NOUMENOpen app
NOUMEN

Qwen · Balanced

Qwen3.7 Plus

Added Jun 1, 2026

Compare models

Choose up to 3 models to compare.1 of 3 chosen

Loading models…

Use in the app

Qwen3.7 Plus is Alibaba's cost-effective Qwen 3.7 multimodal agent model for coding, tool use, productivity workflows, visual understanding, screen reading, and GUI interaction.

  • 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
991.8K
Max output
65.5K

Side by side

Qwen3.7 Plus compared

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

Compare models

Choose up to 3 models to compare.1 of 3 chosen

Loading models…

Qwen3.7 PlusQwenThis modelMistral Medium 3MistralRemove
ProviderQwenMistral
Discovery tierBalancedBalanced
AddedJun 1, 2026Sep 25, 2025
Limits
Context window991.81KBest131.07K
Max output65.54KBest32.77K
Average output—683 tokens
Pricing, USD per 1M tokens
Input$0.40$0.40
Output$1.60Best$2.00
Cache read$0.08—
Cache write$0.50—
Performance
Throughput—107.8 tok/s
Time to first token—0.7 s
Request success (24h)93.1%100.0%Best
Benchmark indexes
Intelligence Index—9.0
Math Index—30.3
Capabilities
ReasoningYesNo
ToolsYesNo
VisionYesYes
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 Plus
  • Mistral Medium 3

Intelligence Index

  • Qwen3.7 Plus—
  • Mistral Medium 39.0
3.8Catalog models by score55.1

Indexes

  • Math Index

    Composite of the math evaluations

    • Qwen3.7 Plus: —
    • Mistral Medium 3: 30.3

Document reasoning

  • AA-LCRv1.1

    Reasoning across long documents

    • Qwen3.7 Plus: —
    • Mistral Medium 3: 31.3%

Reasoning and knowledge

  • Humanity’s Last Exam

    Expert-level questions across academic fields

    • Qwen3.7 Plus: —
    • Mistral Medium 3: 4.1%

  • GPQA Diamond

    Graduate-level science questions

    • Qwen3.7 Plus: —
    • Mistral Medium 3: 57.8%

  • MMLU-Pro

    Multi-subject knowledge and reasoning

    • Qwen3.7 Plus: —
    • Mistral Medium 3: 76.0%

  • IFBench

    Following precise output instructions

    • Qwen3.7 Plus: —
    • Mistral Medium 3: 39.3%

Coding

  • LiveCodeBench

    Recent competitive programming problems

    • Qwen3.7 Plus: —
    • Mistral Medium 3: 40.0%

Math

  • AIME 2025

    Competition mathematics, 2025 problems

    • Qwen3.7 Plus: —
    • Mistral Medium 3: 30.3%

  • AIME

    Competition mathematics

    • Qwen3.7 Plus: —
    • Mistral Medium 3: 44.0%

  • MATH-500

    Competition math problems

    • Qwen3.7 Plus: —
    • Mistral Medium 3: 90.7%

Legacy evaluations

  • Terminal-Bench Hard

    Earlier terminal task suite

    • Qwen3.7 Plus: —
    • Mistral Medium 3: 3.8%

  • τ²-Bench Telecom

    Tool use in a customer-support simulation

    • Qwen3.7 Plus: —
    • Mistral Medium 3: 24.3%

  • AA-LCR (unversioned)

    Long-context reasoning, earlier grading

    • Qwen3.7 Plus: —
    • Mistral Medium 3: 31.3%

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
34.0%
About $0.29 per 1M input tokens with caching
Request success (24h)
93.5%
Unstable

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 71.4%
  • 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-plus",
    "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",
    messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)

Qwen

Other Qwen models, starting with the same family.