elevenlabs-rate-limits
Implement ElevenLabs rate limiting, concurrency queuing, and backoff patterns. Use when handling 429 errors, implementing retry logic, or managing concurrent TTS request throughput for an ElevenLabs integration. Trigger with "elevenlabs rate limit", "elevenlabs throttling", "elevenlabs 429", "elevenlabs retry", "elevenlabs backoff", "elevenlabs concurrent requests".
Allowed Tools
Provided by Plugin
elevenlabs-pack
Claude Code skill pack for ElevenLabs (18 skills)
Installation
This skill is included in the elevenlabs-pack plugin:
/plugin install elevenlabs-pack@claude-code-plugins-plus
Click to copy
Instructions
ElevenLabs Rate Limits
Overview
Handle ElevenLabs rate limits with plan-aware concurrency queuing, exponential backoff, and quota monitoring. ElevenLabs uses two rate limit mechanisms: concurrent request limits (per plan) and system-level throttling. The key insight is that a 429 means two different things depending on its detail.status — and each demands the opposite response.
Prerequisites
- ElevenLabs SDK installed (
@elevenlabs/elevenlabs-js) - Understanding of your subscription plan's limits
p-queuepackage (recommended):npm install p-queue
Instructions
Step 1: Understand the Two 429 Error Types
ElevenLabs returns HTTP 429 for two different reasons. Read the detail.status field to tell them apart — the correct strategy is opposite for each.
| 429 Variant | Response Body | Cause | Strategy |
|---|---|---|---|
toomanyconcurrent_requests |
{"detail":{"status":"toomanyconcurrent_requests"}} |
Exceeded plan concurrency | Queue requests, don't backoff |
system_busy |
{"detail":{"status":"system_busy"}} |
Server overload | Exponential backoff |
Step 2: Know Your Plan Concurrency Limits
Concurrency is capped per plan. Size your queue to this number — never higher.
| Plan | Max Concurrent Requests | Characters/Month |
|---|---|---|
| Free | 2 | 10,000 |
| Starter | 3 | 30,000 |
| Creator | 5 | 100,000 |
| Pro | 10 | 500,000 |
| Scale | 15 | 2,000,000 |
| Business | 15 | Custom |
Step 3: Assemble the Four Building Blocks
Write four small modules and compose them. The full, copy-ready source for each is in references/implementation.md — the skeleton below shows how they fit together.
- Request queue (
rate-limiter.ts) — ap-queuesized to your plan's concurrency limit. This is the response totoomanyconcurrent_requests: queue, do not back off. - Backoff wrapper (
backoff.ts) — exponential backoff with jitter forsystem_busyand 5xx; immediate short retry for concurrency; hard-fail on 401/400/404. - Quota monitor (
quota-monitor.ts) — pollsuser.subscriptioncharacter usage, warns at a threshold, and blocks a request that would overrun remaining quota. - Resilient client (
resilient-client.ts) — composes all three so onegenerateSpeech()call guards quota, queues, and backs off automatically:
// src/elevenlabs/resilient-client.ts (skeleton — full source in references/implementation.md)
export function createResilientClient(plan = "pro") {
const client = new ElevenLabsClient({ maxRetries: 0 }); // we handle retries
const queue = createRequestQueue(plan); // Step 3.1
const quota = new QuotaMonitor(client); // Step 3.3
return {
async generateSpeech(voiceId, text, modelId = "eleven_multilingual_v2") {
await quota.guardRequest(text.length); // Step 3.3
return queue.add(() => // Step 3.1
withBackoff(() => // Step 3.2
client.textToSpeech.convert(voiceId, { text, model_id: modelId })
)
);
},
};
}
Step 4: Mind Model Cost When Managing Quota
Quota is spent in credits-per-character, which varies by model. Use Flash/Turbo models during development to conserve quota.
| Model | Credits per Character | 10,000 Chars Cost |
|---|---|---|
eleven_v3 |
1.0 | 10,000 credits |
elevenmultilingualv2 |
1.0 | 10,000 credits |
elevenflashv2_5 |
0.5 | 5,000 credits |
eleventurbov2_5 |
0.5 | 5,000 credits |
Output
Applying this skill produces four TypeScript modules under src/elevenlabs/ and a rate-limited request path:
rate-limiter.ts— exportscreateRequestQueue(plan)returning a plan-sizedPQueue.backoff.ts— exportswithBackoff(operation, config)returning the operation's result or throwing aftermaxRetries.quota-monitor.ts— exports aQuotaMonitorclass withcheck()→{ used, limit, remaining, pctUsed, warning }andguardRequest(textLength).resilient-client.ts— exportscreateResilientClient(plan)whosegenerateSpeech()returns TTS audio, plusgetQueueStats()andcheckQuota().
At runtime: concurrent requests stay at or below the plan cap, system_busy responses are retried with backoff, and requests that would overrun quota fail fast with a clear error instead of a wasted API call.
Error Handling
| Scenario | Detection | Response |
|---|---|---|
| Concurrent limit hit | 429 + toomanyconcurrent_requests |
Queue; retry after ~50ms per queued request |
| System busy | 429 + system_busy |
Exponential backoff (1s, 2s, 4s, 8s...) |
| Quota exhausted | 401 + quota_exceeded |
Stop requests; alert; wait for reset |
| Server error | 500-599 | Exponential backoff; max 5 retries |
Examples
Concise starting point — batch generation with just the queue:
import { createRequestQueue } from "./elevenlabs/rate-limiter";
const queue = createRequestQueue("pro"); // 10 concurrent
const clips = await Promise.all(
texts.map(text =>
queue.add(() => client.textToSpeech.convert(voiceId, { text, model_id: "eleven_flash_v2_5" }))
)
); // 20 requests, at most 10 in flight
For the full resilient-client example, per-429-variant branching at the call site, and the batch pattern in context, see references/examples.md.
Resources
- ElevenLabs Rate Limits Help
- ElevenLabs Pricing
- p-queue Documentation
- references/implementation.md — full source for all four building blocks
- references/examples.md — worked end-to-end usage examples
Next Steps
For security configuration, see elevenlabs-security-basics.