Speech · Text to speech

ElevenLabs Flash v2.5 API

Flash variant. Fastest TTS with solid quality.

Price
From $0.01 per run $0.05/1k chars
Typical time
~3 s
Model id
eleven_flash_v2_5

ElevenLabs Flash v2.5 runs on one varg API key and one credit balance, the same as every other model here. You pay the provider's price, with no markup.

POST /v2/tools/speech/call
curl -X POST https://api.varg.ai/v2/tools/speech/call \
  -H "Authorization: Bearer $VARG_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
  "model": "eleven_flash_v2_5",
  "text": "Don'\''t miss this limited time offer — tap the link below!",
  "voice": "rachel"
}'
Real outputDon't miss this limited time offer — tap the link below!

ElevenLabs Flash v2.5 pricing

From $0.01 per run. Prices are in US dollars and are the provider's own, with no markup. For the exact price of a request, send the same body to POST https://api.varg.ai/v2/estimate.

  • elevenlabs $0.05/1k chars
    elevenlabs:eleven_flash_v2_5

    Text to speech

    Per 1,000 characters
    $0.05
    Minimum charge
    $0.01
    Most one request can cost
    $1.00
    Typical time
    ~3 s

ElevenLabs Flash v2.5 inputs

The JSON body of the request. Media inputs are URLs: upload a local file with POST /v2/files and pass the URL it returns. Full JSON Schema, no key needed: api.varg.ai/v2/tools/speech?model=eleven_flash_v2_5

ElevenLabs Flash v2.5 request fields
FieldWhat it does
model string requiredeleven_flash_v2_5 picks a route automatically.
text string required —
voice string —

Provider options

Optional, under provider_options.<provider>. Only the options of the provider that runs the job apply; pin a route to choose it.

provider_options.elevenlabs

ElevenLabs Flash v2.5 options for elevenlabs
FieldWhat it does
text string —
voice string —
model_id string —

Call the ElevenLabs Flash v2.5 API

POST https://api.varg.ai/v2/tools/speech/call with Authorization: Bearer $VARG_API_KEY. It answers 202 with a job right away.

1. Send the request

cURL
curl -X POST https://api.varg.ai/v2/tools/speech/call \
  -H "Authorization: Bearer $VARG_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
  "model": "eleven_flash_v2_5",
  "text": "Don'\''t miss this limited time offer — tap the link below!",
  "voice": "rachel"
}'
JavaScript
JavaScript
const headers = {
  Authorization: `Bearer ${process.env.VARG_API_KEY}`,
  'Content-Type': 'application/json',
}

const res = await fetch('https://api.varg.ai/v2/tools/speech/call', {
  method: 'POST',
  headers,
  body: JSON.stringify({
    "model": "eleven_flash_v2_5",
    "text": "Don't miss this limited time offer — tap the link below!",
    "voice": "rachel"
  }),
})
const job = await res.json() // { id: "job_…", status: "queued" }
Python
Python
import os
import requests

headers = {"Authorization": f"Bearer {os.environ['VARG_API_KEY']}"}

job = requests.post(
    "https://api.varg.ai/v2/tools/speech/call",
    headers=headers,
    json={
      "model": "eleven_flash_v2_5",
      "text": "Don't miss this limited time offer — tap the link below!",
      "voice": "rachel"
    },
).json()  # {"id": "job_…", "status": "queued"}

2. Get the result

Poll the job until its status is completed, failed or cancelled; ElevenLabs Flash v2.5 typically takes about 3 s. The result is at output.outputs[0].url.

GET /v2/jobs/{id}
curl https://api.varg.ai/v2/jobs/$JOB_ID \
  -H "Authorization: Bearer $VARG_API_KEY"

# Poll until "status" is completed, failed or cancelled.
# The result is in output.outputs[0].url
JavaScript
JavaScript
let current = job
while (!['completed', 'failed', 'cancelled'].includes(current.status)) {
  await new Promise((resolve) => setTimeout(resolve, 3000))
  current = await (await fetch(`https://api.varg.ai/v2/jobs/${current.id}`, { headers })).json()
}
console.log(current.output?.outputs?.[0]?.url)
Python
Python
import time

while job["status"] not in ("completed", "failed", "cancelled"):
    time.sleep(3)
    job = requests.get(f"https://api.varg.ai/v2/jobs/{job['id']}", headers=headers).json()

print(job["output"]["outputs"][0]["url"])
Or take a webhook instead of polling

Add options.webhook_url and varg POSTs the finished job to it.

request body
{
  "model": "eleven_flash_v2_5",
  "text": "Don't miss this limited time offer — tap the link below!",
  "voice": "rachel",
  "options": {
    "webhook_url": "https://your-app.com/varg-webhook"
  }
}

From Claude, ChatGPT or Cursor (MCP)

The varg MCP server, https://mcp.varg.ai/mcp, runs ElevenLabs Flash v2.5 with call_tool. Sign in with varg, no API key to paste. How to connect it

call_tool
{
  "tool": "speech",
  "input": {
    "model": "eleven_flash_v2_5",
    "text": "Don't miss this limited time offer — tap the link below!",
    "voice": "rachel"
  },
  "wait": true
}

ElevenLabs Flash v2.5 API: questions

How much does ElevenLabs Flash v2.5 cost on varg?
ElevenLabs Flash v2.5 costs from $0.01 per run on varg ($0.05/1k chars on the cheapest route). varg charges the provider's price with no markup, from one credit balance. For the exact price of a request before you run it, send the same body to POST https://api.varg.ai/v2/estimate.
How do I call the ElevenLabs Flash v2.5 API?
Send POST https://api.varg.ai/v2/tools/speech/call with the header "Authorization: Bearer $VARG_API_KEY" and a JSON body that includes "model": "eleven_flash_v2_5". The call answers 202 with a job right away. Poll GET https://api.varg.ai/v2/jobs/{id} until "status" is "completed", then read output.outputs[0].url, or pass options.webhook_url to be called back.
Can I use ElevenLabs Flash v2.5 from Claude, ChatGPT or Cursor?
Yes. Add the varg MCP server (https://mcp.varg.ai/mcp) to Claude, ChatGPT, Cursor or any other MCP client and sign in with varg, with no API key to paste. The agent runs ElevenLabs Flash v2.5 with call_tool, passing tool "speech" and "model": "eleven_flash_v2_5".
How long does a ElevenLabs Flash v2.5 request take?
Typically about 3 s on the fastest route, by the catalog's estimate. The API answers at once with a job id, so nothing waits on an open connection while it runs.

For AI agents: this page as Markdown is varg.ai/models/eleven_flash_v2_5.md, and every model is listed in varg.ai/models/llms.txt.