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Qwen · Efficient

Qwen Long 10M

Added Aug 1, 2024

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Use in the app

Alibaba's huge context window model. Takes in up to 10 million tokens, which is equivalent to dozens of books.

  • PDF input
Input
Text
Output
Text
Discovery tier
Efficient

Pricing

USD per 1M tokens
Input
$0.10
Output
$0.41

Reference prices as published by the model provider. API example

Specifications

Context window
10M
Max output
8.2K

Side by side

Qwen Long 10M compared

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

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Qwen Long 10MQwenThis modelGPT 6 LunaOpenAIRemove
ProviderQwenOpenAI
Discovery tierEfficientEfficient
AddedAug 1, 2024Sep 22, 2026
Limits
Context window10MBest1.05M
Max output8.19K128KBest
Average output—120 tokens
Pricing, USD per 1M tokens
Input$0.10$0.10Best
Output$0.41Best$0.50
Cache read—$0.01
Cache write—$0.13
Performance
Throughput—301.2 tok/s
Time to first token—4.1 s
Request success (24h)—99.7%
Benchmark indexes
Intelligence Index—29.9
Capabilities
ReasoningNoYes
ToolsNoYes
VisionNoYes
Structured outputNoYes
PDF inputYesYes
Reasoning effort—none, low, medium, high, xhigh, max

Public evaluations

Benchmarks

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

  • Qwen Long 10M
  • GPT 6 Luna

Intelligence Index

  • Qwen Long 10M—
  • GPT 6 Luna29.9
3.8Catalog models by score55.1

Agentic work

  • AutomationBench-AA

    Workflow automation, penalized for guardrail violations

    • Qwen Long 10M: —
    • GPT 6 Luna: 40.5%

  • AutomationBench-AA tasks completed

    Workflows finished end to end without a guardrail violation

    • Qwen Long 10M: —
    • GPT 6 Luna: 10.2%

  • AA-Briefcasev1.1

    Agentic knowledge work, rated head to head

    • Qwen Long 10M: —
    • GPT 6 Luna: 1,097 Elo

  • GDPval-AAv2.1

    Economically valuable occupational tasks, rated head to head

    • Qwen Long 10M: —
    • GPT 6 Luna: 1,263 Elo

Document reasoning

  • GDP.pdf

    Professional reasoning over PDF documents, all-pass rate

    • Qwen Long 10M: —
    • GPT 6 Luna: 13.8%

  • AA-LCRv1.1

    Reasoning across long documents

    • Qwen Long 10M: —
    • GPT 6 Luna: 78.3%

  • MLCR-AA

    Long-context reasoning over medical records

    • Qwen Long 10M: —
    • GPT 6 Luna: 18.3%

Reasoning and knowledge

  • Humanity’s Last Exam

    Expert-level questions across academic fields

    • Qwen Long 10M: —
    • GPT 6 Luna: 28.3%

Coding

  • Terminal-Benchv4.0

    Practical software engineering in a terminal

    • Qwen Long 10M: —
    • GPT 6 Luna: 2.5%

  • SciCode

    Scientific computing in Python

    • Qwen Long 10M: —
    • GPT 6 Luna: 50.9%

Legacy evaluations

  • AA-LCR (unversioned)

    Long-context reasoning, earlier grading

    • Qwen Long 10M: —
    • GPT 6 Luna: 78.3%

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

Qwen

Other Qwen models, starting with the same family.