Large Language Modelqwen3.8-max

Qwen 3.8 Max

2.4T MoE Flagship

Alibaba 2.4-trillion-parameter MoE flagship model with native 1M context, state-of-the-art autonomous coding, and comprehensive multimodal reasoning. Supports deterministic 0902 snapshot alias.

AvailableMoE TransformerProprietary

Params

2.4T MoE 1M

Context

Max Output

32K

API Surface/v1/chat/completions

Capabilities & Performance

1,000,000 token seamless document and video context comprehension
Starting at $1.936/M input, $5.807/M output with 10% SLA assurance
Fully compatible with pinned enterprise snapshot alias qwen3.8-max-0902

Transparent Pricing

Lane	Public Rate	Cached
Realtime API	$1.94 / $5.81	$0.242

Prices per 1M tokens. Cached prompt rate applies on prefix hits.

100% OpenAI-Compatible Code

Drop-in API Examples

Get API Key

Python (OpenAI SDK)

from openai import OpenAI

client = OpenAI(
    base_url="https://api.batchin.tech/v1",
    api_key="BATCHIN_API_KEY"
)

resp = client.chat.completions.create(
    model="qwen3.8-max",
    messages=[{"role": "user", "content": "Benchmark system architecture performance and cost profile."}]
)

print(resp.choices[0].message.content)

JavaScript / Node.js

import OpenAI from "openai";

const client = new OpenAI({
  baseURL: "https://api.batchin.tech/v1",
  apiKey: process.env.BATCHIN_API_KEY,
});

const resp = await client.chat.completions.create({
  model: "qwen3.8-max",
  messages: [{ role: "user", content: "Benchmark system architecture performance and cost profile." }],
});

console.log(resp.choices[0]?.message?.content);

cURL / Shell

curl https://api.batchin.tech/v1/chat/completions \
  -H "Authorization: Bearer $BATCHIN_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "qwen3.8-max",
    "messages": [{"role":"user","content":"Benchmark system architecture performance and cost profile."}]
  }'

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