TL;DR
The cost of a prop challenge is a geometric expectation, not a fixed fee. Expected attempts at a 12% pass-rate is 1/0.12 = 8.3; at a more honest 8% pass-rate (the first-attempt average across the supported firm set) it is 12.5. Add reset fees and the eval cost is genuinely measured in thousands, not hundreds. The Glitch Executor cost calculator runs the exact math against any pass-rate input.
Prop-firm marketing leads with the eval fee because that is the only number with one digit. $540 for a $100k FTMO challenge. $99 for an $8,000 FundingPips trial. $137 for an Apex $50k. These are the prices in the way Amazon list prices are the price you pay: theoretical, optimistic, and ignored once you actually transact. The price an operator pays is total spend across however many resets it takes to pass, and at honest pass-rates, that total is 3–9× the headline.
The geometric-expectation model
A prop challenge is a Bernoulli trial: each attempt either passes or fails. If the pass-rate is p, the expected number of attempts until the first pass is 1/p, basic geometric distribution. The expected cost is (1/p) × eval_fee, plus any reset fees the firm charges between attempts. The model is exact when the pass-rate is stable across attempts; in practice operators learn and improve, which raises p modestly over time but does not collapse the expectation by an order of magnitude.
What expected attempts looks like across pass-rates
| Realistic pass-rate | Expected attempts | Total cost at $540/attempt (FTMO 100k) | Total cost at $99/attempt (FundingPips Zero $8k starter) |
|---|---|---|---|
| 30% (skilled, edge proven) | 3.3 | $1,800 | $330 |
| 20% | 5.0 | $2,700 | $495 |
| 12% (FTMO Phase-1-only average) | 8.3 | $4,480 | $825 |
| 8% (full-programme average) | 12.5 | $6,750 | $1,240 |
| 5% (first-time-attempter, no track record) | 20.0 | $10,800 | $1,980 |
The table understates the cost at most firms because it ignores reset fees, account-size markups for partial-payout structures, and the implicit cost of capital tied up in payout cycles. FundingPips Zero charges no reset fees in 2026 but does enforce a $99-per-attempt fee structure with no challenge-pack discount. FTMO offers a 10% Phase 2 retake at $54, which is the cheapest reset in the supported set. The5ers attaches a fee to every fresh High Stakes challenge but caps it at the lowest absolute number in the set.
Why self-funded breakeven moves with the pass-rate
The natural alternative to a $100k prop challenge is trading $100k of your own money. The breakeven math compares total expected prop cost, eval + resets, against the lump-sum required to self-fund. At a 12% pass-rate, FTMO Phase 1 costs ~$4,500 to pass; the operator now controls a $100k funded account with an 80/20 split. To break even against self-funding $100k, the operator must extract 5% in net realised profit from the funded account. At a 0.5% net daily edge that takes 3 weeks. So far so cheap.
The math flips once you include the months-to-funded latency. At 8.3 expected attempts, even an aggressive operator running attempts back-to-back consumes ~4 months in eval mode. During those four months the self-funded operator has been compounding their own capital. By the time the prop operator clears Phase 2 and enters funded, the self-funded operator has lapped them by roughly 6% of capital at the same edge. The break-even point sits around 7 months of post-funded trading, by which point most prop operators have either hit a consistency-cap denial or moved to a different firm.
The three cost line items operators forget
1. Reset fees and re-evaluation friction
Most firms charge for resets even when the headline marketing implies "free retries". FundingPips Zero charges full price per attempt. FTMO offers a discounted Phase 1 reset but still charges. Apex Trader Funding charges nothing for resets but locks the operator into a tighter funded-phase rule once they fund, the implicit cost is rule-friction, not dollars. The "free reset" framing is almost always a soft signal that some other rule has been tightened to compensate.
2. The implicit cost of payout cycles tied up
Funded profit sitting at a prop firm between payout cycles is not earning. At a bi-weekly cycle and 80/20 split, an operator who builds $4,000 of funded profit over two weeks has $3,200 of their share locked in the firm until cycle close. That $3,200 has a real opportunity cost, call it 0.5% of their working capital monthly, that compounds across the funded lifetime of the account. Over 12 months this can erode 6% of total realised payout. The Glitch Executor payout estimator surfaces this number alongside the next-payout date.
