NOUMENOpen app
NOUMEN

Qwen · Frontier

Qwen3.8 Max 0902

Added Sep 2, 2026

Compare models

Choose up to 3 models to compare.1 of 3 chosen

Loading models…

Use in the app

Qwen3.8 Max 0902 is Alibaba's September 2 checkpoint of its flagship Qwen3.8 Max model for coding, knowledge work, data analysis, and long-running agent workflows. It supports text, image, video, PDF input, selectable thinking, 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
none · 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
991.8K
Max output
131.1K

Side by side

Qwen3.8 Max 0902 compared

Specifications, prices, speed and benchmark scores next to each other. Benchmarks below show every compared model too.

Compare models

Choose up to 3 models to compare.1 of 3 chosen

Loading models…

Qwen3.8 Max 0902QwenThis modelGemini 4 ArgonGoogleRemove
ProviderQwenGoogle
Discovery tierFrontierFrontier
AddedSep 2, 2026Oct 13, 2026
Limits
Context window991.81K1.05MBest
Max output131.07KBest65.54K
Average output—1.6K tokens
Pricing, USD per 1M tokens
Input$2.00$2.00
Output$6.00Best$10.00
Cache read$0.25$0.10Best
Cache write$2.50$0.19Best
Performance
Throughput—106.6 tok/s
Time to first token—10.0 s
Request success (24h)97.3%98.6%Best
Benchmark indexes
Intelligence Index—52.6
Capabilities
ReasoningYesYes
ToolsYesYes
VisionYesYes
Structured outputYesYes
PDF inputYesYes
Audio inputNoYes
Video inputYesYes
Reasoning effortnone, low, medium, high, maxlow, medium, high

Public evaluations

Benchmarks

Independent evaluation results, with how each score ranks among the models in the Noumen catalog.

  • Qwen3.8 Max 0902
  • Gemini 4 Argon

Intelligence Index

  • Qwen3.8 Max 0902—
  • Gemini 4 Argon52.6
3.8Catalog models by score55.1

Agentic work

  • AutomationBench-AA

    Workflow automation, penalized for guardrail violations

    • Qwen3.8 Max 0902: —
    • Gemini 4 Argon: 77.5%

  • AutomationBench-AA tasks completed

    Workflows finished end to end without a guardrail violation

    • Qwen3.8 Max 0902: —
    • Gemini 4 Argon: 53.1%

  • Harvey LAB-AAv1.1

    Legal tasks passed in full, with no material hallucination

    • Qwen3.8 Max 0902: —
    • Gemini 4 Argon: 3.9%

  • AA-Briefcasev1.1

    Agentic knowledge work, rated head to head

    • Qwen3.8 Max 0902: —
    • Gemini 4 Argon: 1,486 Elo

  • GDPval-AAv2.1

    Economically valuable occupational tasks, rated head to head

    • Qwen3.8 Max 0902: —
    • Gemini 4 Argon: 1,624 Elo

Document reasoning

  • GDP.pdf

    Professional reasoning over PDF documents, all-pass rate

    • Qwen3.8 Max 0902: —
    • Gemini 4 Argon: 21.8%

  • AA-LCRv1.1

    Reasoning across long documents

    • Qwen3.8 Max 0902: —
    • Gemini 4 Argon: 79.7%

  • MLCR-AA

    Long-context reasoning over medical records

    • Qwen3.8 Max 0902: —
    • Gemini 4 Argon: 13.9%

Reasoning and knowledge

  • Humanity’s Last Exam

    Expert-level questions across academic fields

    • Qwen3.8 Max 0902: —
    • Gemini 4 Argon: 57.1%

Coding

  • Terminal-Benchv4.0

    Practical software engineering in a terminal

    • Qwen3.8 Max 0902: —
    • Gemini 4 Argon: 57.1%

  • SciCode

    Scientific computing in Python

    • Qwen3.8 Max 0902: —
    • Gemini 4 Argon: 61.8%

Legacy evaluations

  • AA-LCR (unversioned)

    Long-context reasoning, earlier grading

    • Qwen3.8 Max 0902: —
    • Gemini 4 Argon: 79.7%

Scores from Artificial Analysis, updated Oct 26, 2026. Artificial Analysis

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
88.0%
About $0.46 per 1M input tokens with caching
Request success (24h)
97.4%
Reliable

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 84.8%
  • 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-0902",
    "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-0902",
    messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)

Qwen

Other Qwen models, starting with the same family.