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Set model to a > separated list of model IDs. If the first model fails or scores below your quality threshold, the next one runs automatically.

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Request

{
  "model": "claude-opus-4.6>gpt-5>gemini-3.1-pro",
  "messages": [{"role": "user", "content": "Review this contract clause..."}],
  "min_quality": 0.85
}

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Response

{
  "model": "gpt-5",
  "fallback": {
    "chain": ["claude-opus-4.6", "gpt-5", "gemini-3.1-pro"],
    "triggered": true,
    "attempts": [
      {"model": "claude-opus-4.6", "success": false, "error": "timeout"},
      {"model": "gpt-5", "success": true, "quality_score": 0.94}
    ]
  },
  "cost": {"this_request": "$0.006"}
}

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Parameters

ParameterTypeDefaultDescription
modelstring—Up to 4 models separated by >. Example: "a>b>c"
min_qualitynumber—If the response scores below this (0–1), fall back to the next model.
fallback_on_errorbooleantrueContinue to the next model on error. Set to false to fail immediately.

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Billing

You’re charged for each model that runs successfully. If the first model times out and the second succeeds, you pay only for the second.

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Code examples

import requests, os

r = requests.post("https://ninjachat.ai/api/v1/chat",
    headers={"Authorization": f"Bearer {os.environ['NINJACHAT_API_KEY']}"},
    json={
        "model": "claude-opus-4.6>gpt-5>gemini-3.1-pro",
        "messages": [{"role": "user", "content": "Analyze this legal document..."}],
        "min_quality": 0.85,
    }
)
data = r.json()
print(f"Resolved to: {data['model']}")
print(f"Fallback triggered: {data['fallback']['triggered']}")