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" alt="How to Deploy Qwen3-4B-Instruct-2507 on AMD/Nvidia GPU Windows" style="display:block; width:100%; height:auto; border-radius:8px;">
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💾 File hash: ec849a26283e5400a8f0270a79cd44f0 (Update date: 2026-07-15)
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The Qwen3-4B-Instruct-2507: A Performance powerhouse for AI Applications
The Qwen3-4B-Instruct-2507 model is a game-changer in the world of artificial intelligence. With its balanced architecture, it delivers strong performance across a wide range of language tasks. This includes tasks such as text generation, sentiment analysis, and language translation. The model’s efficiency and accuracy are on par with the best in the industry, making it an attractive choice for developers seeking a reliable solution.
Key Features:
• Billion-parameter count: 4 billion• Context length: 8 K tokens• Inference speed: Faster than comparable 4 B models• Instruction tuning: Extensive
Unpacking the Strengths of Qwen3-4B-Instruct-2507
The Qwen3-4B-Instruct-2507 model is more than just a impressive specs sheet. Its ability to understand complex prompts and generate coherent responses is unparalleled in its class. This makes it an excellent choice for creative writing, technical documentation, and even educational content.
What Sets It Apart:
• Reasoning speed: Notable gains compared to similar 4 B models• Factual consistency: Higher accuracy than comparable models
Comparison with Similar Models
A comparison with similar 4 B-parameter models shows the Qwen3-4B-Instruct-2507’s superiority. It outperforms its peers in terms of reasoning speed and factual consistency, making it a compelling choice for developers.
| Feature | Value |
|---|---|
| Parameter Count | 4 Billion |
| Context Length | 8 K Tokens |
| Inference Speed | Faster than comparable 4 B models |
Conclusion: A Versatile Solution for AI Applications
The Qwen3-4B-Instruct-2507 model is a versatile solution for developers seeking a reliable and cost-effective choice for production-grade AI applications. Its balanced architecture, combined with its impressive performance capabilities, make it an excellent choice for a wide range of use cases.
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- Script downloading specialized multi-column layout parsing models for PDF scrapers
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