Kling AI Pricing Basics
Overview
Kling AI uses a credit-based pricing system. Credits are consumed per video/image generation based on duration, mode, and model. API pricing uses resource packs billed separately from subscription plans.
Subscription Plans (Web UI)
| Plan |
Monthly |
Credits/Month |
Key Features |
| Free |
$0 |
66/day (no rollover) |
Basic access, watermarked |
| Standard |
$6.99 |
660 |
No watermark, standard models |
| Pro |
$25.99 |
3,000 |
Priority queue, all models |
| Premier |
$64.99 |
8,000 |
Professional mode, priority |
| Ultra |
$180 |
26,000 |
Max priority, all features |
Warning: Paid credits expire at end of billing period. Unused credits do not roll over.
Video Generation Costs
| Duration |
Standard Mode |
Professional Mode |
| 5 seconds |
10 credits |
35 credits |
| 10 seconds |
20 credits |
70 credits |
With Native Audio (v2.6)
| Duration |
Standard + Audio |
Professional + Audio |
| 5 seconds |
50 credits |
100 credits |
| 10 seconds |
100 credits |
200 credits |
Image Generation Costs (Kolors)
| Feature |
Credits |
| Text-to-image |
1 credit/image |
| Image restyle |
2 credits/image |
| Virtual try-on |
5 credits/image |
API Resource Packs
API access is billed separately from subscriptions via prepaid packs:
| Pack |
Units |
Price |
Validity |
| Starter |
1,000 |
~$140 |
90 days |
| Growth |
10,000 |
~$1,400 |
90 days |
| Enterprise |
30,000 |
~$4,200 |
90 days |
1 unit = 1 credit equivalent. API pricing works out to ~$0.07-0.14 per second of generated video.
Cost Estimation
def estimate_cost(videos: int, duration: int = 5, mode: str = "standard",
audio: bool = False) -> dict:
"""Estimate credits needed for a batch of videos."""
base_credits = {
(5, "standard"): 10,
(5, "professional"): 35,
(10, "standard"): 20,
(10, "professional"): 70,
}
per_video = base_credits.get((duration, mode), 10)
if audio:
per_video *= 5 # audio multiplier
total = videos * per_video
return {
"videos": videos,
"credits_per_video": per_video,
"total_credits": total,
"estimated_cost_usd": total * 0.14, # high estimate
}
# Example: 100 five-second standard videos
print(estimate_cost(100, duration=5, mode="standard"))
# → {'videos': 100, 'credits_per_video': 10, 'total_credits': 1000, 'estimated_cost_usd': 140.0}
Cost Optimization Strategies
| Strategy |
Savings |
Trade-off |
Use standard mode for drafts |
3.5x cheaper |
Slightly lower quality |
| Use 5s duration, extend if needed |
2x cheaper per clip |
Requires extension step |
Use kling-v2-5-turbo |
40% faster (less queue time) |
Marginally lower quality than v2.6 |
| Batch during off-peak hours |
Faster processing |
Schedule dependency |
| Skip audio, add in post |
5x cheaper |
Extra post-production step |
| Use callbacks instead of polling |
No cost savings, but fewer API calls |
Requires webhook endpoint |
Budget Guard
class BudgetGuard:
"""Prevent overspending by tracking credit usage."""
def __init__(self, daily_limit: int = 500):
self.daily_limit = daily_limit
self._used_today = 0
def check(self, credits_needed: int) -> bool:
if self._used_today + credits_needed > self.daily_limit:
raise RuntimeError(
f"Budget exceeded: {self._used_today + credits_needed} > {self.daily_limit}"
)
return True
def record(self, credits_used: int):
self._used_today += credits_used
Resources
