CtrlK
BlogDocsLog inGet started
Tessl Logo

klingai-upgrade-migration

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'.

86

Quality

84%

Does it follow best practices?

Impact

Pending

No eval scenarios have been run

SecuritybySnyk

Passed

No known issues

SKILL.md
Quality
Evals
Security

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

VersionReleaseKey Changes
v1.02024-06Initial T2V + I2V
v1.52024-091080p, motion brush, I2V-only model
v1.62024-11Lip sync, camera paths, effects API
v2.02025-03Quality leap, kling-v2-master
v2.12025-06Optimized I2V, kling-v2-1-master for T2V
v2.5 Turbo2025-0940% faster, best speed/quality ratio
v2.62025-12Native 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

Featurev1.0v1.5v1.6v2.0v2.1v2.5Tv2.6
Text-to-videoYYYYI2V onlyYY
Image-to-videoYYYYYYY
Camera control--YYYYY
Motion brush-YYYYYY
Lip sync--YYYYY
Effects--YYYYY
Native audio------Y
1080p-YYYYYY

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"] = 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

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
Repository
jeremylongshore/claude-code-plugins-plus-skills
Last updated
Created

Is this your skill?

If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.