Qwen3 Next 80B A3B Instruct
qwen/qwen3-next-80b-a3b-instruct
Qwen3-Next uses a highly sparse MoE design: 80B total parameters, but only ~3B activated per inference step. Experiments show that, with global load balancing, increasing total expert parameters while keeping activated experts fixed steadily reduces training loss.Compared to Qwen3’s MoE (128 total experts, 8 routed), Qwen3-Next expands to 512 total experts, combining 10 routed experts + 1 shared expert — maximizing resource usage without hurting performance.
The Qwen3-Next-80B-A3B-Instruct performs comparably to our flagship model Qwen3-235B-A22B-Instruct-2507, and shows clear advantages in tasks requiring ultra-long context (up to 256K tokens).
Features
Serverless API
Docs
qwen/qwen3-next-80b-a3b-instruct is available via Novita's serverless API, where you pay per token. There are several ways to call the API, including OpenAI-compatible endpoints with exceptional reasoning performance.
On-demand Deployments
Docs
On-demand deployments allow you to use qwen/qwen3-next-80b-a3b-instruct on dedicated GPUs with high-performance serving stack with high reliability and no rate limits.
Available Serverless
Run queries immediately, pay only for usage
Input$0.15 / M Tokens
Output$1.5 / M Tokens
Use the following code examples to integrate with our API:
1from openai import OpenAI
2
3client = OpenAI(
4 api_key="<Your API Key>",
5 base_url="https://api.novita.ai/openai"
6)
7
8response = client.chat.completions.create(
9 model="qwen/qwen3-next-80b-a3b-instruct",
10 messages=[
11 {"role": "system", "content": "You are a helpful assistant."},
12 {"role": "user", "content": "Hello, how are you?"}
13 ],
14 max_tokens=32768,
15 temperature=0.7
16)
17
18print(response.choices[0].message.content)Info
Provider
Qwen
Quantization
bf16
Supported Functionality
Context Length
131072
Max Output
32768
Serverless
Supported
Function Calling
Supported
Structured Output
Supported
Reasoning
Supported
Anthropic API
Supported
Input Capabilities
text
Output Capabilities
text