Using Qwen3-Next-80B-A3B-Thinking on Vercel AI Gateway

Implementation guide · Qwen3 · Alibaba

Serverless

Open Source

Vercel AI Gateway exposes Qwen3-Next-80B-A3B-Thinking through model ID alibaba/qwen3-next-80b-a3b-thinking. Use the setup steps, sourced pricing, capabilities, and official provider links below to validate this route before deployment.

Last refreshed 2026-10-19. Next refresh: weekly.

Quick Start

1
Create an account at Vercel AI Gateway and generate an API key.
2
Use the Vercel AI Gateway SDK or REST API to call alibaba/qwen3-next-80b-a3b-thinking — see the documentation for request format.
3
You'll be billed $0.15/1M input, $1.20/1M output tokens. See full pricing.

API Portal Documentation Pricing Model Card

Code Examples

Install

pip install openai

API key

AI_GATEWAY_API_KEY

Model ID

alibaba/qwen3-next-80b-a3b-thinking

creator/model-name e.g. kwaipilot/kat-coder-pro-v2

import os
from openai import OpenAI

client = OpenAI(
    api_key=os.environ["AI_GATEWAY_API_KEY"],
    base_url="https://ai-gateway.vercel.sh/v1"
)
response = client.chat.completions.create(
    model="alibaba/qwen3-next-80b-a3b-thinking",
    messages=[{"role": "user", "content": "Hello"}]
)
print(response.choices[0].message.content)

Pricing on Vercel AI Gateway

Type	Price (per 1M)
Input tokens	$0.15
Output tokens	$1.20

Capabilities

Reasoning

About Qwen3-Next-80B-A3B-Thinking

Qwen3-Next-80B-A3B-Thinking is the thinking-mode variant of Alibaba Qwen's Qwen3-Next-80B-A3B, an 80B-parameter mixture-of-experts model with 3B active parameters per token and a hybrid Gated DeltaNet + Gated Attention architecture. It was announced on 2025-09-11 alongside the Instruct variant, with Apache-2.0 open weights on Hugging Face.

Full model details →

Model Specs

Released2025-09-11

Parameters80B-A3B

ArchitectureMixture of Experts

Vercel