Urgent! LLM Fallback/Latency Issue
# support
d
Hello,I am experiencing a critical LLM latency issue that appears to be caused by an unwanted automatic model fallback in the Vapi infrastructure. My Assistant is currently configured to use Llama 3 70B with the Groq provider (or previously GPT-4o Mini Cluster). However, for multiple calls, the system is consistently falling back to Gemini-2.5-flash (Google provider). This is resulting in unacceptably high LLM latency, frequently ranging around 3-4sec, making the real-time conversation unusable. Evidence: Configured Model: Llama 3 70B (Groq) Observed Fallback (Log Detail): The latest call log shows the Google model being used instead of the configured one. Call ID: 019a0b78-e67c-7118-8a9f-f0a9d26b60a4 Log Data: The log for this call explicitly shows "provider": "google" and "model": "gemini-2.5-flash".Could you please investigate why the system is failing to route to my configured Groq model and why it is instead defaulting to a high-latency Google model?Thank you for your urgent attention to this issue.
c
Hi Daniel, Thank you for sending the call ID. Based on the information from that specific call, here’s what we’re seeing in the configuration:
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{
  "cost": 0.64165,
  "type": "model",
  "model": {
    "model": "llama3-70b-8192",
    "provider": "groq"
  },
  "promptTokens": 51278,
  "completionTokens": 490
},
...
{
  "cost": 0.0002247,
  "type": "analysis",
  "model": {
    "model": "gemini-2.5-flash",
    "provider": "google"
  },
  "analysisType": "summary",
  "promptTokens": 624,
  "completionTokens": 15
}
The
gemini
model you’re seeing is only being used for post-call analysis, not during the assistant conversation itself. Your assistant’s active LLM during the call was indeed Llama 3 70B (Groq). Also, due to how our platform is structured, if Groq were to fail to complete a request, the call would end with a pipeline error rather than falling back to a different model. Currently, only OpenAI is configured to support fallback models. You can find more details in our API documentation here: 👉 [Vapi API – Fallback Models](https://docs.vapi.ai/api-reference/assistants/create#request.body.model.OpenAI.fallbackModels) If you have any other questions or need further clarification, feel free to reach out — happy to help. Best, Kyle Vapi Support Team
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