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Models / QwenQwen /  / Qwen3-Next-80B-A3B-Thinking API

Qwen3-Next-80B-A3B-Thinking API

Next-generation reasoning model with extreme efficiency

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API Usage
How to use Qwen3-Next-80B-A3B-ThinkingModel CardPrompting Qwen3-Next-80B-A3B-ThinkingApplications & Use Cases

This model is not currently supported on Together AI.

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Advanced Reasoning Engine:
Qwen3-Next Thinking features the same highly sparse MoE architecture but specialized for complex reasoning tasks. Supports only thinking mode with automatic tag inclusion, delivering exceptional analytical performance while maintaining extreme efficiency with 10x+ higher throughput on long contexts and may generate longer thinking content than predecessors.

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Qwen3-Next-80B-A3B-Thinking API Usage

Endpoint

Qwen/Qwen3-Next-80B-A3B-Thinking
cURL
Python
TypeScript
curl -X POST "https://api.together.xyz/v1/chat/completions" \
  -H "Authorization: Bearer $TOGETHER_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "Qwen/Qwen3-Next-80B-A3B-Thinking",
    "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": "Qwen/Qwen3-Next-80B-A3B-Thinking",
    "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": "Qwen/Qwen3-Next-80B-A3B-Thinking",
    "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": "Qwen/Qwen3-Next-80B-A3B-Thinking",
    "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": "Qwen/Qwen3-Next-80B-A3B-Thinking",
    "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": "Qwen/Qwen3-Next-80B-A3B-Thinking"
  }'

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": "Qwen/Qwen3-Next-80B-A3B-Thinking"
  }'

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": "Qwen/Qwen3-Next-80B-A3B-Thinking"
  }'

curl -X POST "https://api.together.xyz/v1/audio/transcriptions" \
  -H "Authorization: Bearer $TOGETHER_API_KEY" \
  -F "model=Qwen/Qwen3-Next-80B-A3B-Thinking" \
  -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": "Qwen/Qwen3-Next-80B-A3B-Thinking",
    "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": "Qwen/Qwen3-Next-80B-A3B-Thinking",
    "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="Qwen/Qwen3-Next-80B-A3B-Thinking",
  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="Qwen/Qwen3-Next-80B-A3B-Thinking",
    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="Qwen/Qwen3-Next-80B-A3B-Thinking",
    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="Qwen/Qwen3-Next-80B-A3B-Thinking",
  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="Qwen/Qwen3-Next-80B-A3B-Thinking",
  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 = "Qwen/Qwen3-Next-80B-A3B-Thinking",
  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="Qwen/Qwen3-Next-80B-A3B-Thinking",
)

print(response.choices[0].text)


from together import Together

client = Together()

speech_file_path = "speech.mp3"

response = client.audio.speech.create(
  model="Qwen/Qwen3-Next-80B-A3B-Thinking",
  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="Qwen/Qwen3-Next-80B-A3B-Thinking",
    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="Qwen/Qwen3-Next-80B-A3B-Thinking"
)

from together import Together

client = Together()

job = client.videos.create(
    model="Qwen/Qwen3-Next-80B-A3B-Thinking",
    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: 'Qwen/Qwen3-Next-80B-A3B-Thinking',
  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: "Qwen/Qwen3-Next-80B-A3B-Thinking",
    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: "Qwen/Qwen3-Next-80B-A3B-Thinking",
    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: "Qwen/Qwen3-Next-80B-A3B-Thinking",
    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: "Qwen/Qwen3-Next-80B-A3B-Thinking",
    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: 'Qwen/Qwen3-Next-80B-A3B-Thinking',
  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: "Qwen/Qwen3-Next-80B-A3B-Thinking"
  });
  
  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: 'Qwen/Qwen3-Next-80B-A3B-Thinking',
  });

  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: "Qwen/Qwen3-Next-80B-A3B-Thinking",
  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: "Qwen/Qwen3-Next-80B-A3B-Thinking"
  });

import Together from "together-ai";

const together = new Together();

const job = await together.videos.create({
  model: "Qwen/Qwen3-Next-80B-A3B-Thinking",
  frame_images: [
    {
      input_image: "https://cdn.pixabay.com/photo/2020/05/20/08/27/cat-5195431_1280.jpg",
    }
  ]
});

How to use Qwen3-Next-80B-A3B-Thinking

Model details

Architecture Overview:
• 48 layers with 2048 hidden dimension and hybrid layout pattern
• 512 total experts with 10 activated and 1 shared expert per MoE layer
• Multi-token prediction mechanism for faster analytical processing

Thinking Mode Optimization:
• Supports only thinking mode with automatic tag inclusion
• Specialized post-training for complex reasoning chains on 15T tokens
• May generate longer thinking content for comprehensive analysis

Performance Characteristics:
• 262K native context length, extensible to 1M tokens with YaRN scaling
• More than 10x higher throughput on contexts over 32K tokens
• SGLang and vLLM deployment support with Multi-Token Prediction

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Prompting Qwen3-Next-80B-A3B-Thinking

Applications & Use Cases

Research & Analysis:
• Scientific research and hypothesis generation with detailed reasoning
• Complex data analysis and pattern recognition
• Academic writing and literature review with analytical depth

Problem Solving:
• Engineering design challenges requiring multi-step analysis
• Strategic business planning and decision-making support
• Mathematical problem solving and proof generation

Professional Applications:
• Legal case analysis and argument construction
• Medical diagnosis assistance with reasoning transparency
• Financial modeling and risk assessment with detailed rationale

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Model Provider:

Qwen

Type:

Chat

Variant:

Parameters:

80B (3B activated)

Deployment:

✔ Serverless

✔ On-Demand Dedicated

✔ Monthly Reserved

Quantization

Context length:

262K

Resolution / Duration

Pricing:

Check pricing

Run in playground

Deploy model

Deploy model

Quickstart docs

Quickstart docs

Serverless

On-Demand Dedicated

Looking for production scale? Deploy on a dedicated endpoint

Deploy Qwen3-Next-80B-A3B-Thinking on a dedicated endpoint with custom hardware configuration, as many instances as you need, and auto-scaling.

Get started
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