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Qwen · Efficient

Qwen3.6 Flash

Added Apr 17, 2026

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Use in the app

Qwen3.6 Flash is Alibaba's fast native vision-language model in the Qwen 3.6 family. It improves over 3.5 Flash with stronger coding/agent performance and better spatial intelligence, including object localization and detection.

  • Vision
  • Video input
Input
Text, Images, Video
Output
Text
Discovery tier
Efficient

Pricing

USD per 1M tokens
Input
$0.19
Output
$1.16
Cache read
$0.02
Cache write
$0.24

Reference prices as published by the model provider. API example

Specifications

Context window
991.8K
Max output
65.5K

Side by side

Qwen3.6 Flash compared

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

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Qwen3.6 FlashQwenThis modelGPT 5.6 LunaOpenAIRemove
ProviderQwenOpenAI
Discovery tierEfficientEfficient
AddedApr 17, 2026Jul 9, 2026
Limits
Context window991.81K1.05MBest
Max output65.54K128KBest
Average output—281 tokens
Pricing, USD per 1M tokens
Input$0.19Best$0.20
Output$1.16Best$1.20
Cache read$0.02$0.02
Cache write$0.24Best$0.25
Performance
Throughput—545.5 tok/s
Time to first token—10.8 s
Request success (24h)100.0%Best99.9%
Benchmark indexes
Intelligence Index—37.3
Coding Index—71.4
Capabilities
ReasoningNoYes
ToolsNoYes
VisionYesYes
Structured outputNoYes
PDF inputNoYes
Video inputYesNo
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.

  • Qwen3.6 Flash
  • GPT 5.6 Luna

Intelligence Index

  • Qwen3.6 Flash—
  • GPT 5.6 Luna37.3
3.8Catalog models by score55.1

Indexes

  • Coding Index

    Composite of the coding evaluations

    • Qwen3.6 Flash: —
    • GPT 5.6 Luna: 71.4

Agentic work

  • AutomationBench-AA

    Workflow automation, penalized for guardrail violations

    • Qwen3.6 Flash: —
    • GPT 5.6 Luna: 50.2%

  • AutomationBench-AA tasks completed

    Workflows finished end to end without a guardrail violation

    • Qwen3.6 Flash: —
    • GPT 5.6 Luna: 18.6%

  • AA-Briefcasev1.1

    Agentic knowledge work, rated head to head

    • Qwen3.6 Flash: —
    • GPT 5.6 Luna: 1,339 Elo

  • GDPval-AAv2.1

    Economically valuable occupational tasks, rated head to head

    • Qwen3.6 Flash: —
    • GPT 5.6 Luna: 1,460 Elo

Document reasoning

  • GDP.pdf

    Professional reasoning over PDF documents, all-pass rate

    • Qwen3.6 Flash: —
    • GPT 5.6 Luna: 24.0%

  • AA-LCRv1.1

    Reasoning across long documents

    • Qwen3.6 Flash: —
    • GPT 5.6 Luna: 83.7%

  • MLCR-AA

    Long-context reasoning over medical records

    • Qwen3.6 Flash: —
    • GPT 5.6 Luna: 20.0%

Reasoning and knowledge

  • Humanity’s Last Exam

    Expert-level questions across academic fields

    • Qwen3.6 Flash: —
    • GPT 5.6 Luna: 39.5%

  • GPQA Diamond

    Graduate-level science questions

    • Qwen3.6 Flash: —
    • GPT 5.6 Luna: 91.1%

Coding

  • Terminal-Benchv4.0

    Practical software engineering in a terminal

    • Qwen3.6 Flash: —
    • GPT 5.6 Luna: 11.6%

  • SciCode

    Scientific computing in Python

    • Qwen3.6 Flash: —
    • GPT 5.6 Luna: 53.6%

Legacy evaluations

  • AA-LCR (unversioned)

    Long-context reasoning, earlier grading

    • Qwen3.6 Flash: —
    • GPT 5.6 Luna: 83.7%

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.

Request success (24h)
100.0%
Reliable
Hourly request success · last 72 hoursLowest hour 100.0%
  • 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/qwen3.6-flash",
    "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/qwen3.6-flash",
    messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)

Qwen

Other Qwen models, starting with the same family.