 are the ones people guess. Pull 30 recent pull requests and time the reviews with a stopwatch. It takes an afternoon and it will change your conclusion.

A script you can run in twenty minutes

The script below is a proposal, not a measured result. I have not attached a run log, and every number in LANES is an assumption you are expected to overwrite with your own invoice and calendar data.

#!/usr/bin/env python3
"""Compare three AI coding lanes on cost per accepted change.

STATUS: proposal. Every number in LANES is an ASSUMPTION.
Usage:
    python3 lane_breakeven.py --attempts 900 --loaded-hourly 78 --ops-hourly 95
"""

import argparse
from dataclasses import dataclass


@dataclass(frozen=True)
class Lane:
    name: str
    fixed_monthly: float       # paid whether you use it or not
    per_attempt: float         # tokens, API calls, power, per attempt
    review_minutes: float      # human review per attempt
    ops_hours_monthly: float   # upgrades, incidents, key rotation
    accept_rate: float         # fraction of attempts that survive review


LANES = [
    Lane("A free hosted",  0.0,   0.00, 24.0, 0.0, 0.58),
    Lane("B self-hosted", 1450.0, 0.02, 27.0, 9.0, 0.57),
    Lane("C paid metered",  0.0,  0.41, 23.0, 1.0, 0.61),
]


def cost_per_accepted(lane, attempts, loaded_hourly, ops_hourly):
    accepted = attempts * lane.accept_rate
    if accepted <= 0:
        return float("inf"), 0.0
    tokens = attempts * lane.per_attempt
    review = attempts * (lane.review_minutes / 60.0) * loaded_hourly
    ops = lane.ops_hours_monthly * ops_hourly
    total = lane.fixed_monthly + tokens + review + ops
    return total / accepted, total


def self_host_breakeven(self_lane, paid_lane, ops_hourly):
    """Attempts/month where self-hosting ties the metered lane.

    Review cost is treated as lane-independent, which holds only when
    accept_rate and review_minutes match. Change the inputs rather than
    trusting this number if they don't.
    """
    fixed_gap = (self_lane.fixed_monthly
                 + self_lane.ops_hours_monthly * ops_hourly
                 - paid_lane.fixed_monthly)
    per_attempt_gap = paid_lane.per_attempt - self_lane.per_attempt
    if per_attempt_gap <= 0:
        return None
    return max(fixed_gap, 0.0) / per_attempt_gap


def main():
    p = argparse.ArgumentParser()
    p.add_argument("--attempts", type=float, default=900.0)
    p.add_argument("--loaded-hourly", type=float, default=78.0)
    p.add_argument("--ops-hourly", type=float, default=95.0)
    args = p.parse_args()

    print(f"attempts/month={args.attempts:.0f}  loaded=${args.loaded_hourly:.0f}/h")
    print(f"{'lane':<16}{'total/mo':>12}{'accepted':>10}{'per accepted':>14}")
    for lane in LANES:
        per, total = cost_per_accepted(
            lane, args.attempts, args.loaded_hourly, args.ops_hourly)
        accepted = args.attempts * lane.accept_rate
        print(f"{lane.name:<16}{total:>12,.0f}{accepted:>10.0f}{per:>14,.2f}")

    be = self_host_breakeven(LANES[1], LANES[2], args.ops_hourly)
    print()
    if be is None:
        print("self-host ties the metered lane at any volume for these inputs")
    else:
        print(f"self-host ties the metered lane at ~{be:,.0f} attempts/month "
              f"(~{be / 5.0:,.0f} per engineer at 5 engineers)")

    minute_cost = (args.attempts / 60.0) * args.loaded_hourly
    print(f"one extra review minute per attempt costs ~${minute_cost:,.0f}/month")


if __name__ == "__main__":
    main()

A filled example (hypothetical, fully specified)

Picture a five-engineer squad. 900 attempts a month, $78 loaded hourly, $95 hourly for the one person who owns infrastructure. Lane A has no fixed cost and no metered cost because it is free today. Lane B carries a $1,450/month amortized hardware and power line, plus nine ops hours. Lane C meters at $0.41 per attempt plus one ops hour.

python3 lane_breakeven.py --attempts 900 --loaded-hourly 78 --ops-hourly 95

These outputs are arithmetic from the assumptions above — not measurements of any product.

attempts/month=900  loaded=$78/h
lane                 total/mo  accepted  per accepted
A free hosted          28,080       522         53.79
B self-hosted          33,913       513         66.11
C paid metered         27,374       549         49.86

self-host ties the metered lane at ~5,910 attempts/month (~1,182 per engineer at 5 engineers)
one extra review minute per attempt costs ~$1,170/month

Look at the shape of that table. The entire metered token bill for Lane C is $369/month. The review line for the same lane is $26,910/month. The model choice is roughly 1.4% of the total.

