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Qwen3.7 Flash Thinking

Added Jul 25, 2026

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Use in the app

Qwen3.7 Flash with thinking enabled for deeper multimodal reasoning, coding, search and computer-use agents, spatial reasoning, and multi-step task execution.

  • Reasoning
  • Tools
  • Vision
  • Structured output
  • Video input
Input
Text, Images, Video
Output
Text
Reasoning effort
none · high
Discovery tier
Efficient

Pricing

USD per 1M tokens
Input
$0.03
Output
$0.13
Cache read
$0.006
Cache write
$0.038

Reference prices as published by the model provider. API example

Specifications

Context window
983.6K
Max output
65.5K

Side by side

Qwen3.7 Flash Thinking compared

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

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Qwen3.7 Flash ThinkingQwenThis modelSolar Pro 4upstageRemove
ProviderQwenupstage
Discovery tierEfficientEfficient
AddedJul 25, 2026Aug 11, 2026
Limits
Context window983.62KBest524.29K
Max output65.54K131.07KBest
Average output—546 tokens
Pricing, USD per 1M tokens
Input$0.03$0.03
Output$0.13$0.12Best
Cache read$0.006$0.006
Cache write$0.038—
Performance
Throughput—118.2 tok/s
Time to first token—3.8 s
Request success (24h)100.0%Best99.9%
Benchmark indexes
Intelligence Index—26.6
Capabilities
ReasoningYesNo
ToolsYesYes
VisionYesNo
Structured outputYesYes
Video inputYesNo
Reasoning effortnone, high—

Public evaluations

Benchmarks

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

  • Qwen3.7 Flash Thinking
  • Solar Pro 4

Intelligence Index

  • Qwen3.7 Flash Thinking—
  • Solar Pro 426.6
3.8Catalog models by score55.1

Agentic work

  • AutomationBench-AA

    Workflow automation, penalized for guardrail violations

    • Qwen3.7 Flash Thinking: —
    • Solar Pro 4: 13.6%

  • AutomationBench-AA tasks completed

    Workflows finished end to end without a guardrail violation

    • Qwen3.7 Flash Thinking: —
    • Solar Pro 4: 2.4%

  • AA-Briefcasev1.1

    Agentic knowledge work, rated head to head

    • Qwen3.7 Flash Thinking: —
    • Solar Pro 4: 1,093 Elo

  • GDPval-AAv2.1

    Economically valuable occupational tasks, rated head to head

    • Qwen3.7 Flash Thinking: —
    • Solar Pro 4: 1,106 Elo

Document reasoning

  • GDP.pdf

    Professional reasoning over PDF documents, all-pass rate

    • Qwen3.7 Flash Thinking: —
    • Solar Pro 4: 7.0%

  • AA-LCRv1.1

    Reasoning across long documents

    • Qwen3.7 Flash Thinking: —
    • Solar Pro 4: 70.7%

Reasoning and knowledge

  • Humanity’s Last Exam

    Expert-level questions across academic fields

    • Qwen3.7 Flash Thinking: —
    • Solar Pro 4: 29.8%

  • GPQA Diamond

    Graduate-level science questions

    • Qwen3.7 Flash Thinking: —
    • Solar Pro 4: 89.1%

Coding

  • Terminal-Benchv4.0

    Practical software engineering in a terminal

    • Qwen3.7 Flash Thinking: —
    • Solar Pro 4: 0.0%

  • SciCode

    Scientific computing in Python

    • Qwen3.7 Flash Thinking: —
    • Solar Pro 4: 48.0%

Legacy evaluations

  • AA-LCR (unversioned)

    Long-context reasoning, earlier grading

    • Qwen3.7 Flash Thinking: —
    • Solar Pro 4: 70.7%

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
25.8%
About $0.0238 per 1M input tokens with caching
Request success (24h)
100.0%
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 73.9%
  • 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/qwen3.7-flash:thinking",
    "reasoning_effort": "none",
    "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/qwen3.7-flash:thinking",
    messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)

Qwen

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