Qwen2.5-0.5B

Qwen2.5-0.5B is the smallest model in the series, featuring 500 million parameters. It supports a 32K-token context window and can generate up to 8K tokens at once. The key advantages of this model are its exceptionally low power consumption and high processing speed while maintaining reasonable output quality. Optimized for deployment on resource-constrained devices—including mobile devices, IoT systems, and edge computing—it delivers solid performance in language understanding and basic reasoning tasks thanks to its high-quality pretraining on 18 trillion tokens.

Qwen2.5-0.5B is ideal for integration into applications requiring fast responses with limited computational power, such as website chatbots, mobile assistants, autocompletion systems, and basic text processing. It also serves as an excellent base model for fine-tuning specific tasks with minimal training and inference costs.

Announce Date: 19.09.2024
Parameters: 0.5B
Context: 32K
Attention Type: Full Attention
VRAM requirements: 0.6 GB using 4 bits quantization
Developer: Alibaba
Transformers Version: 4.43.1
License: Apache 2.0

Use our pre-built public endpoints to test inference and explore Qwen2.5-0.5B capabilities.

Rent your own physically dedicated instance with hourly or long-term monthly billing.

We recommend deploying private instances in the following scenarios:

• maximize endpoint performance,
• enable full context for long sequences,
• ensure top-tier security for data processing in an isolated, dedicated environment,
• use custom weights, such as fine-tuned models or LoRA adapters.

Contact our dedicated neural networks support team at nn@immers.cloud or send your request to the sales department at sale@immers.cloud.