3. The capital-locked-out-during-resets cost
Between attempts, the operator's capital is at the firm waiting for the next attempt to start. Many firms apply a minimum cooling-off period (2–7 days) between attempts. At 8.3 expected attempts and a 3-day average cooldown, the operator loses 25 days of trading optionality across the eval phase. For traders running multiple strategies, that compound friction is real, and rarely modelled.
How to use the cost calculator before you fund
The prop-firm-vs-self-funded calculator on Glitch Executor takes three inputs: target firm, your realistic pass-rate (default 12%), and your time horizon. It returns expected total spend, expected weeks until first funded, expected breakeven against self-funding, and an honest "months until you should consider switching to self-funded" recommendation. The inputs encode into the URL, so an operator can paste a calculation into a Discord thread and the same numbers reproduce for the recipient.
The defaults are deliberately pessimistic, 12% pass-rate, 80% split, 6-month time horizon, because every operator overestimates their pass-rate on first attempt. If the headline number scares you, the strategy is still right: either find an edge that produces a higher real pass-rate, or accept the cost as the price of the leverage.
Citations
FAQ
- Why do firms advertise pass-rates higher than what the geometric model predicts?
- The headline pass-rate is usually Phase-1 only or "lifetime pass-rate of all submitted attempts", both of which are weighted by repeat-attempter survivorship. Operators who give up after two failures vanish from the statistic; operators who persist are over-represented. The honest number for a first-time attempter is 5–8% across the supported set; for a third-attempt operator it climbs to 15–20% as they learn the firm-specific rules.
- Does a higher account size change the expected cost calculus?
- It shifts the absolute dollar amount but not the structural answer. A $200k FTMO challenge costs ~$1,080 per attempt at the same pass-rate, exactly double the $100k. The breakeven against self-funding doubles in absolute terms (self-funded $200k vs prop $200k) but stays at the same number of months. The right account size is determined by your edge's capacity, not by the cost model.
- How do I improve my real pass-rate?
- Three changes move the number most: (1) pre-flight the strategy against the firm's actual rules using the firm-rule-aware backtester, (2) reduce position size on the first 5 days of any attempt to absorb the inevitable variance, (3) treat the consistency-cap rule as a hard limit during the funded phase, not a soft signal. Each of these moves a typical first-attempter from 5% to roughly 12% pass-rate, which halves the expected cost.
- Is reset cost ever worth paying?
- Yes, when the alternative is starting a new firm with a different rule set the strategy has not been pre-flighted against. Pay the reset to stay in a rule set you already know rather than switching to a new firm at apparent zero cost. Familiarity with the rule set is itself a pass-rate multiplier.
- What pass-rate should I assume if I have never traded prop before?
- Use 5%. The calculator default is 12% which fits a second- or third-attempt operator. First-time attempters who have not yet experienced firm-rule pressure are well below average. Assuming 5% gives an expected-cost figure that almost always turns out to be optimistic for first-attempters, which is the right error direction.
- When does self-funded actually win on this math?
- When your edge is real and your capital is greater than ~$30k. Below $30k the leverage benefit of a $100k+ funded account outweighs the geometric cost. Above $30k the math flips: you can self-fund at a size that approximates funded leverage, you keep 100% of profit, and you avoid the consistency-cap risk on every payout cycle.
- How often does the Glitch Executor firm-rule changelog refresh?
- Quarterly for the catalogue-level audit, weekly for the price/fee watcher, and event-driven for any rule that changes mid-quarter. Most firms revise reset structures and minimum-account-size fees during promotional periods; the watcher surfaces those diffs as soon as the firm's public page changes.
Related firm rule pages
This post references the rule sets for the firms below. The full rule + payout brief for each is on its dedicated page.
How we maintain accuracy
Reviewed by Ryan Tran, Strategy Lead, Glitch Executor. Every quantitative claim cites a primary source; firm-rule values come from the firm-rule registry audited quarterly in this repo. No paid placements, no fabricated reviews.
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Written by Ryan Tran
Strategy Lead · Glitch ExecutorWrites on prop-firm rule modelling, backtest correctness, and why most "passed challenge" stories don't reproduce.
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