TokenMix Research Lab · 2026-04-24

Chat completion API provider returned error Fix Guide

"Chat completion API provider returned error" Fix Guide

The error chat completion API provider returned error appears in Cursor, Cline, Continue.dev, and OpenRouter-integrated apps when an upstream LLM provider fails mid-request. It's a generic wrapper error — the actual problem varies. Root causes include: provider rate limit (429), model not available at provider, authentication failure on provider's side, provider outage, malformed request that passes gateway validation but fails at provider, and content filtering blocks. This guide walks through diagnosing and fixing each sub-case. TokenMix.ai includes automatic fallback routing that converts most of these errors into successful retries on alternate providers.

Table of Contents


Confirmed vs Speculation

Claim Status
Error appears in multiple IDE / tools Yes — common wrapper
Usually upstream provider issue Yes
Same error masks different causes Yes — frustrating
Cursor shows more detail in logs Yes — check ~/.cursor/logs
Gateway-level retry can fix Often
Permanent issue requires manual fix Sometimes

Snapshot note (2026-04-24): Error-wrapping behavior differs across IDE versions (Cursor 3.x logs behave differently from 2.x), Cline release cycles, and OpenRouter's fallback config. Sub-error taxonomy below reflects the most common patterns seen as of April 2026 — specific error-code text varies slightly between provider versions. Always check raw upstream error before applying the "right fix".

Step 1: Get the Actual Provider Error

The wrapper error hides the real problem. To debug:

Cursor: Open ~/.cursor/logs/[latest].log → search for "provider returned" or "completion_error"

Cline: Output panel → Cline → look for full stack trace with upstream_error

OpenRouter: Response body JSON has error.metadata.raw field with original provider error

TokenMix.ai: Response headers include X-Provider-Error-Code and X-Provider-Error-Message showing the underlying cause

Common Sub-Errors

Underlying error Root cause Fix
429 Rate limit Provider rate limit hit Backoff, tier upgrade, or route elsewhere
401 Unauthorized Provider's key invalid/revoked at gateway layer Gateway refresh or contact support
model not found Model ID doesn't exist at this provider Check exact model ID
503 Service unavailable Provider outage Wait or fallback
context length exceeded Prompt too long Reduce or use longer-context model
content filter triggered Prompt / response blocked by safety Adjust content or use more permissive model
billing_required Provider needs payment Update billing on provider side
invalid request format Gateway → provider schema mismatch Check SDK version, update if old

Fix by App: Cursor, Cline, OpenRouter

In Cursor (BYOK mode):

  1. Check error log for specific provider error
  2. Try different model ID in settings
  3. If using OpenRouter: check OpenRouter dashboard for provider health
  4. Switch to direct provider (Anthropic direct vs via OpenRouter)

In Cline:

  1. Open Output panel → Cline output
  2. Look for full error stack
  3. Common fix: switch model provider entirely (Anthropic → OpenAI or vice versa)
  4. For persistent issues: check Cline GitHub issues

In OpenRouter:

  1. OpenRouter dashboard → Request history → expand failed request
  2. Shows upstream provider raw error
  3. OpenRouter has automatic fallback — ensure it's enabled in model settings
  4. Some models configurable to "always fallback on error"

Via TokenMix.ai:

Implementing Robust Retry Logic

from openai import OpenAI, APIError
import time

def robust_call(prompt, models=None):
    """Try models in order, fallback on error"""
    models = models or [
        "anthropic/claude-sonnet-4-6",
        "openai/gpt-5-4",
        "z-ai/glm-5.1"  # budget fallback
    ]
    
    client = OpenAI(base_url="https://api.tokenmix.ai/v1", api_key="key")
    
    for model in models:
        for attempt in range(3):
            try:
                return client.chat.completions.create(
                    model=model,
                    messages=[{"role": "user", "content": prompt}]
                )
            except APIError as e:
                if "rate_limit" in str(e).lower():
                    time.sleep(2 ** attempt)
                    continue
                # Other errors: break to next model
                break
    
    raise RuntimeError("All providers failed")

Key principles: different error types = different strategies. Rate limit = retry same model. Other errors = fall over to different model.

FAQ

Why is the error so unhelpful?

Tools that wrap multiple providers (gateways, IDEs) sometimes catch upstream errors and wrap them generically to provide unified UX. Trade-off: uniformity at cost of debuggability. Always check logs for underlying details.

Does this error mean the provider is down?

Not necessarily. Could be your auth issue, rate limit, malformed request, or content filter — none are "provider down." Check provider status page (status.openai.com, status.anthropic.com) to confirm.

Can I prevent this error?

Not entirely — transient errors happen. Design for resilience: implement exponential backoff, multi-provider fallback, circuit breaker pattern (stop calling failing provider temporarily). TokenMix.ai does this automatically.

What if I get this error with my own Anthropic/OpenAI direct call?

Then the gateway isn't the wrapper — your app / SDK is. Check SDK version is current. Check error response body for specific provider error. Direct calls give you raw error; no gateway mystery.

Do tools like Cursor auto-retry?

Some yes, some no. Cursor 3.x has auto-retry for transient errors. Cline has limited retry. OpenRouter depends on fallback config. For production code, implement your own retry layer — don't rely on tool defaults.

Is this the same as "upstream error"?

Yes, different naming. "Upstream error" is more technical; "chat completion API provider returned error" is user-facing. Both mean the same thing.

How common is this error in production?

With single-provider setup: <1% of requests typical. With good multi-provider fallback (via TokenMix.ai): approaches 0% visible errors since fallbacks succeed.


Sources

By TokenMix Research Lab · Updated 2026-04-24