Error 401: what to do when mimo-v2.5 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.

mimo-v2.5 is served by Xiaomi. 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 mimo-v2.5 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 = 'mimo-v2.5'


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
VendorXiaomi
Context1M
CapabilitiesReasoning, Tools, Files, Open Weights, Vision, Audio
API formatsopenai, openai-response, openai-response-compact, anthropic, gemini, openai-alpha-search
Billing formulap * 0.14 + cr * 0.0028 + c * 0.28

FAQ

Does switching to a smaller model reduce 401?

Building a fallback into the architecture is more reliable than patching errors one by one. This model from Xiaomi has several upstream nodes the gateway can switch between. Keep a lighter fallback model ready so the main flow never breaks. Put the model name in config, so switching upstreams needs no code change.

Staging is fine but production returns 401 — what could differ?

Keep the request ID and the raw response body, otherwise nothing can be traced. This model is served by Xiaomi, so upstream status follows the vendor’s own announcements. Log the request ID on every failure — it beats the status code when debugging. Reproduce it once in a staging environment with the same request body.

Do I need to upgrade my plan to fix 401 on mimo-v2.5?

It is mainly a quota matter, not a fault in the model itself. Raising the plan ceiling or lowering the call rate both help. Input price is about $0.14 per million tokens. With billing p * 0.14 + cr * 0.0028 + c * 0.28, failed requests are not counted toward usage. Check your balance and rate limits in the console before debugging code.

Do failed requests count against my rate limit quota?

No charge — only output actually produced counts toward usage. Input price is about $0.14 per million tokens. With billing p * 0.14 + cr * 0.0028 + c * 0.28, the cost of long output comes mostly from output tokens. When estimating cost from p * 0.14 + cr * 0.0028 + c * 0.28, include the retry budget.

Other errors on this model

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Data updated: 2026-10-10 15:40

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