Together AI Status: How to Check If the Together API Is Down Right Now (2026)
Updated June 2026 · 6 min read · API Status Check
Quick Answer
Check Together AI API status at status.together.ai (official) for real-time inference status. You can also test the API directly at api.together.xyz/v1/chat/completions.
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The Official Together AI Status Page
Together AI maintains an official status page at status.together.ai. It tracks status across the Together platform:
What Each Together AI Status Means
Monitor Together AI API health independently
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Try Better Stack Free →Together AI for Production: Resilience Patterns
Together AI is popular for serving open models at scale, including chat, embeddings, images, and fine-tuned models. Here is how to stay resilient against Together outages:
Implement Exponential Backoff for API Calls
Together errors during shared-capacity pressure are usually transient. Use exponential backoff with jitter: 1-second initial delay, double each retry, ±20% jitter, up to 60 seconds. Most partial Together incidents resolve within minutes.
# Python retry pattern for Together AI
import time, random
def together_with_retry(fn, max_retries=4):
for attempt in range(max_retries):
try:
return fn()
except Exception as e:
if attempt == max_retries - 1:
raise
delay = (2 ** attempt) + random.uniform(0, 1)
time.sleep(min(delay, 60))
continueUse a Dedicated Endpoint for Critical Models
Together's serverless endpoints share capacity, so a demand spike on a popular model can degrade your latency. For uptime- and latency-critical workloads, provision a dedicated endpoint with reserved capacity — it is isolated from shared-serverless incidents and gives you predictable throughput.
Configure an OpenAI-Compatible Fallback
Together uses an OpenAI-compatible API, so failover is simple: switch your client's base_url to another OpenAI-compatible provider (OpenAI, Fireworks, Groq, or a self-hosted server) when Together returns errors. Use a circuit breaker: after 3 consecutive errors in 60 seconds, route to fallback for 5 minutes, then probe Together again.
Pin Model Names and Cache Embeddings
Together hosts hundreds of models and rotates its catalog; keep model identifiers in config so a deprecation doesn't need a code deploy. For RAG pipelines, cache embeddings keyed by content hash so retrieval keeps working during an embeddings outage.
5 Ways to Check Together AI Status Right Now
Official Together AI Status Page
Visit status.together.ai for real-time per-component status. Subscribe to notifications for instant outage alerts.
status.together.ai →Test the Together API Directly
Make a quick chat completions call to verify the endpoint is responding:
# Quick Together AI health check
curl -s -o /dev/null -w "%{http_code} — %{time_total}s\n" \
-X POST https://api.together.xyz/v1/chat/completions \
-H "Authorization: Bearer $TOGETHER_API_KEY" \
-H "Content-Type: application/json" \
-d '{"model":"meta-llama/Llama-3.3-70B-Instruct-Turbo","messages":[{"role":"user","content":"hi"}],"max_tokens":1}'
# 200 = healthy, 429 = rate limited, 503 = outageCheck the Together Dashboard
Log into the Together dashboard and review usage and error-rate views. A spike in errors often shows in your dashboard before an incident is declared publicly.
Together Dashboard →Search X/Twitter
Search 'Together AI down' or 'Together API outage' on X. Together's developer community reports issues quickly.
Search X for 'together ai down' →Probe Your Dedicated Endpoint or Fallback
Test a dedicated endpoint or your fallback provider. If those work but the serverless API fails, the issue is shared-serverless-specific, not your network or code.
Common Together AI Errors During Outages
These are the errors and symptoms you'll encounter when Together AI is having issues:
"HTTP 503 Service Unavailable from api.together.xyz"The inference API is experiencing an outage or shared capacity is overloaded. Check status.together.ai. 503s during Together incidents are often transient — retry with exponential backoff, or switch to a dedicated endpoint."HTTP 429 Too Many Requests"You hit a rate limit (requests/min or tokens/min), which varies by model and tier. Implement backoff. For consistent throughput on a hot model, a dedicated endpoint avoids shared-serverless throttling."Request timeout / stream stalls mid-generation"Inference is timing out under load. For streaming responses this shows as the stream starting then stalling. Set explicit client timeouts and add retry logic."model not available / invalid model"The model name is deprecated, misspelled, or was removed from serverless. Together rotates its large model catalog — this is not an outage. Update your model identifier from the current model list."HTTP 500 Internal Server Error"An unexpected error on Together's infrastructure, usually transient during degraded performance. Retry with backoff; if 500s persist with no incident posted, contact Together support with your request ID."HTTP 401 Unauthorized"Not an outage — your API key is missing, malformed, or revoked. Verify the key in the Together dashboard and confirm your Authorization header uses the Bearer scheme.What to Do When Together AI Is Down
Immediate Response
- Verify on status.together.ai before troubleshooting your code
- Activate your OpenAI-compatible fallback provider
- Pause batch jobs and back off retries to avoid 429 storms
- Surface a graceful error: "AI features temporarily unavailable"
- Subscribe to status.together.ai if you haven't already
Long-Term Resilience
- Provision a dedicated endpoint for critical, latency-sensitive models
- Use a circuit breaker with automatic failover to a second provider
- Keep model names in config so deprecations don't need a deploy
- Monitor your own Together error rate — it detects degradation before status.together.ai
- Keep fallback prompts tested — an untested fallback is useless
Frequently Asked Questions
Where is the official Together AI status page?
Together AI's official status page is at status.together.ai. It tracks the inference API (chat/completions, embeddings, images), fine-tuning, and dedicated endpoints. Subscribe to notifications for production alerting.
What is the difference between serverless and dedicated endpoints for uptime?
Serverless endpoints share capacity across all Together customers, so a demand spike on a popular model can degrade your latency or trigger 429s. Dedicated endpoints reserve isolated capacity for your workload, giving predictable throughput and insulation from shared-serverless incidents — the better choice for production-critical paths.
Is Together AI downtime the same as a rate limit?
No. Rate limits (HTTP 429) are usage caps that reset per minute — not an outage. An outage returns 500/503 errors regardless of usage, or times out. If you only see 429s, check your usage in the Together dashboard, add backoff, or move to a dedicated endpoint.
How does Together AI compare to OpenAI for reliability?
OpenAI runs first-party closed models at very high traffic with a long incident history. Together specializes in serving open models (Llama, Mixtral, Qwen, and more) on shared and dedicated infrastructure. Because Together is OpenAI-compatible, the safest production setup uses one as primary and the other as an automatic fallback.
Does Together AI offer an uptime SLA?
Contractual uptime SLAs are typically part of dedicated-endpoint and enterprise agreements. Standard pay-as-you-go serverless access does not include a guaranteed SLA. For workloads needing guaranteed availability, use a dedicated endpoint or pair Together with a fallback provider.
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