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Rate Limits and Throughput
This page covers RPM and TPM limits for Phoeniqs Model as a Service subscriptions. For an overview of the service, see the MaaS landing page.
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Rate limits per subscription
Every MaaS subscription has requests-per-minute (RPM) and tokens-per-minute (TPM) limits. These apply per subscription, not per user or per API key, and are tied to your plan tier. All API keys created on the same subscription draw from the same RPM and TPM budget.
When you exceed either limit, further requests within that minute are rejected until the window resets. If you consistently hit these ceilings during normal use, review the guidance below or consider adding credits to move into a higher tier. See Subscription plans.
Per subscription, not per key
Creating additional API keys does not increase your RPM or TPM allowance. Limits are enforced at the subscription level so that usage stays predictable across your organisation.
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Model context window vs. rate limits
A model's context window is separate from RPM and TPM. It is the maximum number of tokens a single request can contain (input plus output). Raising your TPM ceiling does not increase a model's context window.
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Why these limits exist
MaaS runs on shared infrastructure that serves many customers simultaneously. RPM and TPM limits keep the platform stable under load: without them, a single heavy consumer can consume disproportionate capacity and degrade response quality or availability for everyone else on the platform.
These limits exist to ensure the stability of our MaaS offering for all customers, not to restrict legitimate use. They are a fairness and capacity mechanism, distinct from your monthly credit allowance. You can still have credits available while temporarily hitting a per-minute throughput ceiling during burst traffic.
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Agentic workloads and TPM
TPM limits were rarely a practical concern until teams began using models such as GLM 5 for agentic coding. Agent workflows, including tool calls, MCP context, long conversation history, and repeated prompt expansion, consume tokens far faster than chat or document workloads. That adoption is a healthy signal, but it has changed the load profile on the platform faster than the underlying infrastructure was sized for.
If you are building coding agents or IDE integrations, plan for higher token throughput and consider models with larger context windows where appropriate. See Active Models for context window sizes and pricing.
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Higher throughput coming soon
Phoeniqs will soon roll out plans that let companies purchase a larger reserved amount of TPM on top of their existing subscription. This will give organisations with sustained high-throughput needs a dedicated capacity allocation without affecting other customers on the platform.
Until those plans are available, use the tier table above as your reference, and contact your Phoeniqs account team if you need guidance on sizing your subscription.
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Related links