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error 715-123420 when creating an available LLM model

Saphane 20 Reputation points
2026-04-15T15:08:56.4266667+00:00

Hi,

I have a problem when I want to deploy a LLM model available for and region (gpt-4.1,gpt-4o, text-embeddings-3-small, etc) I always get this error message since yesterday:

User's image

Client Request ID

571359f2-b961-4884-9457-064615d71400

Trace ID

4282ca4e-5314-42c0-80e1-3a798f3f876b

Service Request ID

de503db7-2cfb-43b7-8f4d-afa0bb1cdc6a

I've seen many questions about this error and that's why I gently ask for help to unlock the situation.

Warm Regards,
KS

Azure OpenAI Service
Azure OpenAI Service

An Azure service that provides access to OpenAI’s GPT-3 models with enterprise capabilities.

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Answer accepted by question author
  1. Q&A Assist
    2026-04-15T15:09:20.7166667+00:00
    AI generated content. This question contains an answer created with AI from Q&A Assist. Learn more

    Error 715-123420 during deployment is a generic platform-side failure that the portal surfaces when the deployment request cannot be completed, even though the model and region appear valid. The provided context does not include a product-side workaround or specific remediation steps for this exact error code.

    Given that:

    • The models being deployed (for example, gpt‑4.1, gpt‑4o, text-embeddings-3-small) are listed as available for the chosen region, and
    • The error message explicitly instructs to contact support and provides Trace ID, Client Request ID, and Service Request ID,

    the required next step is to open an Azure support request so the service team can investigate the backend failure using those IDs. Include:

    • The exact error code 715-123420 and message.
    • The region and model name/version selected.
    • The Client Request ID, Trace ID, and Service Request ID from the portal screenshot.
    • The approximate time (with timezone) when the failure occurred.

    If the deployment is business‑critical, create the ticket under a technical support plan with appropriate severity so the engineering team can check for region‑specific capacity, subscription restrictions, or transient platform incidents that are not visible in the public documentation.


    References:

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