Qwen3 235B A22B Instruct 2507
ActiveQwen3-235B-A22B-Instruct-2507 is a multilingual, instruction-tuned mixture-of-experts language model based on the Qwen3-235B architecture, with 22B active parameters per forward pass. It is optimized for general-purpose text generation, including instruction following,...
Overview
Qwen3-235B-A22B-Instruct-2507 is a multilingual, instruction-tuned mixture-of-experts language model based on the Qwen3-235B architecture, with 22B active parameters per forward pass. It is optimized for general-purpose text generation, including instruction following,...
History
Qwen3 235B A22B Instruct 2507 became available via the Alibaba API on 2025-07-21.
Training & availability
Training data has a knowledge cutoff of 2025-06-30 — 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: 262K tokens.
-
Input modalities: text.
Recommended for: long-context, cheap.
Limitations
- Text-only — cannot process images, audio, or video inputs.
Pricing
- Input: $0.0710 per 1M tokens
- Output: $0.1000 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/qwen3-235b-a22b-2507",
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.
Popularity
Signals from open-source communities — not a quality measure, but useful for gauging adoption among developers.
Integrations & tooling support
- Tool calling
- Not supported
- Structured outputs
- Not supported
Price vs quality
Priced low — good for high-volume tasks. Quality tier pending more benchmark coverage.
- Quality percentile
- —
- Effective price
- $0.0928/1M
- Pricing breakdown
- $0.071/1M in
$0.1/1M out
Community ratings
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Comments
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