Error 401: what to do when gpt-5-mini fails

A 401 means authentication failed: the request carries no API key, or the key is invalid, deleted or expired.

401 Unauthorized means the request carries no valid credential. The gateway could not identify the caller, so the request never reaches the upstream model. Checking the Authorization header and the key status is the only path forward.

gpt-5-mini is served by OpenAI. Everything on this page — triggers, fixes and measured data — is compiled from the real runtime behaviour of this model at the gateway layer.

At this gateway, the most common trigger is: The Authorization header is missing. The recommended first action is: Send the header as Authorization: Bearer followed by your key.

Common causes

  • The Authorization header is missing
  • The key is misspelled or has stray whitespace
  • The key was deleted or disabled on the Tokens page
  • A key from another platform was used by mistake

How to fix

  • Send the header as Authorization: Bearer followed by your key
  • Generate a fresh key on the Tokens page
  • Check that you are not using a key from another service
  • Verify the key with a minimal curl request

Retry with exponential backoff

The snippet below retries when gpt-5-mini returns 401, up to 5 attempts, with an increasing wait plus random jitter so concurrent calls do not retry in lockstep. Read the base URL and API key from environment variables — never hardcode them.

import os, time, random
import requests

BASE  = os.getenv("OPENAI_BASE_URL")   # e.g. https://<your-gateway>/v1
KEY   = os.getenv("OPENAI_API_KEY")
MODEL = 'gpt-5-mini'


def chat(messages, retries=5):
    """Retry with exponential backoff + jitter."""
    for i in range(retries):
        try:
            r = requests.post(
                BASE + "/chat/completions",
                headers={"Authorization": "Bearer " + KEY},
                json={"model": MODEL, "messages": messages, "stream": True},
                timeout=60,
            )
            if r.status_code == 429 or r.status_code >= 500:
                time.sleep(min(2 ** i + random.uniform(0, 1), 30))
                continue
            r.raise_for_status()
            return r.json()
        except requests.exceptions.Timeout:
            time.sleep(min(2 ** i + random.uniform(0, 1), 30))
    raise RuntimeError("gave up after " + str(retries) + " retries")


print(chat([{"role": "user", "content": "hello"}]))

Key facts for this model

API endpointhttps://api.airai.cc/v1
OpenAI-compatibleOpenAI-compatible
VendorOpenAI
Context400K
CapabilitiesReasoning, Tools, Files, Vision
API formatsopenai, openai-response, openai-response-compact, anthropic, gemini, openai-alpha-search
Billing formulap * 0.25 + cr * 0.025 + c * 2

FAQ

How much concurrency is safe?

Concurrency and timeouts are the real variables here, not the model itself. Lower the concurrency first — most throughput complaints disappear once you do. This model has a 400K context window and comes from OpenAI. A 400K context means long inputs add noticeably to first-token latency. For long outputs, raise the timeout to 60 seconds or more. Use batching or a queue to smooth peaks — steadier than raising concurrency on the fly.

Does 401 affect requests already sent to gpt-5-mini?

This error is unrelated to model capability; it is a gateway-layer issue. The capability tags for this model are Reasoning, Tools, Files, Vision. Decide account-level versus model-level first; the two need completely different handling.

Will retrying cause the request to run twice?

Retrying is the most effective first step. With billing p * 0.25 + cr * 0.025 + c * 2, failed requests are not counted toward usage. Use exponential backoff for retryable errors and return immediately for the rest.

Does sharing one key across several services make 401 more likely?

It is mainly a quota matter, not a fault in the model itself. With billing p * 0.25 + cr * 0.025 + c * 2, the cost of long output comes mostly from output tokens. Check your balance and rate limits in the console before debugging code. When estimating cost from p * 0.25 + cr * 0.025 + c * 2, include the retry budget.

Other errors on this model

Other models with the same error

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Data updated: 2026-10-10 18:35

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