The top-ranked futures prop firms for 2026 — compared by fees, payouts, drawdown, and trader rules.
Ready public-evidence plans are sorted ahead of partial or unavailable plans when possible, and missing public fields cannot look favorable in the ranking.
This ranking uses topic metric with estimated model inputs. Numeric output can run, but at least one input is an explicit assumption or legacy fallback rather than confirmed ordinary public evidence.
Informational comparison from ordinary public product/help/rule material. Missing public values stay visible as blockers instead of being treated as neutral.
Primary model note: rankings prioritize rule-derived difficulty, economic friction, constraints, and trader fit from ordinary public product/rule evidence; EV/pass probability are secondary scenario comparison estimates.
Rule-derived ranking blocked by missing public fields: max_profit_split_pct, payout_frequency.
This ranking uses topic metric with estimated model inputs. Numeric output can run, but at least one input is an explicit assumption or legacy fallback rather than confirmed ordinary public evidence.
Informational comparison from ordinary public product/help/rule material. Missing public values stay visible as blockers instead of being treated as neutral.
Primary model note: rankings prioritize rule-derived difficulty, economic friction, constraints, and trader fit from ordinary public product/rule evidence; EV/pass probability are secondary scenario comparison estimates.
Rule-derived ranking blocked by missing public fields: max_profit_split_pct, payout_frequency.
This ranking uses topic metric with estimated model inputs. Numeric output can run, but at least one input is an explicit assumption or legacy fallback rather than confirmed ordinary public evidence.
Informational comparison from ordinary public product/help/rule material. Missing public values stay visible as blockers instead of being treated as neutral.
Primary model note: rankings prioritize rule-derived difficulty, economic friction, constraints, and trader fit from ordinary public product/rule evidence; EV/pass probability are secondary scenario comparison estimates.
Rule-derived ranking blocked by missing public fields: max_profit_split_pct, payout_frequency.
This ranking uses topic metric with estimated model inputs. Numeric output can run, but at least one input is an explicit assumption or legacy fallback rather than confirmed ordinary public evidence.
Informational comparison from ordinary public product/help/rule material. Missing public values stay visible as blockers instead of being treated as neutral.
Primary model note: rankings prioritize rule-derived difficulty, economic friction, constraints, and trader fit from ordinary public product/rule evidence; EV/pass probability are secondary scenario comparison estimates.
Rule-derived ranking blocked by missing public fields: max_profit_split_pct, payout_frequency.
This ranking uses topic metric with estimated model inputs. Numeric output can run, but at least one input is an explicit assumption or legacy fallback rather than confirmed ordinary public evidence.
Informational comparison from ordinary public product/help/rule material. Missing public values stay visible as blockers instead of being treated as neutral.
Primary model note: rankings prioritize rule-derived difficulty, economic friction, constraints, and trader fit from ordinary public product/rule evidence; EV/pass probability are secondary scenario comparison estimates.
Rule-derived ranking blocked by missing public fields: max_profit_split_pct, payout_frequency.
This ranking uses topic metric with estimated model inputs. Numeric output can run, but at least one input is an explicit assumption or legacy fallback rather than confirmed ordinary public evidence.
Informational comparison from ordinary public product/help/rule material. Missing public values stay visible as blockers instead of being treated as neutral.
Primary model note: rankings prioritize rule-derived difficulty, economic friction, constraints, and trader fit from ordinary public product/rule evidence; EV/pass probability are secondary scenario comparison estimates.
Rule-derived ranking blocked by missing public fields: max_profit_split_pct, payout_frequency.
This ranking uses topic metric with estimated model inputs. Numeric output can run, but at least one input is an explicit assumption or legacy fallback rather than confirmed ordinary public evidence.
Informational comparison from ordinary public product/help/rule material. Missing public values stay visible as blockers instead of being treated as neutral.
Primary model note: rankings prioritize rule-derived difficulty, economic friction, constraints, and trader fit from ordinary public product/rule evidence; EV/pass probability are secondary scenario comparison estimates.
Rule-derived ranking blocked by missing public fields: max_profit_split_pct, payout_frequency.
This ranking uses topic metric with estimated model inputs. Numeric output can run, but at least one input is an explicit assumption or legacy fallback rather than confirmed ordinary public evidence.
