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
Prerequisites
- A named project, billing owner, approved daily and per-run credit ceilings, and a current provider pricing source. Treat the tables above as estimates until verified against the account's active plan or resource pack.
- Define the model, duration, mode, audio setting, retry allowance, and expected failure rate. Use synthetic prompts and rights-cleared media for all estimation canaries; no real customer or personal data is needed.
- Have a sandbox destination, draft/watermarked output policy, approval threshold, and a plan to cancel queued work and remove test outputs if the estimate is exceeded.
Instructions
- Describe the workload and calculate the worst-case credits, including audio, retries, polling overhead where applicable, and a safety reserve. Check that the run fits both the project and account ceilings.
- Run a single low-cost synthetic canary through
BudgetGuard. Confirm the selected model/mode and actual credit charge before authorizing the larger run.
- Require owner approval for the budget, destination, and promotion from draft/watermarked output to final delivery. Track actual credits by opaque run ID and aggregate model, not by prompt or media.
- Stop when a ceiling, policy check, rate limit, or cost anomaly fires. Cancel pending work where supported, remove quarantined outputs, and restore the approved lower-cost mode or last approved plan.
- At closeout, reconcile estimate versus actual, expire temporary artifacts and access, and retain a redacted cost receipt only.
Output
Return a budget worksheet or receipt with opaque run ID, pricing-source timestamp, model/mode/duration/audio assumptions, expected and maximum credits, reserve, actual credits, estimated currency range, approval state, canary result, destination class, retention deadline, and rollback/removal action. Exclude billing identifiers, prompts, media, user identities, and credentials.
Error Handling
- If pricing or model parameters are stale or unknown, label the estimate provisional and stop before submission; do not infer a cheaper rate.
- If credits are depleted or the charge exceeds the ceiling, pause the run and reconcile completed tasks before retrying. A policy refusal or rights failure is not a reason to retry.
- If actual usage diverges from the estimate, quarantine outputs, cancel remaining tasks, notify the billing owner, and record the redacted variance and cleanup receipt.
Examples
For a synthetic 20-clip draft run, set duration=5, mode=standard, audio=false, credits_max=200, reserve=20%, destination=sandbox-review, and watermark=draft. Require approval=granted after the canary and actual_credits<=200; otherwise cancel pending tasks and remove the canary outputs.
Resources
1---2name: klingai-pricing-basics3description: Understand Kling AI pricing, credits, and cost optimization strategies. Use when budgeting or estimating costs. Trigger with phrases like 'kling ai pricing', 'klingai credits', 'kling ai cost', 'klingai budget'.4license: MIT5---6# Kling AI Pricing Basics
7
8## Overview
9
10Kling 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.
11
12## Subscription Plans (Web UI)
13
14| Plan | Monthly | Credits/Month | Key Features |
15|------|---------|---------------|-------------|
16| Free | $0 | 66/day (no rollover) | Basic access, watermarked |
17| Standard | $6.99 | 660 | No watermark, standard models |
18| Pro | $25.99 | 3,000 | Priority queue, all models |
19| Premier | $64.99 | 8,000 | Professional mode, priority |
20| Ultra | $180 | 26,000 | Max priority, all features |
21
22**Warning:** Paid credits expire at end of billing period. Unused credits do not roll over.
23
24## Video Generation Costs
25
26| Duration | Standard Mode | Professional Mode |
27|----------|--------------|-------------------|
28| 5 seconds | 10 credits | 35 credits |
29| 10 seconds | 20 credits | 70 credits |
30
31### With Native Audio (v2.6)
32
33| Duration | Standard + Audio | Professional + Audio |
34|----------|-----------------|---------------------|
35| 5 seconds | 50 credits | 100 credits |
36| 10 seconds | 100 credits | 200 credits |
37
38## Image Generation Costs (Kolors)
39
40| Feature | Credits |
41|---------|---------|
42| Text-to-image | 1 credit/image |
43| Image restyle | 2 credits/image |
44| Virtual try-on | 5 credits/image |
45
46## API Resource Packs
47
48API access is billed separately from subscriptions via prepaid packs:
49
50| Pack | Units | Price | Validity |
51|------|-------|-------|----------|
52| Starter | 1,000 | ~$140 | 90 days |
53| Growth | 10,000 | ~$1,400 | 90 days |
54| Enterprise | 30,000 | ~$4,200 | 90 days |
55
56**1 unit = 1 credit equivalent.** API pricing works out to ~$0.07-0.14 per second of generated video.
57
58## Cost Estimation
59
60```python
61def estimate_cost(videos: int, duration: int = 5, mode: str = "standard",
62 audio: bool = False) -> dict:
63 """Estimate credits needed for a batch of videos."""
