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Qwen · Balanced

Qwen3.7 Plus Thinking

Added Jun 1, 2026

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Use in the app

Qwen3.7 Plus with thinking mode enabled for deeper multimodal reasoning, coding, tool use, screen reading, and productivity workflows.

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

Pricing

USD per 1M tokens
Input
$0.40
Output
$1.60
Cache read
$0.08
Cache write
$0.50

Reference prices as published by the model provider. API example

Specifications

Context window
983.6K
Max output
65.5K

Side by side

Qwen3.7 Plus 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 Plus ThinkingQwenThis modelDoubao 1.5 Vision Pro 32kdoubaoRemove
ProviderQwendoubao
Discovery tierBalancedBalanced
AddedJun 1, 2026Nov 20, 2024
Limits
Context window983.62KBest32K
Max output65.54KBest8.19K
Pricing, USD per 1M tokens
Input$0.40Best$0.46
Output$1.60$1.38Best
Cache read$0.08—
Cache write$0.50—
Capabilities
ReasoningYesNo
ToolsYesNo
VisionYesYes
Video inputYesNo
Reasoning effortnone, high—

Public evaluations

Benchmarks

There are no public benchmark results for these models yet.

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
0.0%
About $0.40 per 1M input tokens with caching

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.

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

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