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

python
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

python
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

• Pricing Page
• API Resource Packs