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Qwen · Balanced

Qwen3 Max

Added Sep 5, 2025

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Use in the app

Qwen3 Max improves accuracy in coding and science, instruction following, and tool calling.

Input
Text
Output
Text
Discovery tier
Balanced

Pricing

USD per 1M tokens
Input
$1.20
Output
$6.00

Reference prices as published by the model provider. API example

Specifications

Context window
256K
Max output
32.8K

Side by side

Qwen3 Max compared

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

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Qwen3 MaxQwenThis modelKimi K2 0905MoonshotRemove
ProviderQwenMoonshot
Discovery tierBalancedOpen weights
AddedSep 5, 2025Sep 25, 2025
Limits
Context window256K262.14KBest
Max output32.77K100.35KBest
Average output—677 tokens
Pricing, USD per 1M tokens
Input$1.20$0.40Best
Output$6.00$1.80Best
Performance
Throughput—55.2 tok/s
Time to first token—3.2 s
Request success (24h)—100.0%
Benchmark indexes
Intelligence Index15.6Best15.3
Math Index80.7Best57.3
Capabilities
ToolsNoYes
Structured outputNoYes
Reasoning effort——

Public evaluations

Benchmarks

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

  • Qwen3 Max
  • Kimi K2 0905

Intelligence Index

  • Qwen3 Max15.6
  • Kimi K2 090515.3

Qwen3 Max: Better than 39% of 326 scored models

3.8Catalog models by score55.1

Indexes

  • Math Index

    Composite of the math evaluations

    • Qwen3 Max: 80.7Top
    • Kimi K2 0905: 57.3

Document reasoning

  • AA-LCRv1.1

    Reasoning across long documents

    • Qwen3 Max: 50.0%
    • Kimi K2 0905: 53.0%Top

Reasoning and knowledge

  • Humanity’s Last Exam

    Expert-level questions across academic fields

    • Qwen3 Max: 11.9%Top
    • Kimi K2 0905: 6.4%

  • GPQA Diamond

    Graduate-level science questions

    • Qwen3 Max: 76.4%
    • Kimi K2 0905: 76.7%Top

  • MMLU-Pro

    Multi-subject knowledge and reasoning

    • Qwen3 Max: 84.1%Top
    • Kimi K2 0905: 81.9%

  • IFBench

    Following precise output instructions

    • Qwen3 Max: 44.1%Top
    • Kimi K2 0905: 41.7%

Coding

  • LiveCodeBench

    Recent competitive programming problems

    • Qwen3 Max: 76.7%Top
    • Kimi K2 0905: 61.0%

Math

  • AIME 2025

    Competition mathematics, 2025 problems

    • Qwen3 Max: 80.7%Top
    • Kimi K2 0905: 57.3%

Legacy evaluations

  • Terminal-Bench Hard

    Earlier terminal task suite

    • Qwen3 Max: 20.5%
    • Kimi K2 0905: 23.5%Top

  • τ²-Bench Telecom

    Tool use in a customer-support simulation

    • Qwen3 Max: 74.3%Top
    • Kimi K2 0905: 73.4%

  • AA-LCR (unversioned)

    Long-context reasoning, earlier grading

    • Qwen3 Max: 50.0%
    • Kimi K2 0905: 53.0%Top

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

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

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