Error 400: what to do when claude-haiku-4-5-20251001 fails

A 400 means the request itself is invalid — a missing field, a wrong type, or a parameter this model does not support. Retrying will not help; the request body must change.

400 Bad Request means the server refuses to process the request because the body itself is invalid. Unlike 5xx, a 400 will not resolve by retrying — you get the same response every time. The parameters must be fixed first.

claude-haiku-4-5-20251001 is served by Anthropic. 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: A required field is missing (model or messages). The recommended first action is: Check the request body against the parameter table on this page.

Common causes

  • A required field is missing (model or messages)
  • A parameter has the wrong type
  • A parameter is not supported by this model
  • messages is malformed or role has an invalid value

How to fix

  • Check the request body against the parameter table on this page
  • Remove unsupported parameters and retry
  • Make sure messages is an array with valid role values
  • Start from a minimal request, then add parameters one by one

Retry with exponential backoff

The snippet below retries when claude-haiku-4-5-20251001 returns 400, 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 = 'claude-haiku-4-5-20251001'


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
VendorAnthropic
Context200K
CapabilitiesReasoning, Tools, Files, Vision
API formatsopenai, openai-response, openai-response-compact, anthropic, gemini, openai-alpha-search
Billing formulap * 1 + cr * 0.1 + cc * 1.25 + cc1h * 2 + c * 5

FAQ

With several upstream nodes, does the gateway switch automatically on 400?

It is usually transient and recovers on its own. The capability tags for this model are Reasoning, Tools, Files, Vision. If it persists for several minutes, contact platform support to confirm upstream status. Decide account-level versus model-level first; the two need completely different handling.

How should I monitor 400 in production?

Group the errors by time and node first; the pattern is usually obvious once you do. Keep the request ID and the raw response body, otherwise nothing can be traced. This model is served by Anthropic, so upstream status follows the vendor’s own announcements. Log the request ID on every failure — it beats the status code when debugging.

How long should the timeout be?

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 200K context window and comes from Anthropic. A 200K context means long inputs add noticeably to first-token latency. For long outputs, raise the timeout to 60 seconds or more. Add a cache layer so repeated requests do not all hit the model.

Is 400 related to how claude-haiku-4-5-20251001 is billed?

Only the output already produced is billed; the failed part is not. With billing p * 1 + cr * 0.1 + cc * 1.25 + cc1h * 2 + c * 5, failed requests are not counted toward usage. Check your balance and rate limits in the console before debugging code.

Other errors on this model

Other models with the same error

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Data updated: 2026-10-10 15:55

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