64 base_credits = {
65 (5, "standard"): 10,
66 (5, "professional"): 35,
67 (10, "standard"): 20,
68 (10, "professional"): 70,
69 }
70 per_video = base_credits.get((duration, mode), 10)
71 if audio:
72 per_video *= 5 # audio multiplier
73
74 total = videos * per_video
75 return {
76 "videos": videos,
77 "credits_per_video": per_video,
78 "total_credits": total,
79 "estimated_cost_usd": total * 0.14, # high estimate
80 }
81
82# Example: 100 five-second standard videos
83print(estimate_cost(100, duration=5, mode="standard"))
84# → {'videos': 100, 'credits_per_video': 10, 'total_credits': 1000, 'estimated_cost_usd': 140.0}
85```
86
87## Cost Optimization Strategies
88
89| Strategy | Savings | Trade-off |
90|----------|---------|-----------|
91| Use `standard` mode for drafts | 3.5x cheaper | Slightly lower quality |
92| Use 5s duration, extend if needed | 2x cheaper per clip | Requires extension step |
93| Use `kling-v2-5-turbo` | 40% faster (less queue time) | Marginally lower quality than v2.6 |
94| Batch during off-peak hours | Faster processing | Schedule dependency |
95| Skip audio, add in post | 5x cheaper | Extra post-production step |
96| Use callbacks instead of polling | No cost savings, but fewer API calls | Requires webhook endpoint |
97
98## Budget Guard
99
100```python
101class BudgetGuard:
102 """Prevent overspending by tracking credit usage."""
103
104 def __init__(self, daily_limit: int = 500):
105 self.daily_limit = daily_limit
106 self._used_today = 0
107
108 def check(self, credits_needed: int) -> bool:
109 if self._used_today + credits_needed > self.daily_limit:
110 raise RuntimeError(
111 f"Budget exceeded: {self._used_today + credits_needed} > {self.daily_limit}"
112 )
113 return True
114
115 def record(self, credits_used: int):
116 self._used_today += credits_used
117```
118
119## Prerequisites
120
121- A named project, billing owner, approved daily and per-run credit ceilings, and a current provider pricing source. Treat the tables above as estimates until verified against the account's active plan or resource pack.
122- Define the model, duration, mode, audio setting, retry allowance, and expected failure rate. Use synthetic prompts and rights-cleared media for all estimation canaries; no real customer or personal data is needed.
123- Have a sandbox destination, draft/watermarked output policy, approval threshold, and a plan to cancel queued work and remove test outputs if the estimate is exceeded.
124
125## Instructions
126
1271. Describe the workload and calculate the worst-case credits, including audio, retries, polling overhead where applicable, and a safety reserve. Check that the run fits both the project and account ceilings.
1282. Run a single low-cost synthetic canary through `BudgetGuard`. Confirm the selected model/mode and actual credit charge before authorizing the larger run.
1293. Require owner approval for the budget, destination, and promotion from draft/watermarked output to final delivery. Track actual credits by opaque run ID and aggregate model, not by prompt or media.
1304. Stop when a ceiling, policy check, rate limit, or cost anomaly fires. Cancel pending work where supported, remove quarantined outputs, and restore the approved lower-cost mode or last approved plan.
1315. At closeout, reconcile estimate versus actual, expire temporary artifacts and access, and retain a redacted cost receipt only.
132
133## Output
134
135Return a budget worksheet or receipt with opaque run ID, pricing-source timestamp, model/mode/duration/audio assumptions, expected and maximum credits, reserve, actual credits, estimated currency range, approval state, canary result, destination class, retention deadline, and rollback/removal action. Exclude billing identifiers, prompts, media, user identities, and credentials.
136
137## Error Handling
138
139- If pricing or model parameters are stale or unknown, label the estimate provisional and stop before submission; do not infer a cheaper rate.
140- If credits are depleted or the charge exceeds the ceiling, pause the run and reconcile completed tasks before retrying. A policy refusal or rights failure is not a reason to retry.
141- If actual usage diverges from the estimate, quarantine outputs, cancel remaining tasks, notify the billing owner, and record the redacted variance and cleanup receipt.
142
143## Examples
144
145For a synthetic 20-clip draft run, set `duration=5`, `mode=standard`, `audio=false`, `credits_max=200`, `reserve=20%`, `destination=sandbox-review`, and `watermark=draft`. Require `approval=granted` after the canary and `actual_credits<=200`; otherwise cancel pending tasks and remove the canary outputs.
146
147## Resources
148
149- [Pricing Page](https://app.klingai.com/global/dev/document-api/productBilling/prePaidResourcePackage)
150- [API Resource Packs](https://app.klingai.com/global/dev)