Error 429: what to do when grok-4.20-0309-reasoning fails

A 429 means you hit a rate limit: the number of requests or tokens sent within a time window exceeded your plan quota.

429 Too Many Requests is a rate-limit response, not an error. It means the request itself is valid but exceeded the request rate or concurrency allowed by your current plan. Back off and retry within the window indicated by the response headers; the request body does not need to change.

grok-4.20-0309-reasoning is served by xAI. 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: Too many concurrent requests. The recommended first action is: Limit concurrency and retry with exponential backoff.

Common causes

  • Too many concurrent requests
  • Quota of the current plan exhausted
  • Retrying immediately without backoff

How to fix

  • Limit concurrency and retry with exponential backoff
  • Switch to a plan with a larger quota
  • Cache repeated requests

Retry with exponential backoff

The snippet below retries when grok-4.20-0309-reasoning returns 429, 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 = 'grok-4.20-0309-reasoning'


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
VendorxAI
Context1M
CapabilitiesReasoning, Tools, Files, Vision
API formatsopenai, openai-response, openai-response-compact, anthropic, gemini, openai-alpha-search
Billing formulap * 1.25 + cr * 0.2 + c * 2.5) : tier("200k_plus", p * 2.5 + cr * 0.4 + c * 5

FAQ

How many retry attempts is reasonable?

You usually do not need to change business code, just the call cadence. Retrying is the most effective first step. With billing p * 1.25 + cr * 0.2 + c * 2.5) : tier("200k_plus", p * 2.5 + cr * 0.4 + c * 5, failed requests are not counted toward usage. Set the retry ceiling to 3–5 attempts and add jitter.

Can setting max_tokens too high trigger 429?

The request parameters must change; retrying alone will not help. This is a client-side configuration issue; nothing changes server-side. The capability tags are Reasoning, Tools, Files, Vision, and parameter ceilings follow from that capability set. The 1M context window sets the maximum input per request; anything beyond it is rejected outright. Fail fast on parameter errors instead of spending retries on them.

429 keeps recurring on grok-4.20-0309-reasoning — how do I tell whether it is the model or my account?

This error is unrelated to model capability; it is a gateway-layer issue. The capability tags for this model are Reasoning, Tools, Files, Vision. If it persists for several minutes, contact platform support to confirm upstream status.

Will I be charged when grok-4.20-0309-reasoning returns 429?

No charge — only output actually produced counts toward usage. Only the output already produced is billed; the failed part is not. With billing p * 1.25 + cr * 0.2 + c * 2.5) : tier("200k_plus", p * 2.5 + cr * 0.4 + c * 5, the cost of long output comes mostly from output tokens. When estimating cost from p * 1.25 + cr * 0.2 + c * 2.5) : tier("200k_plus", p * 2.5 + cr * 0.4 + c * 5, include the retry budget.

Other errors on this model

Other models with the same error

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Data updated: 2026-10-10 15:45

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