Qwen3 30B A3B Thinking 2507
VerifiedOpen-weight 30B reasoning model with 128k context for extended text tasks.
About Qwen3 30B A3B Thinking 2507
Built on the Qwen3 architecture, this model provides full open-weight access, enabling researchers and developers to inspect, fine-tune, and deploy it locally. Its 30B parameter scale balances capability with practical hardware requirements while maintaining a 131072-token context window for handling lengthy documents or conversations.
The Thinking variant emphasizes structured reasoning over multiple steps, making it suitable for tasks that benefit from step-by-step text analysis. Typical usage includes document summarization, technical writing assistance, and multi-turn dialogue where maintaining coherence across long contexts matters.
Because weights are publicly released, the model supports customization for domain-specific applications without vendor lock-in. Users commonly run it for research experiments, internal tooling, or production systems that require transparent and modifiable language models.
Capabilities
How Qwen3 30B A3B Thinking 2507 compares
Qwen3 30B A3B Thinking 2507 (striped bar) vs other language models on intelligence, speed and price.
Price
USD per 1M output tokens · Lower is better · Qwen3 30B A3B Thinking 2507 ranks #20 of 66
Sources: Artificial Analysis (intelligence, speed) · OpenRouter (price).
Best for
Long-Context Document Analysis
The model handles extended inputs effectively for tasks like summarizing lengthy reports or extracting insights from large datasets within its 131072-token context.
Complex Code Generation
It supports creating and refining intricate code structures across multiple languages while following detailed instructions for implementation.
Mathematical and Logical Reasoning
Users benefit from its step-by-step approach to solving advanced math problems and performing structured logical deductions.
Strengths & limitations
Strengths
- +Strong reasoning focus via Thinking variant
- +Efficient 30B-scale performance
- +Large 128k context window
- +Solid multilingual support
Limitations
- –Text-only modality
- –Not multimodal
- –Moderate size limits peak capability vs larger models
Cost calculator
Estimate what Qwen3 30B A3B Thinking 2507 would cost for your usage.
Based on Qwen3 30B A3B Thinking 2507's $0.08/1M input · $0.40/1M output. Estimate only — actual cost varies by provider and caching.
Quick start
OpenRouter's API is OpenAI-compatible — most SDKs work by just swapping the base URL. Only the model slug changes between models.
import OpenAI from "openai";
const client = new OpenAI({
baseURL: "https://openrouter.ai/api/v1",
apiKey: process.env.OPENROUTER_API_KEY,
});
const completion = await client.chat.completions.create({
model: "qwen/qwen3-30b-a3b-thinking-2507",
messages: [{ role: "user", content: "Hello!" }],
});
console.log(completion.choices[0].message.content);Model slug: qwen/qwen3-30b-a3b-thinking-2507
Editor's verdict
Qwen3 30B A3B Thinking 2507 is Alibaba Qwen's open-weight language models with a 131K-token context window.
At $0.40 per 1M output tokens, it is very cost-efficient for its class.
As an open-weight model you can self-host it or call it through a hosted API.
Best suited to strong reasoning focus via thinking variant and efficient 30b-scale performance.
Frequently asked questions
The model provides a context window of 131072 tokens.
User reviews
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