Qwen · Open weights

Qwen3.6 27B

Added Apr 23, 2026Open weights

Qwen3.6 27B is a native vision-language dense model with stronger agentic coding and STEM reasoning than Qwen 3.5 27B. It also improves spatial intelligence (including object localization/detection), plus video understanding, document OCR, and visual-agent workflows.

Tools
Vision
Video input

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

Pricing

USD per 1M tokens

Input: $0.20
Output: $2.24

Reference prices as published by the model provider. API example

Specifications

Context window: 262.1K
Max output: 65.5K

Side by side

Qwen3.6 27B compared

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

Limits
	Qwen3.6 27BQwenThis model	The Drummer Cydonia 24B v4MistralRemove
Provider	Qwen	Mistral
Discovery tier	Open weights	Open weights
Added	Apr 23, 2026	Jul 22, 2025
Context window	262.14KBest	32.77K
Max output	65.54K	—
Average output	—	535 tokens
Pricing, USD per 1M tokens
Input	$0.20	$0.20Best
Output	$2.24	$0.24Best
Performance
Request success (24h)	100.0%	—
Capabilities
Tools	Yes	No
Vision	Yes	No
Video input	Yes	No
Reasoning effort	—	—

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.

Request success (24h): 100.0%; Reliable

Hourly request success · last 72 hoursLowest hour 85.7%

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/qwen3.6-27b",
    "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/qwen3.6-27b",
    messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)

Qwen

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