Together AI is a cloud platform for running and serving open models through an OpenAI-compatible API, plus hosted endpoints for inference, fine-tuning, and dedicated GPU capacity. Teams use it to power chatbots, retrieval pipelines, agents, batch generation jobs, and production apps that call its inference endpoints at scale. Because so much of that traffic is automated and latency-sensitive, even a brief disruption shows up fast: API calls start timing out, jobs stall, and downstream features that depend on a model response break. When that happens, the first job is to confirm whether the problem is Together AI itself or something on your side. Check the live verdict and recent user reports at the top of this page before you start digging.
Common reasons Together AI stops working
- API endpoint errors or timeouts. Inference requests return 5xx responses, hang, or time out, usually pointing to a backend or capacity problem rather than your code.
- Authentication failures. An expired, revoked, or misconfigured API key returns 401 or 403 errors, which can look like an outage but are account-level.
- Rate limits and quota caps. Bursts of traffic trigger 429 responses; you are being throttled, not necessarily seeing a platform failure.
- Slow or degraded inference. Endpoints respond, but latency spikes or tokens stream slowly, often during periods of heavy demand on shared capacity.
- Model or endpoint availability. A specific hosted model or a dedicated endpoint is unavailable, cold-starting, or has been deprecated while the rest of the platform is fine.
- Fine-tuning or batch jobs stuck. Long-running jobs queue, stall, or fail without completing.
- Dashboard, billing, or console issues. The web console or login fails even when the inference API keeps serving requests.
- Network and regional problems. DNS, your ISP, a VPN, or a regional route can block reachability for you while others connect normally.
How to fix Together AI when it is not working
- Check the status at the top of this page first. If the live verdict and user reports show a wider problem, the issue is likely on Together AI’s side and you should wait rather than change your code.
- Read the actual error code. A 401 or 403 means authentication, 429 means rate limiting, and 5xx or timeouts point to the platform. Each needs a different fix.
- Verify your API key. Confirm the key is active, has the right permissions, and is being sent correctly. Rotate it if you suspect it was revoked.
- Retry with backoff. For timeouts and 429s, add exponential backoff and retries instead of hammering the endpoint, which only deepens throttling.
- Test a second model or endpoint. If one hosted model fails, try another. If a dedicated endpoint is down, fall back to a shared one to isolate the fault.
- Rule out your network. Switch off any VPN, try a different connection, and test the endpoint from a separate machine or region.
- Reduce load. Lower concurrency, batch size, or request rate so you stay inside quota while the platform recovers.
- Check capacity and billing. Confirm your account is in good standing and you have not exhausted credits or a spending cap.
If none of that restores service, the problem is most likely Together AI itself. For a calm, structured checklist while you wait, see our guide on what to do when an AI tool is down.
Is Together AI down, or is it just you?
Some failures are global and some are local. A platform-wide outage hits everyone at once: API calls fail across regions and reports climb quickly. A local issue, like a stale API key, a tripped rate limit, a VPN, or a regional network fault, only affects you. The fastest way to tell them apart is to compare your experience against the live verdict and the crowd-sourced reports near the top of this page. If others are reporting the same symptoms at the same time, it is almost certainly Together AI. If the page looks healthy and only you are affected, focus on your key, your quota, and your network.
How we check Together AI
Together AI publishes an official status page at status.together.ai, and our monitor reads its live status feed directly, including the per-component breakdown: the Website, the Playground and each inference model are tracked separately, and only the Website component drives the main verdict. On top of that we run our own independent reachability check against Together AI from the outside, probing it the way a real client would and watching for failures, errors, and slow responses. We combine that signal with the crowd-sourced user reports submitted on this page, so the verdict reflects both what our checks see and what real users are experiencing right now. For the full details of how we test and score services, see our methodology.
Alternatives to Together AI during an outage
If Together AI is down and you need to keep shipping, several peer platforms serve open and hosted models through similar APIs. Groq focuses on very low-latency inference. Replicate hosts a broad catalog of models behind a simple API. Hugging Face offers inference endpoints across a large model library. Before you switch any production traffic, confirm the backup is healthy on its own status page first, since outages sometimes overlap. Keeping one alternative pre-integrated and tested makes failover far less painful when it counts.
Where Together AI tends to break
Together AI is a platform for running open models through a hosted inference API, plus a web console for keys, billing, and usage. Because it serves a large catalog of community and open weight models, problems are often scoped to a single model or family rather than the whole service. A model can be deprecated, taken down, or temporarily unavailable while every other endpoint keeps responding, so a failure on one model name does not mean Together is down.
When the platform itself struggles, your code sees it as HTTP errors: 429 when you hit per minute request or token limits, 401 or 403 for an invalid or revoked key, 404 for a model that no longer exists at that identifier, and 5xx during backend trouble. The console where you sign in and manage API keys is a separate surface from inference, so you can lose dashboard access while requests still succeed.
- Confirm whether failures hit one model or all of them.
- Check that the model identifier still exists and has not been renamed.
- Watch for 429s that signal your own account rate limit, not an outage.