Qwen3 30B A3B Instruct 2507
VerifiedOpen-weight LLM for multilingual instruction and long-context tasks.
About Qwen3 30B A3B Instruct 2507
Built on the Qwen3 series, the model provides full parameter access through its open-weight release. This enables fine-tuning and local deployment by developers and researchers. The 131072-token context supports coherent processing of lengthy documents and conversations.
Its instruct tuning focuses on accurate response to user directives across varied domains. The architecture balances capability with accessibility for text-only workloads. Open weights encourage experimentation and adaptation without proprietary restrictions.
Common applications include chat interfaces, code assistance, and document analysis. Users deploy it for multilingual text generation and reasoning tasks. The design suits both individual prototyping and integration into larger systems.
Capabilities
How Qwen3 30B A3B Instruct 2507 compares
Qwen3 30B A3B Instruct 2507 (striped bar) vs other language models on intelligence, speed and price.
Price
USD per 1M output tokens · Lower is better · Qwen3 30B A3B Instruct 2507 ranks #10 of 78
Sources: Artificial Analysis (intelligence, speed) · OpenRouter (price).
Best for
Long-document summarization
The 131072-token context window enables processing and condensing entire books, research papers, or legal contracts into concise summaries while retaining key details.
Multi-turn instruction following
As an instruct-tuned LLM, it maintains coherence across extended conversations and executes complex, multi-step user directives accurately.
Technical content creation
It supports generation of code, technical documentation, and explanations by leveraging its large context for referencing prior code snippets or specifications.
Strengths & limitations
Strengths
- +Strong coding and math performance
- +Effective 128k context handling
- +Robust Chinese-English bilingual support
- +Efficient inference for model size
Limitations
- –Text-only modality
- –No native vision capabilities
- –Knowledge limited to training cutoff
Cost calculator
Estimate what Qwen3 30B A3B Instruct 2507 would cost for your usage.
Based on Qwen3 30B A3B Instruct 2507's $0.05/1M input · $0.19/1M 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-instruct-2507",
messages: [{ role: "user", content: "Hello!" }],
});
console.log(completion.choices[0].message.content);Model slug: qwen/qwen3-30b-a3b-instruct-2507
Editor's verdict
Qwen3 30B A3B Instruct 2507 is Alibaba Qwen's open-weight language models with a 131K-token context window.
At $0.19 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 coding and math performance and effective 128k context handling.
Frequently asked questions
The model supports a context window of 131072 tokens.
User reviews
Real, verified reviews from the community shape this model's rating.
Loading reviews…
Other Qwen models
Sibling versions in the Qwen family from Alibaba Qwen.
Similar models
Other language models worth comparing.