The cost math — when AI video is viable and when it bankrupts you — step 6 of 6

Final drill. Synthesize price + retake + quality into a router: route_to_model(budget, quality_floor, retake_tolerance) that takes:

• budget (float): max dollars per finished minute the user can spend.
• quality_floor (str): minimum acceptable quality, one of "ai_flavored", "client_grade", "premium".
• retake_tolerance (float): the retake multiplier the user expects to hit.

Each model has a quality_tier per this table:

Quality ordering (each tier accepts higher tiers as substitutes): ai_flavored < client_grade < premium. So if quality_floor == "client_grade", both client_grade and premium models are eligible.

Algorithm:

1. Filter models down to those whose quality_tier is >= quality_floor.
2. Compute each eligible model's $/min real = price_per_sec × 60 × retake_tolerance.
3. Keep only models where $/min real <= budget.
4. From the remaining set, return the CHEAPEST one (lowest $/min real). On a tie, prefer the model that appears EARLIER in the PRICES dict order.
5. If no model fits, return "NO MATCH".

Five scenarios run. Expected output:

$10 + ai_flavored + 2.5x       -> Hailuo 02 (768p)
$20 + client_grade + 3.0x      -> Kling 3.0 standard
$50 + premium + 1.5x           -> Sora 2 Pro (720p)
$200 + premium + 4.0x          -> Sora 2 Pro (720p)
$2 + client_grade + 5.0x       -> NO MATCH