Models / QwenQwen / / Qwen3-Coder 480B A35B Instruct API
Qwen3-Coder 480B A35B Instruct API
480B-parameter MoE coding model with 35B active, 256K context, and agentic performance rivaling Claude Sonnet on complex development tasks.

This model is not currently supported on Together AI.
Visit our Models page to view all the latest models.
Qwen3-Coder 480B A35B Instruct 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": "Qwen/Qwen3-Coder-480B-A35B-Instruct-FP8",
"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-Coder-480B-A35B-Instruct-FP8",
"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-Coder-480B-A35B-Instruct-FP8",
"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-Coder-480B-A35B-Instruct-FP8",
"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-Coder-480B-A35B-Instruct-FP8",
"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-Coder-480B-A35B-Instruct-FP8"
}'
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-Coder-480B-A35B-Instruct-FP8"
}'
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-Coder-480B-A35B-Instruct-FP8"
}'
curl -X POST "https://api.together.xyz/v1/audio/transcriptions" \
-H "Authorization: Bearer $TOGETHER_API_KEY" \
-F "model=Qwen/Qwen3-Coder-480B-A35B-Instruct-FP8" \
-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-Coder-480B-A35B-Instruct-FP8",
"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-Coder-480B-A35B-Instruct-FP8",
"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-Coder-480B-A35B-Instruct-FP8",
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-Coder-480B-A35B-Instruct-FP8",
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-Coder-480B-A35B-Instruct-FP8",
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-Coder-480B-A35B-Instruct-FP8",
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-Coder-480B-A35B-Instruct-FP8",
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-Coder-480B-A35B-Instruct-FP8",
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-Coder-480B-A35B-Instruct-FP8",
)
print(response.choices[0].text)
from together import Together
client = Together()
speech_file_path = "speech.mp3"
response = client.audio.speech.create(
model="Qwen/Qwen3-Coder-480B-A35B-Instruct-FP8",
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-Coder-480B-A35B-Instruct-FP8",
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-Coder-480B-A35B-Instruct-FP8"
)
from together import Together
client = Together()
job = client.videos.create(
model="Qwen/Qwen3-Coder-480B-A35B-Instruct-FP8",
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-Coder-480B-A35B-Instruct-FP8',
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-Coder-480B-A35B-Instruct-FP8",
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-Coder-480B-A35B-Instruct-FP8",
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-Coder-480B-A35B-Instruct-FP8",
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-Coder-480B-A35B-Instruct-FP8",
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-Coder-480B-A35B-Instruct-FP8',
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-Coder-480B-A35B-Instruct-FP8"
});
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-Coder-480B-A35B-Instruct-FP8',
});
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-Coder-480B-A35B-Instruct-FP8",
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-Coder-480B-A35B-Instruct-FP8"
});
import Together from "together-ai";
const together = new Together();
const job = await together.videos.create({
model: "Qwen/Qwen3-Coder-480B-A35B-Instruct-FP8",
frame_images: [
{
input_image: "https://cdn.pixabay.com/photo/2020/05/20/08/27/cat-5195431_1280.jpg",
}
]
});
How to use Qwen3-Coder 480B A35B Instruct
Model details
Architecture Overview:
• Mixture-of-Experts architecture with 480B total parameters and 35B active parameters
• Native 256K token context window, extendable to 1M tokens using Yarn interpolation
• Advanced grouped query attention mechanism for memory efficiency
Training Methodology:
• Trained on 7.5 trillion high-quality tokens with 70% code ratio across 358 programming languages
• Sophisticated post-training with supervised fine-tuning and reinforcement learning workflows
• Constitutional AI training for safety alignment and responsible code generation
Performance Characteristics:
• State-of-the-art SWE-bench Verified results at 69.6%, comparable to Claude Sonnet 4
• Exceptional agentic coding capabilities with 37.5 score on complex autonomous workflows
• Superior tool use and browser automation performance for development tasks
Prompting Qwen3-Coder 480B A35B Instruct
Applications & Use Cases
Agentic Development Workflows:
• Autonomous software engineering tasks spanning multiple files and services
• Legacy system modernization with comprehensive analysis and migration planning
• End-to-end feature development across backend APIs, frontend components, & databases
Advanced Code Generation:
• Repository-scale refactoring and architectural improvements
• Complex debugging and root cause analysis across distributed systems
• Code completion and fill-in-the-middle for development environments
Enterprise Integration:
• Custom development workflows with fine-tuning capabilities
• Production deployment automation and CI/CD pipeline generation
• Code review assistance and security vulnerability identification
Developer Tooling:
• Integration with platforms like Qwen Code, CLINE, and VS Code extensions
• Batch processing for large codebase analysis and transformation
• Real-time coding assistance with context-aware suggestions
Model Provider:
Qwen
Type:
Code
Variant:
Parameters:
480B (35B activated)
Deployment:
Serverless
On-Demand Dedicated
Monthly Reserved
Quantization
Context length:
256K
Resolution / Duration
Pricing:
$2.00 Per 1M Tokens
Check pricing
Run in playground
Deploy model
Quickstart docs
Quickstart docs
Serverless
Looking for production scale? Deploy on a dedicated endpoint
Deploy Qwen3-Coder 480B A35B Instruct on a dedicated endpoint with custom hardware configuration, as many instances as you need, and auto-scaling.
