Whisper Large v3 Turbo (Streaming) API

Realtime speech transcription optimized for voice agents

Try Streaming Whisper

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Whisper Large v3 Turbo enables realtime voice agent applications with WebSocket streaming transcription. Purpose-built infrastructure combines optimized model inference with intelligent voice activity detection and turn detection, delivering complete transcripts 1.4 seconds faster than alternatives. Ideal for conversational AI, customer support bots, and any application requiring natural, low-latency voice interaction.

Whisper Large v3 Turbo (Streaming) API Usage

Endpoint

curl -X POST "https://api.together.xyz/v1/chat/completions" \
  -H "Authorization: Bearer $TOGETHER_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "openai/whisper-large-v3",
    "messages": [
      {
        "role": "user",
        "content": "What are some fun things to do in New York?"
      }
    ]
}'
curl -X POST "https://api.together.xyz/v1/images/generations" \
  -H "Authorization: Bearer $TOGETHER_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "openai/whisper-large-v3",
    "prompt": "Draw an anime style version of this image.",
    "width": 1024,
    "height": 768,
    "steps": 28,
    "n": 1,
    "response_format": "url",
    "image_url": "https://huggingface.co/datasets/patrickvonplaten/random_img/resolve/main/yosemite.png"
  }'
curl -X POST https://api.together.xyz/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $TOGETHER_API_KEY" \
  -d '{
    "model": "openai/whisper-large-v3",
    "messages": [{
      "role": "user",
      "content": [
        {"type": "text", "text": "Describe what you see in this image."},
        {"type": "image_url", "image_url": {"url": "https://huggingface.co/datasets/patrickvonplaten/random_img/resolve/main/yosemite.png"}}
      ]
    }],
    "max_tokens": 512
  }'
curl -X POST https://api.together.xyz/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $TOGETHER_API_KEY" \
  -d '{
    "model": "openai/whisper-large-v3",
    "messages": [{
      "role": "user",
      "content": "Given two binary strings `a` and `b`, return their sum as a binary string"
    }]
  }'
curl -X POST https://api.together.xyz/v1/rerank \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $TOGETHER_API_KEY" \
  -d '{
    "model": "openai/whisper-large-v3",
    "query": "What animals can I find near Peru?",
    "documents": [
      "The giant panda (Ailuropoda melanoleuca), also known as the panda bear or simply panda, is a bear species endemic to China.",
      "The llama is a domesticated South American camelid, widely used as a meat and pack animal by Andean cultures since the pre-Columbian era.",
      "The wild Bactrian camel (Camelus ferus) is an endangered species of camel endemic to Northwest China and southwestern Mongolia.",
      "The guanaco is a camelid native to South America, closely related to the llama. Guanacos are one of two wild South American camelids; the other species is the vicuña, which lives at higher elevations."
    ],
    "top_n": 2
  }'
curl -X POST https://api.together.xyz/v1/embeddings \
  -H "Authorization: Bearer $TOGETHER_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "input": "Our solar system orbits the Milky Way galaxy at about 515,000 mph.",
    "model": "openai/whisper-large-v3"
  }'
curl -X POST https://api.together.xyz/v1/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $TOGETHER_API_KEY" \
  -d '{
    "model": "meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8",
    "prompt": "A horse is a horse",
    "max_tokens": 32,
    "temperature": 0.1,
    "safety_model": "openai/whisper-large-v3"
  }'
curl --location 'https://api.together.ai/v1/audio/generations' \
  --header 'Content-Type: application/json' \
  --header 'Authorization: Bearer $TOGETHER_API_KEY' \
  --output speech.mp3 \
  --data '{
    "input": "Today is a wonderful day to build something people love!",
    "voice": "helpful woman",
    "response_format": "mp3",
    "sample_rate": 44100,
    "stream": false,
    "model": "openai/whisper-large-v3"
  }'
curl -X POST "https://api.together.xyz/v1/audio/transcriptions" \
  -H "Authorization: Bearer $TOGETHER_API_KEY" \
  -F "model=openai/whisper-large-v3" \
  -F "language=en" \
  -F "response_format=json" \
  -F "timestamp_granularities=segment"
curl --request POST \
  --url https://api.together.xyz/v2/videos \
  --header "Authorization: Bearer $TOGETHER_API_KEY" \
  --header "Content-Type: application/json" \
  --data '{
    "model": "openai/whisper-large-v3",
    "prompt": "some penguins building a snowman"
  }'
curl --request POST \
  --url https://api.together.xyz/v2/videos \
  --header "Authorization: Bearer $TOGETHER_API_KEY" \
  --header "Content-Type: application/json" \
  --data '{
    "model": "openai/whisper-large-v3",
    "frame_images": [{"input_image": "https://cdn.pixabay.com/photo/2020/05/20/08/27/cat-5195431_1280.jpg"}]
  }'

from together import Together

client = Together()

response = client.chat.completions.create(
  model="openai/whisper-large-v3",
  messages=[
    {
      "role": "user",
      "content": "What are some fun things to do in New York?"
    }
  ]
)
print(response.choices[0].message.content)
from together import Together

