How much does Groq Whisper Large v3 cost on varg?

Groq Whisper Large v3 costs from $0.06 per run on varg. 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 Groq Whisper Large v3 API?

Send POST https://api.varg.ai/v2/tools/transcription/call with the header "Authorization: Bearer $VARG_API_KEY" and a JSON body that includes "model": "groq_whisper_large_v3". 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 Groq Whisper Large v3 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 Groq Whisper Large v3 with call_tool, passing tool "transcription" and "model": "groq_whisper_large_v3".

How long does a Groq Whisper Large v3 request take?

Typically about 5 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.

Transcription · Transcription

Groq Whisper Large v3 API

Groq-hosted Whisper Large v3. Fast inference with high accuracy.

Price: From $0.06 per run
Typical time: ~5 s
Model id: groq_whisper_large_v3

Groq Whisper Large v3 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/transcription/call

curl -X POST https://api.varg.ai/v2/tools/transcription/call \
  -H "Authorization: Bearer $VARG_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
  "model": "groq_whisper_large_v3",
  "audio_url": "https://example.com/audio.mp3"
}'

Try it in the Playground Get an API key

Groq Whisper Large v3 pricing

From $0.06 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.

groq $0.06
groq:whisper_large_v3
Transcription
Fixed price
$0.06
Typical time
~5 s

Groq Whisper Large v3 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/transcription?model=groq_whisper_large_v3

Groq Whisper Large v3 request fields
Field	What it does
`model` string required	`groq_whisper_large_v3` picks a route automatically.
`prompt` string	—
`audio_url` string (URL) required	—
`language` string	Allowed e.g. en \| ru \| es \| de \| fr \| it \| pt \| ja \| ko \| zh \| hi \| ar

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.groq`

Groq Whisper Large v3 options for groq
Field	What it does
`language` string	Allowed e.g. en \| ru \| es \| de \| fr \| it \| pt \| ja \| ko \| zh \| hi \| ar
`audio_url` string (URL)	—

Call the Groq Whisper Large v3 API

POST https://api.varg.ai/v2/tools/transcription/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/transcription/call \
  -H "Authorization: Bearer $VARG_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
  "model": "groq_whisper_large_v3",
  "audio_url": "https://example.com/audio.mp3"
}'

JavaScript

const headers = {
  Authorization: `Bearer ${process.env.VARG_API_KEY}`,
  'Content-Type': 'application/json',
}

const res = await fetch('https://api.varg.ai/v2/tools/transcription/call', {
  method: 'POST',
  headers,
  body: JSON.stringify({
    "model": "groq_whisper_large_v3",
    "audio_url": "https://example.com/audio.mp3"
  }),
})
const job = await res.json() // { id: "job_…", status: "queued" }

Python

import os
import requests

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

job = requests.post(
    "https://api.varg.ai/v2/tools/transcription/call",
    headers=headers,
    json={
      "model": "groq_whisper_large_v3",
      "audio_url": "https://example.com/audio.mp3"
    },
).json()  # {"id": "job_…", "status": "queued"}

2. Get the result

Poll the job until its status is completed, failed or cancelled; Groq Whisper Large v3 typically takes about 5 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

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

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": "groq_whisper_large_v3",
  "audio_url": "https://example.com/audio.mp3",
  "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 Groq Whisper Large v3 with call_tool. Sign in with varg, no API key to paste. How to connect it

call_tool

{
  "tool": "transcription",
  "input": {
    "model": "groq_whisper_large_v3",
    "audio_url": "https://example.com/audio.mp3"
  },
  "wait": true
}