Qwen-Max
ActiveQwen-Max, based on Qwen2.5, provides the best inference performance among [Qwen models](/qwen), especially for complex multi-step tasks. It's a large-scale MoE model that has been pretrained on over 20 trillion...
Overview
Qwen-Max, based on Qwen2.5, provides the best inference performance among [Qwen models](/qwen), especially for complex multi-step tasks. It's a large-scale MoE model that has been pretrained on over 20 trillion...
History
Qwen-Max became available via the Alibaba API on 2025-02-01.
Training & availability
Training data has a knowledge cutoff of 2025-03-31 — information about events after that date is unlikely to appear in the model's responses. Alibaba has not released the underlying model weights — access is via their hosted API only.
Capabilities
-
Context window: 32K tokens.
-
Input modalities: text.
Limitations
-
The knowledge cutoff is 12 months old — this model will not know about recent events, releases, or API changes.
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The context window (32K tokens) is modest by 2026 standards — unsuitable for processing long documents in a single request.
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Text-only — cannot process images, audio, or video inputs.
Pricing
- Input: $1.0400 per 1M tokens
- Output: $4.1600 per 1M tokens
Use the cost calculator above to estimate monthly spend for your workload.
Quick start
Minimal example using the OpenRouter API. Copy, paste, replace the key.
from openai import OpenAI
client = OpenAI(
base_url="https://openrouter.ai/api/v1",
api_key="sk-or-...",
)
resp = client.chat.completions.create(
model="alibaba/qwen-max",
messages=[{"role": "user", "content": "Explain quantum computing in one sentence."}],
)
print(resp.choices[0].message.content)Cost calculator
Estimate your monthly bill. Presets are typical workload sizes.
Integrations & tooling support
- Tool calling
- Not supported
- Structured outputs
- Not supported
Price vs quality
Standard pricing band. Quality tier pending more benchmark coverage.
- Quality percentile
- —
- Effective price
- $3.38/1M
- Pricing breakdown
- $1.04/1M in
$4.16/1M out
Community ratings
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Comments
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