Qwen · Frontier

Qwen3.8 Max Thinking

Added Aug 3, 2026

Qwen3.8 Max Thinking enables generation-time reasoning for deeper coding, knowledge work, data analysis, and long-running agent workflows. It supports text, image, video, PDF input, tool calling, structured output, and a near-million-token context window.

Reasoning
Tools
Vision
Structured output
PDF input
Video input

Input: Text, Images, Video
Output: Text
Reasoning effort: low · medium · high · max
Discovery tier: Frontier

Pricing

USD per 1M tokens

Input: $2.00
Output: $6.00
Cache read: $0.25
Cache write: $2.50

Reference prices as published by the model provider. API example

Specifications

Context window: 991K
Max output: 131.1K

Side by side

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TryKimi K3.1 Pro Gemini 4 Argon GPT 6.1 Sol All 3

Public evaluations

Benchmarks

There are no public benchmark results for Qwen3.8 Max Thinking yet.

Live routing data

Performance and reliability

Recent averages across requests routed for this model. Your own speed depends on prompt length, reasoning effort and load.

Prompt cache hits: 96.2%; About $0.32 per 1M input tokens with caching
Request success (24h): 89.9%; Unstable

Cache hits are the share of input tokens recently served from a prompt cache across all requests. They are not a forecast of your own hit rate.

Hourly request success · last 72 hoursLowest hour 26.4%

Healthy (98% or more)
Degraded (90–98%)
Down (under 90%)
No requests

Developers

Use it through the API

Noumen’s API is OpenAI-compatible: any Chat Completions client works with a base URL and a key.

Read the quickstart

curl https://www.noumen.xyz/api/v1/chat/completions \
  -H "Authorization: Bearer $NOUMEN_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "qwen/qwen3.8-max:thinking",
    "reasoning_effort": "medium",
    "messages": [{ "role": "user", "content": "Explain this stack trace." }]
  }'

import os
from openai import OpenAI

client = OpenAI(base_url="https://www.noumen.xyz/api/v1", api_key=os.environ["NOUMEN_API_KEY"])
reply = client.chat.completions.create(
    model="qwen/qwen3.8-max:thinking",
    messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)

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