Qwen · Balanced
Qwen 3.6 Plus
Qwen 3.6 Plus is a commercial native multimodal agent model with a major step up over the 3.5 series in agentic coding, front-end programming, OCR, object localization, and general vision-language performance. Supports text, image, and video input with a 1M context window.
- Tools
- Vision
- Video input
- Input
- Text, Images, Video
- Output
- Text
- Discovery tier
- Balanced
Pricing
USD per 1M tokens- Input
- $0.33
- Output
- $1.95
- Cache read
- $0.0325
- Cache write
- $0.41
Reference prices as published by the model provider. API example
Specifications
- Context window
- 991.8K
- Max output
- 65.5K
Side by side
Qwen 3.6 Plus compared
Specifications, prices, speed and benchmark scores next to each other. Benchmarks below show every compared model too.
| Qwen 3.6 PlusQwenThis model | MiniMax M2-herMiniMaxRemove | |
|---|---|---|
| Provider | Qwen | MiniMax |
| Discovery tier | Balanced | Balanced |
| Added | Apr 2, 2026 | Jan 12, 2025 |
| Limits | ||
| Context window | 991.81KBest | 65.53K |
| Max output | 65.54KBest | 2.05K |
| Average output | — | 186 tokens |
| Pricing, USD per 1M tokens | ||
| Input | $0.33 | $0.30Best |
| Output | $1.95 | $1.21Best |
| Cache read | $0.0325 | — |
| Cache write | $0.41 | — |
| 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.
Developers
Use it through the API
Noumen’s API is OpenAI-compatible: any Chat Completions client works with a base URL and a key.
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-plus",
"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-plus",
messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)Qwen
Related models
Other Qwen models, starting with the same family.