Qwen · Balanced

Qwen3.7 Plus Thinking

Added Jun 1, 2026

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.

Limits
	Qwen3.7 Plus ThinkingQwenThis model	Qwen3.5 PlusQwenRemove
Provider	Qwen	Qwen
Discovery tier	Balanced	Balanced
Added	Jun 1, 2026	Feb 16, 2026
Context window	983.62K	983.62K
Max output	65.54K	65.54K
Average output	—	141 tokens
Pricing, USD per 1M tokens
Input	$0.40	$0.40
Output	$1.60Best	$2.40
Cache read	$0.08	$0.04Best
Cache write	$0.50	—
Capabilities
Reasoning	Yes	No
Tools	Yes	No
Vision	Yes	Yes
Video input	Yes	Yes
Reasoning effort	none, 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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