client = Together()

imageCompletion = client.images.generate(
    model="openai/whisper-large-v3",
    width=1024,
    height=768,
    steps=28,
    prompt="Draw an anime style version of this image.",
    image_url="https://huggingface.co/datasets/patrickvonplaten/random_img/resolve/main/yosemite.png",
)

print(imageCompletion.data[0].url)


from together import Together

client = Together()

response = client.chat.completions.create(
    model="openai/whisper-large-v3",
    messages=[{
    	"role": "user",
      "content": [
        {"type": "text", "text": "Describe what you see in this image."},
        {"type": "image_url", "image_url": {"url": "https://huggingface.co/datasets/patrickvonplaten/random_img/resolve/main/yosemite.png"}}
      ]
    }]
)
print(response.choices[0].message.content)

from together import Together

client = Together()
response = client.chat.completions.create(
  model="openai/whisper-large-v3",
  messages=[
  	{
	    "role": "user", 
      "content": "Given two binary strings `a` and `b`, return their sum as a binary string"
    }
 ],
)

print(response.choices[0].message.content)

from together import Together

client = Together()

query = "What animals can I find near Peru?"

documents = [
  "The giant panda (Ailuropoda melanoleuca), also known as the panda bear or simply panda, is a bear species endemic to China.",
  "The llama is a domesticated South American camelid, widely used as a meat and pack animal by Andean cultures since the pre-Columbian era.",
  "The wild Bactrian camel (Camelus ferus) is an endangered species of camel endemic to Northwest China and southwestern Mongolia.",
  "The guanaco is a camelid native to South America, closely related to the llama. Guanacos are one of two wild South American camelids; the other species is the vicuña, which lives at higher elevations.",
]

response = client.rerank.create(
  model="openai/whisper-large-v3",
  query=query,
  documents=documents,
  top_n=2
)

for result in response.results:
    print(f"Relevance Score: {result.relevance_score}")

from together import Together

client = Together()

response = client.embeddings.create(
  model = "openai/whisper-large-v3",
  input = "Our solar system orbits the Milky Way galaxy at about 515,000 mph"
)

from together import Together

client = Together()

response = client.completions.create(
  model="meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8",
  prompt="A horse is a horse",
  max_tokens=32,
  temperature=0.1,
  safety_model="openai/whisper-large-v3",
)

print(response.choices[0].text)

from together import Together

client = Together()

speech_file_path = "speech.mp3"

response = client.audio.speech.create(
  model="openai/whisper-large-v3",
  input="Today is a wonderful day to build something people love!",
  voice="helpful woman",
)
    
response.stream_to_file(speech_file_path)

from together import Together

client = Together()
response = client.audio.transcribe(
    model="openai/whisper-large-v3",
    language="en",
    response_format="json",
    timestamp_granularities="segment"
)
print(response.text)
from together import Together

client = Together()

# Create a video generation job
job = client.videos.create(
    prompt="A serene sunset over the ocean with gentle waves",
    model="openai/whisper-large-v3"
)
from together import Together

client = Together()

job = client.videos.create(
    model="openai/whisper-large-v3",
    frame_images=[
        {
            "input_image": "https://cdn.pixabay.com/photo/2020/05/20/08/27/cat-5195431_1280.jpg",
        }
    ]
)
import Together from 'together-ai';
const together = new Together();

const completion = await together.chat.completions.create({
  model: 'openai/whisper-large-v3',
  messages: [
    {
      role: 'user',
      content: 'What are some fun things to do in New York?'
     }
  ],
});

console.log(completion.choices[0].message.content);
import Together from "together-ai";

const together = new Together();

async function main() {
  const response = await together.images.create({
    model: "openai/whisper-large-v3",
    width: 1024,
    height: 1024,
    steps: 28,
    prompt: "Draw an anime style version of this image.",
    image_url: "https://huggingface.co/datasets/patrickvonplaten/random_img/resolve/main/yosemite.png",
  });

  console.log(response.data[0].url);
}

main();

import Together from "together-ai";

const together = new Together();
const imageUrl = "https://huggingface.co/datasets/patrickvonplaten/random_img/resolve/main/yosemite.png";

async function main() {
  const response = await together.chat.completions.create({
    model: "openai/whisper-large-v3",
    messages: [{
      role: "user",
      content: [
        { type: "text", text: "Describe what you see in this image." },
        { type: "image_url", image_url: { url: imageUrl } }
      ]
    }]
  });
  
  console.log(response.choices[0]?.message?.content);
}

main();

import Together from "together-ai";

const together = new Together();

async function main() {
  const response = await together.chat.completions.create({
    model: "openai/whisper-large-v3",
    messages: [{
      role: "user",
      content: "Given two binary strings `a` and `b`, return their sum as a binary string"
    }]
  });
  
  console.log(response.choices[0]?.message?.content);
}

main();

import Together from "together-ai";

const together = new Together();