Informational comparison from ordinary public product/help/rule material. Missing public values stay visible as blockers instead of being treated as neutral.
Primary model note: rankings prioritize rule-derived difficulty, economic friction, constraints, and trader fit from ordinary public product/rule evidence; EV/pass probability are secondary scenario comparison estimates.
Rule-derived ranking blocked by missing public fields: max_profit_split_pct, payout_frequency.
This ranking uses topic metric with estimated model inputs. Numeric output can run, but at least one input is an explicit assumption or legacy fallback rather than confirmed ordinary public evidence.
Informational comparison from ordinary public product/help/rule material. Missing public values stay visible as blockers instead of being treated as neutral.
Primary model note: rankings prioritize rule-derived difficulty, economic friction, constraints, and trader fit from ordinary public product/rule evidence; EV/pass probability are secondary scenario comparison estimates.
Rule-derived ranking blocked by missing public fields: max_profit_split_pct, payout_frequency.
This ranking uses topic metric with estimated model inputs. Numeric output can run, but at least one input is an explicit assumption or legacy fallback rather than confirmed ordinary public evidence.
Informational comparison from ordinary public product/help/rule material. Missing public values stay visible as blockers instead of being treated as neutral.
Primary model note: rankings prioritize rule-derived difficulty, economic friction, constraints, and trader fit from ordinary public product/rule evidence; EV/pass probability are secondary scenario comparison estimates.
Rule-derived ranking blocked by missing public fields: max_profit_split_pct, payout_frequency.
This ranking uses topic metric with estimated model inputs. Numeric output can run, but at least one input is an explicit assumption or legacy fallback rather than confirmed ordinary public evidence.
Informational comparison from ordinary public product/help/rule material. Missing public values stay visible as blockers instead of being treated as neutral.
Primary model note: rankings prioritize rule-derived difficulty, economic friction, constraints, and trader fit from ordinary public product/rule evidence; EV/pass probability are secondary scenario comparison estimates.
Rule-derived ranking blocked by missing public fields: max_profit_split_pct, payout_frequency.
This ranking uses topic metric with estimated model inputs. Numeric output can run, but at least one input is an explicit assumption or legacy fallback rather than confirmed ordinary public evidence.
Informational comparison from ordinary public product/help/rule material. Missing public values stay visible as blockers instead of being treated as neutral.
Primary model note: rankings prioritize rule-derived difficulty, economic friction, constraints, and trader fit from ordinary public product/rule evidence; EV/pass probability are secondary scenario comparison estimates.
Rule-derived ranking blocked by missing public fields: max_profit_split_pct, payout_frequency.
This ranking uses topic metric with estimated model inputs. Numeric output can run, but at least one input is an explicit assumption or legacy fallback rather than confirmed ordinary public evidence.
Informational comparison from ordinary public product/help/rule material. Missing public values stay visible as blockers instead of being treated as neutral.
Primary model note: rankings prioritize rule-derived difficulty, economic friction, constraints, and trader fit from ordinary public product/rule evidence; EV/pass probability are secondary scenario comparison estimates.
Rule-derived ranking blocked by missing public fields: max_profit_split_pct, payout_frequency.
This ranking uses topic metric with estimated model inputs. Numeric output can run, but at least one input is an explicit assumption or legacy fallback rather than confirmed ordinary public evidence.
Informational comparison from ordinary public product/help/rule material. Missing public values stay visible as blockers instead of being treated as neutral.
Primary model note: rankings prioritize rule-derived difficulty, economic friction, constraints, and trader fit from ordinary public product/rule evidence; EV/pass probability are secondary scenario comparison estimates.
Rule-derived ranking blocked by missing public fields: max_profit_split_pct, payout_frequency.
The best firm depends on your priorities. DayTraders offers 100% splits, MFF has the highest ratings, and Apex has the largest user base.
There are 14+ established CME futures prop firms. New firms launch regularly, but not all are reputable. Stick to well-reviewed firms.
Yes. Prop firms provide funded capital without personal financial risk. The key is choosing firms with favorable rules for your trading style.
Major 2026 changes include Apex switching to one-time fees, new firms entering the market, and more firms offering daily payouts.