klingai-upgrade-migration

name	klingai-upgrade-migration
description	Migrate between Kling AI model versions safely. Use when upgrading from v1.x to v2.x or adopting new features. Trigger with phrases like 'klingai upgrade', 'kling ai migrate', 'klingai version update', 'upgrade kling model'.
allowed-tools	Read, Write, Edit, Bash(npm:*), Grep
version	1.18.0
license	MIT
author	Jeremy Longshore <[e-mail]>
tags	["saas","kling-ai","migration","upgrade"]
compatibility	Designed for Claude Code

Kling AI Upgrade & Migration

Overview

Guide for migrating between Kling AI model versions. Covers breaking changes, parameter differences, feature availability, and parallel testing strategies.

Version History

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

Migration: v1.x to v2.x

# 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)
• Camera control intensities produce different results at same values
• Generation times differ (v2.x generally slower, higher quality)

Migration: v2.x to v2.6 with Audio

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 Availability Matrix

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

Parallel A/B Comparison

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.time() - info[])
             r[][] == :
                info[] = r[].get()
        time.sleep()

     model, info  results.items():
        ()
     results

Rollback Strategy

# 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

Resources

• Model Documentation
• Developer Portal