10 Million Free Tokens: A Token-Budget Field Test on a Free Server

MonkeyCode, an open-source AI coding project offering free model access and a free server option, was field-tested to measure how far its 10-million-token allowance goes on realistic coding tasks. The test harness, built by a developer, revealed that full-file rewrites consume about 3,300 tokens per run, eleven times more than fresh code generation, and that task choice can change capacity by an order of magnitude, from 3,000 to 33,000 tasks. The findings aim to help developers plan token budgets instead of guessing.

A teammate received a free AI coding allowance last month. He burned it in two days. Not on complex architecture. On repeated full-file rewrites. Each rewrite consumed thousands of tokens. The allowance died before the week ended. Most developers cannot answer one simple question: the token cost of a refactor. This article answers it with a reproducible harness. The goal is planning a 10-million-token allowance instead of guessing. The test target is MonkeyCode, an open-source AI coding project. It offers free model access and a free server option. The operator states the free allowance at 10 million tokens. Disclosure: This article was prepared as part of MonkeyCode's product outreach. The experiment measures one thing: how far the allowance goes on realistic tasks. It also shows where the free server performs well and where it breaks. Token counting is the foundation. Real tokenizers vary by model. A 4-characters-per-token heuristic is stable enough for budgeting. The harness logs every request. python budget harness.py import csv import time from dataclasses import dataclass @dataclass class Task: name: str system: str user: str @dataclass class Run: task: str prompt tokens: int completion tokens: int total tokens: int latency s: float status: str def estimate tokens text: str - int: 4 chars per token is a safe budgeting heuristic. return max 1, len text // 4 def call model system: str, user: str - str: """Replace with the provider SDK call.""" raise NotImplementedError "Add your provider adapter here." def run task task: Task - Run: prompt tokens = estimate tokens task.system + estimate tokens task.user start = time.perf counter try: output = call model task.system, task.user status = "ok" except Exception as exc: output = str exc status = "failed" latency = round time.perf counter - start, 2 completion tokens = estimate tokens output return Run task.name, prompt tokens, completion tokens, prompt tokens + completion tokens, latency, status The harness writes a CSV log. Each row records task, prompt tokens, completion tokens, total, latency, and status. The call model stub is the only part to replace. Swap in the provider SDK. Token cost depends on task shape. The benchmark set covers five common shapes. TASKS = Task "generate", "You write short, correct Python. No explanations.", "Write a pagination helper. Inputs: page, page size, total. " "Return a dict with items, page, has next, total pages." , Task "debug", "You explain one root cause. Be brief.", "This traceback appears: paste traceback . What is the root cause?" , Task "tests", "You write pytest tests. Use asserts. Cover edge cases.", "Write tests for the pagination helper." , Task "refactor", "You refactor Python for readability. Keep behavior identical.", "Refactor this function: paste 30-line function ." , Task "rewrite", "You rewrite this whole file. Keep the public API.", "Rewrite this file with better structure: paste 200-line file ." , Sample run: five repetitions per task, identical prompts. | Task | Prompt tokens | Completion tokens | Total per run | |---|---|---|---| | generate | ~120 | ~180 | ~300 | | debug | ~210 | ~140 | ~350 | | tests | ~260 | ~390 | ~650 | | refactor | ~350 | ~420 | ~770 | | rewrite | ~1,400 | ~1,900 | ~3,300 | Full-file rewrites cost eleven times a fresh generation. That is the entire budgeting problem in one table. Simple division turns the table into a plan. Task choice changes capacity by an order of magnitude. A team that defaults to rewrites gets 3,000 tasks. A team that defaults to targeted edits gets 33,000. The cheapest token is the one you never send. The harness then ran 50 tasks on the free server. Ten per task type. Sequential execution. No retries. Sample results: The free server performs well on short, focused tasks. Generations and debug sessions completed without drama. It breaks on long completions and rapid sequential calls. Two rewrites exceeded the response window. One burst of quick calls was rejected. Free tiers carry no guarantees. Teams with client SLAs should not build on them. Large monorepo work explodes token counts. Regulated environments need audit trails a free server does not promise. Sample size is 50 tasks over one day. The heuristic counts 4 characters per token. Real tokenizers differ. Quotas and model availability change. Verify current terms before relying on any number here. Token blindness is a budget leak. A 10-million-token allowance is generous on small tasks. It evaporates on rewrites. The harness turns guessing into accounting. Fork it, run it, and share your numbers.