Qwen 3.8 Max pricing for data extraction

Quick start

Call Qwen 3.8 Max with the OpenAI Python SDK pointed at DashScope:

import os
from openai import OpenAI

client = OpenAI(
    base_url="https://dashscope.aliyuncs.com/compatible-mode/v1",
    api_key=os.environ["DASHSCOPE_API_KEY"],
)
response = client.chat.completions.create(
    model="qwen3.8-max",
    max_tokens=1000,
    messages=[{"role": "user", "content": "Your prompt here"}]
)
# Cost: ~$0.0140 per call at standard rates
# Input:  $2.00/MTok
# Output: $6.00/MTok

How Qwen 3.8 Max compares on cost

Per-call cost for all models scoring 50+ on data extraction benchmarks. Hover for details.

Cheapest viable option: Gemini 3 Flash at $0.005000/call (64% less, 86/100 quality).

What drives data extraction cost

Extraction is input-heavy and output-light (the raw document goes in, structured fields come out), which makes it one of the cheapest tasks per unit of value on this list. Output is small enough that output pricing is nearly irrelevant. Cost tracks document size, so the lever is sending only the pages that contain the fields you want.

For Qwen 3.8 Max specifically, that means output tokens cost 3.0x more than input, at $6.00 vs $2.00 per MTok. At this use case’s 4,000/1,000 token split, output accounts for 43% of the $0.0140 per-call cost.

Qwen 3.8 Max quality benchmarks for data extraction

Benchmark data for data extraction is pending for Qwen 3.8 Max. Test against your own evaluation suite before moving to production.

Benchmark data is not yet available for Qwen 3.8 Max. We recommend testing against your own evaluation criteria.

About Qwen 3.8 Max

Prices from help.aliyun.com/en/model-studio (qwen3.8-max, read 2026-10-11). Cache hit: $0.25/MTok input. Not yet benchmarked, so never recommended.

Other models from Alibaba (Qwen)

You can compare Qwen 3.8 Max head-to-head against any other model on our model comparison pages, or track how pricing has changed over time on the pricing history tracker.

Frequently asked questions