Guide for migrating between Kling AI model versions. Covers breaking changes, parameter differences, feature availability, and parallel testing strategies.
| Version | Release | Key Changes |
|---|---|---|
| v1.0 | 2024-06 | Initial T2V + I2V |
| v1.5 | 2024-09 | 1080p, motion brush, I2V-only model |
| v1.6 | 2024-11 | Lip sync, camera paths, effects API |
| v2.0 | 2025-03 | Quality leap, kling-v2-master |
| v2.1 | 2025-06 | Optimized I2V, kling-v2-1-master for T2V |
| v2.5 Turbo | 2025-09 | 40% faster, best speed/quality ratio |
| v2.6 | 2025-12 | Native audio, 30-48 FPS, highest quality |
# v1.x request
body = {
"model_name": "kling-v1-6",
"prompt": "A sunset over mountains",
"duration": "5",
"mode": "standard",
}
# v2.x -- only model_name changes
body["model_name"] = "kling-v2-master"
Breaking changes:
kling-v2-1 is I2V-only (no text-to-video support)body["model_name"] = "kling-v2-6"
body["motion_has_audio"] = True # NEW: synchronized audio
# Cost impact: audio multiplies credits 5x
# 5s standard: 10 -> 50 credits
| Feature | v1.0 | v1.5 | v1.6 | v2.0 | v2.1 | v2.5T | v2.6 |
|---|---|---|---|---|---|---|---|
| Text-to-video | Y | Y | Y | Y | I2V only | Y | Y |
| Image-to-video | Y | Y | Y | Y | Y | Y | Y |
| Camera control | - | - | Y | Y | Y | Y | Y |
| Motion brush | - | Y | Y | Y | Y | Y | Y |
| Lip sync | - | - | Y | Y | Y | Y | Y |
| Effects | - | - | Y | Y | Y | Y | Y |
| Native audio | - | - | - | - | - | - | Y |
| 1080p | - | Y | Y | Y | Y | Y | Y |
def compare_models(prompt, models):
"""Generate same prompt across models for comparison."""
results = {}
for model in models:
r = requests.post(f"{BASE}/videos/text2video", headers=get_headers(), json={
"model_name": model, "prompt": prompt, "duration": "5", "mode": "standard",
}).json()
results[model] = {"task_id": r["data"]["task_id"], "start": time.time()}
# Poll all
while any("url" not in r for r in results.values()):
for model, info in results.items():
if "url" in info or "error" in info:
continue
r = requests.get(
f"{BASE}/videos/text2video/{info['task_id']}", headers=get_headers()
).json()
if r["data"]["task_status"] == "succeed":
info["url"] = r["data"]["task_result"]["videos"][0]["url"]
info["time"] = round(time.time() - info["start"])
elif r["data"]["task_status"] == "failed":
info["error"] = r["data"].get("task_status_msg")
time.sleep(10)
for model, info in results.items():
print(f"{model}: {info.get('url', info.get('error'))} ({info.get('time', '?')}s)")
return results
# Feature flag for instant rollback
KLING_MODEL = os.environ.get("KLING_MODEL_VERSION", "kling-v2-master")
body["model_name"] = KLING_MODEL
# To rollback: export KLING_MODEL_VERSION=kling-v1-6