Qwen · Open weights

Qwen: QvQ Max

Added Mar 28, 2025Open weights

QvQ Max is the top model of the Qwen series. QvQ Max is capable of thinking and reasoning, can achieve significantly enhanced performance especially on hard problems.

Vision

Input: Text, Images
Output: Text
Discovery tier: Open weights

Pricing

USD per 1M tokens

Input: $1.20
Output: $4.80

Reference prices as published by the model provider. API example

Specifications

Context window: 128K
Max output: 8.2K

Side by side

Qwen: QvQ Max compared

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

Limits
	Qwen: QvQ MaxQwenThis model	Qwen 3.8 27B KimikoQwenRemove
Provider	Qwen	Qwen
Discovery tier	Open weights	Open weights
Added	Mar 28, 2025	Oct 5, 2026
Context window	128K	262.14KBest
Max output	8.19K	32.77KBest
Average output	—	210 tokens
Pricing, USD per 1M tokens
Input	$1.20	$0.10Best
Output	$4.80	$0.60Best
Cache read	—	$0.05
Performance
Request success (24h)	—	100.0%
Capabilities
Reasoning	No	Yes
Tools	No	Yes
Vision	Yes	Yes
Reasoning effort	—	—

Public evaluations

Benchmarks

There are no public benchmark results for these models yet.

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

Qwen

Other Qwen models, starting with the same family.