That is the finding most teams miss while they argue about which model is smarter.

Sensitivity: three variables, three different answers

A single point estimate is not a decision. Move these three and watch the ranking change.

• Review minutes. Here, one extra minute per attempt costs about $1,170/month. Lane B's review is four minutes slower than Lane C's, which is worth roughly $4,680/month — more than three times Lane B's entire hardware line. That single assumption decides the answer.
• Accept rate. Drop Lane C's accept rate from 0.61 to 0.55 and its cost per accepted change moves from $49.86 to about $55.30, which makes the free lane the cheapest option again. Accept rate is not a detail; it is a ranking variable.
• Ops hours. Self-hosting only ties the metered lane at roughly 5,910 attempts/month for these inputs. Cut ops to two hours and hardware to $700 and the crossover falls to about 2,282 attempts — still around 456 attempts per engineer per month.

And if Lane A quietly throttles or queues, adding three minutes of waiting per attempt costs about $3,510/month. "Free" becomes the second-most-expensive lane without anyone changing a price.

Fit criteria: five questions, one table

Answer these before you pick a lane. The scorecard is a conversation tool, not objective truth — its job is to surface disagreement, not to settle it.

1. Can your source code leave your network at all? If no, Lane A and Lane C are disqualified and the real choice is Lane B versus not adopting.
2. Does one named person spend at least four hours a week owning infrastructure? If no, do not choose Lane B.
3. What is your attempts per month? Below ~1,500, fixed costs dominate and self-hosting almost never amortizes.
4. How spiky is demand? Steady load favors self-hosting; bursty load favors metered billing.
5. How much review headroom do you have? The model shows review dominates, so adding a lane without adding review capacity just relocates the queue.

Signal	Free hosted	Self-hosted	Paid metered
Code can leave your network	no → disqualified	yes	no → disqualified
Named infra owner ≥4h/week	not needed	required	not needed
Attempts per month	low to mid	high enough to amortize	any, but cap the spend
Demand shape	steady, low stakes	steady, sensitive data	spiky bursts
Cost of leaving	low	high, hardware is sunk	low

Hard gates, an owner, an expiry

A model without an enforcement clause is a slide. Write these down.

• Lane A gate: re-approve every 30 days. Free allocations change; a decision made against today's terms should expire with them.
• Lane B gate: kill it if ops hours exceed your stated ceiling for two consecutive months. Name the owner and the ceiling.
• Lane C gate: alert at 80% of the monthly cap, and require a second approval above it.
• Expiry: every lane decision expires in 90 days or when any input moves more than 25%. Whichever comes first.
• Exit criteria: if review minutes per accepted change rise 25% for two consecutive weeks, stop adding seats or lanes and fix the review path first.

One owner per lane. An expiry date. A written exit condition. That is the whole governance cost.

Limitations, and who should skip this

The model above ignores switching costs, quality differences beyond accept rate, and queueing delays when a hosted tier throttles. It treats review cost as lane-independent in the crossover formula, which is wrong whenever review minutes actually differ — and in the example, they do.

Skip this approach if you are a solo developer with fewer than 50 attempts a month; noise will dominate every number and you will spend more time modeling than coding. Skip it if your code cannot leave your network and you have no infra owner — your answer is "none of these lanes," and that is a legitimate answer. And do not build a roadmap on a free allocation you have not dated.

What I would ask you

Before you switch lanes, answer one question: which variable would have to move — review minutes, attempts per month, or ops hours — before your current lane stops being the right choice?

If the honest answer is "review minutes," then the cheapest experiment is a bounded pilot on a free lane, because you are not testing the model. You are testing one number with a stopwatch. MonkeyCode's free model access and free server option exist for exactly that kind of bounded test, and the operator's terms — including the advertised 10M free tokens — are theirs to set and worth reading before you plan a quarter around them.

Measure the review minutes first. Everything else is cheaper than guessing wrong about those.