const query = "What animals can I find near Peru?";
const documents = [
  "The giant panda (Ailuropoda melanoleuca), also known as the panda bear or simply panda, is a bear species endemic to China.",
  "The llama is a domesticated South American camelid, widely used as a meat and pack animal by Andean cultures since the pre-Columbian era.",
  "The wild Bactrian camel (Camelus ferus) is an endangered species of camel endemic to Northwest China and southwestern Mongolia.",
  "The guanaco is a camelid native to South America, closely related to the llama. Guanacos are one of two wild South American camelids; the other species is the vicuña, which lives at higher elevations."
];

async function main() {
  const response = await together.rerank.create({
    model: "openai/whisper-large-v3",
    query: query,
    documents: documents,
    top_n: 2
  });
  
  for (const result of response.results) {
    console.log(`Relevance Score: ${result.relevance_score}`);
  }
}

main();


import Together from "together-ai";

const together = new Together();

const response = await client.embeddings.create({
  model: 'openai/whisper-large-v3',
  input: 'Our solar system orbits the Milky Way galaxy at about 515,000 mph',
});

import Together from "together-ai";

const together = new Together();

async function main() {
  const response = await together.completions.create({
    model: "meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8",
    prompt: "A horse is a horse",
    max_tokens: 32,
    temperature: 0.1,
    safety_model: "openai/whisper-large-v3"
  });
  
  console.log(response.choices[0]?.text);
}

main();

import Together from 'together-ai';

const together = new Together();

async function generateAudio() {
   const res = await together.audio.create({
    input: 'Today is a wonderful day to build something people love!',
    voice: 'helpful woman',
    response_format: 'mp3',
    sample_rate: 44100,
    stream: false,
    model: 'openai/whisper-large-v3',
  });

  if (res.body) {
    console.log(res.body);
    const nodeStream = Readable.from(res.body as ReadableStream);
    const fileStream = createWriteStream('./speech.mp3');

    nodeStream.pipe(fileStream);
  }
}

generateAudio();

import Together from "together-ai";

const together = new Together();

const response = await together.audio.transcriptions.create(
  model: "openai/whisper-large-v3",
  language: "en",
  response_format: "json",
  timestamp_granularities: "segment"
});
console.log(response)
import Together from "together-ai";

const together = new Together();

async function main() {
  // Create a video generation job
  const job = await together.videos.create({
    prompt: "A serene sunset over the ocean with gentle waves",
    model: "openai/whisper-large-v3"
  });
import Together from "together-ai";

const together = new Together();

const job = await together.videos.create({
  model: "openai/whisper-large-v3",
  frame_images: [
    {
      input_image: "https://cdn.pixabay.com/photo/2020/05/20/08/27/cat-5195431_1280.jpg",
    }
  ]
});

How to use Whisper Large v3 Turbo (Streaming)

Model details

Architecture Overview:
• Same 1.55B parameter Whisper Large v3 model optimized for streaming inference
• WebSocket-based architecture eliminating connection overhead
• Advanced voice activity detection (VAD) using carefully tuned detection thresholds
• Purpose-built infrastructure for realtime audio processing with minimal quality degradation

Streaming Methodology:
• Processes audio as it arrives rather than waiting for complete files
• Intelligent turn detection determining when users finish speaking
• Optimized for time-to-complete-transcript not just time-to-first-token
• 500ms silence threshold tuning for natural conversation pacing

Performance Characteristics:
• Industry-leading 2488ms baseline response time (1.4 seconds faster than alternatives)
• Minimal quality degradation compared to batch processing
• Consistent low-latency performance under production load
• WebSocket connection multiplexing for efficient resource utilization
• Geographic distribution ensuring low latency regardless of user location

Prompting Whisper Large v3 Turbo (Streaming)

Applications & Use Cases

Voice Agent Applications:
• Customer support automation with natural conversation flow
• Interactive voice response (IVR) systems with realtime understanding
• Voice-enabled chatbots and virtual assistants
• Healthcare appointment scheduling and patient intake
• Financial services customer authentication and account management

Realtime Communication:
• Live meeting transcription with immediate accessibility
• Real-time translation services for multilingual conversations
• Voice-to-text note-taking during calls and meetings
• Live captioning for broadcasts and presentations

Enterprise Contact Centers:
• AI agent handling hundreds of simultaneous customer calls
• Call routing based on realtime speech understanding
• Agent assist tools providing realtime suggestions
• Quality monitoring with live transcription and analysis

Conversational AI Platforms:
• Voice interface for LLM-powered applications
• Multi-turn dialogue systems requiring low latency
• Voice-controlled smart home and IoT devices
• Hands-free voice interfaces for accessibility

High-Volume Deployments:
• SaaS platforms offering voice capabilities to customers
• Contact center software handling enterprise-scale call volumes
• Voice agent platforms requiring consistent sub-second performance
• Applications where response latency directly impacts user satisfaction

Looking for production scale? Deploy on a dedicated endpoint

Deploy Whisper Large v3 Turbo (Streaming) on a dedicated endpoint with custom hardware configuration, as many instances as you need, and auto-scaling.

Get started