Replicate Status: How to Check If Replicate API Is Down (2026)
Updated June 2026 · 6 min read · API Status Check
Quick Answer
Check Replicate status at status.replicate.com (official) for real-time predictions and deployment status. You can also test the API directly at api.replicate.com/v1/predictions.
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The Official Replicate Status Page
Replicate maintains an official status page at status.replicate.com. It tracks status across the Replicate platform:
What Each Replicate Status Means
Monitor Replicate API health independently
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Try Better Stack Free →Replicate API for Production: Resilience Patterns
Replicate makes it easy to run open-source AI models at scale. Here is how to build resilient production apps on top of the Replicate API:
Poll Prediction Status With Timeout Handling
Replicate's async prediction model means you submit a job and poll for completion. Always set a maximum poll duration — predictions can fail silently if you poll indefinitely. For synchronous use cases, use Replicate's official client libraries which handle polling automatically.
# Python: poll Replicate prediction with timeout
import replicate, time
def run_with_timeout(model, input, timeout=300):
prediction = replicate.predictions.create(
version=model, input=input
)
start = time.time()
while prediction.status not in ["succeeded", "failed", "canceled"]:
if time.time() - start > timeout:
prediction.cancel()
raise TimeoutError("Replicate prediction timed out")
time.sleep(2)
prediction.reload()
if prediction.status == "failed":
raise RuntimeError(prediction.error)
return prediction.outputUse Webhooks Instead of Long Polling
For high-volume or slow-running predictions (image generation, video, audio), configure webhook callbacks instead of polling. Replicate sends a POST to your endpoint when a prediction completes. This eliminates polling overhead and is more resilient to short API disruptions.
Use Deployments for Production Workloads
Replicate Deployments provision dedicated hardware for your model and keep it warm — eliminating cold-start delays and giving you predictable throughput. Deployments are isolated from shared Predictions API capacity events. The additional cost is justified for production latency-sensitive features.
Track and Retry Failed Predictions
During partial Replicate outages, predictions transition to 'failed'. Build a prediction tracker that logs submission IDs and requeues failed predictions after an incident. Never fire-and-forget Replicate predictions in production — always track IDs so you can resubmit if needed.
5 Ways to Check Replicate Status Right Now
Official Replicate Status Page
Visit status.replicate.com for real-time component status. Subscribe to email notifications for instant outage alerts.
status.replicate.com →Test the Predictions API Directly
Submit a quick prediction and check the response:
# Quick Replicate API health check
curl -s -o /dev/null -w "%{http_code} — %{time_total}s\n" \
-X POST https://api.replicate.com/v1/predictions \
-H "Authorization: Token $REPLICATE_API_TOKEN" \
-H "Content-Type: application/json" \
-d '{"version":"stability-ai/sdxl:...","input":{"prompt":"test"}}'
# 201 = prediction created, 401 = auth error, 503 = outageCheck Your Replicate Dashboard
Log into replicate.com/predictions to see recent prediction history and failure rates. A spike in failed predictions often shows before an official incident is declared.
Replicate Dashboard →Search X/Twitter
Search 'Replicate down' or 'Replicate API outage' on X. The developer community reports issues quickly.
Search X for 'replicate api down' →Check Replicate Discord
Replicate has an active Discord community where outages are reported and acknowledged quickly. Check the #help and #status channels for real-time reports.
Common Replicate API Errors During Outages
These are the errors and symptoms you'll encounter when Replicate is having issues:
"Prediction status: 'failed' with no error message"Usually an infrastructure issue — the worker processing your prediction crashed or was preempted. Resubmit the prediction. If failures persist at high rates, check status.replicate.com."HTTP 503 Service Unavailable"Replicate is experiencing an outage or is temporarily overloaded. Check status.replicate.com. Retry with exponential backoff."HTTP 429 Too Many Requests"You've exceeded Replicate's rate limits. Implement request queuing. Replicate's rate limits apply per API token and reset per minute."Prediction stuck in 'starting' for more than 5 minutes"Extended cold starts can indicate infrastructure issues provisioning hardware. Check status.replicate.com. For frequently-run models, Deployments eliminate cold starts."Webhooks not firing / delayed webhook delivery"Check the Webhooks component on status.replicate.com. Webhook delays are tracked separately from prediction completion. Predictions may succeed but webhook delivery can lag during incidents."HTTP 401 Invalid token"Not an outage — your API token is wrong or has been revoked. Verify the token at replicate.com/account/api-tokens and check the Authorization header uses the Token scheme.What to Do When Replicate Is Down
Immediate Response
- Verify on status.replicate.com before troubleshooting code
- Stop retrying — back off to avoid 429 storms
- Queue pending prediction jobs for resubmission after recovery
- Surface a graceful error: "AI features temporarily unavailable"
- Check webhook delivery separately — it may lag behind recovery
Long-Term Resilience
- Use Deployments for production — isolated from shared capacity events
- Always track prediction IDs for resubmission after failures
- Use webhooks for completion instead of long polling
- Monitor your own prediction failure rate independently
- Set prediction timeouts — never poll indefinitely
Frequently Asked Questions
Where is the official Replicate status page?
Replicate's official status page is at status.replicate.com. It tracks the Predictions API, Deployments, webhooks, and the Replicate website. Subscribe to email notifications for production alerting.
Why is my Replicate prediction taking so long?
Long prediction times have two causes: cold starts (model loading) and slow inference (compute-heavy models). Cold starts are common for models you run infrequently — the response will eventually arrive. Slow inference is model-dependent — video generation and large image models take longer by design. Only check status.replicate.com if predictions are failing, not just slow.
What is the difference between Replicate Predictions and Deployments?
Predictions run on shared, on-demand hardware that cold-starts when idle. Deployments provision dedicated hardware that stays warm and handles traffic up to a configured max workers count. Predictions are cheaper for infrequent use; Deployments are better for production latency-sensitive apps.
How does Replicate's API compare to Hugging Face for reliability?
Both use on-demand inference with cold-start behavior for infrequently-used models. Replicate's model marketplace emphasizes production-ready models with versioned APIs; Hugging Face Inference API has a broader model selection but more free-tier limitations. Both offer dedicated tiers for production workloads.
Does Replicate have an uptime SLA?
Replicate Deployments offer SLAs under enterprise agreements. The shared Predictions API does not come with a contractual uptime guarantee. For workloads requiring guaranteed availability, use Deployments with an enterprise agreement or design your system to tolerate and retry failed predictions.
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