Qwen2.5-14B

Qwen2.5-14B features 14 billion parameters, 48 layers, and a 40/8 attention head architecture, representing a substantial increase in computational power and complexity compared to the 7B version. The model supports a 128K-token context window with 8K-token generation capability, enabling it to process voluminous documents and execute complex multi-step tasks.

The uniqueness of Qwen2.5-14B lies in its reintroduction to the series after being absent from Qwen2, effectively bridging the critical gap between 7B and larger models. This size proves particularly valuable for organizations requiring high performance without the substantial costs associated with 32B or 72B-level models. The model demonstrates significant improvements in expert-level knowledge, complex reasoning, and multi-domain task handling capabilities.

Qwen2.5-14B is ideally suited for medium-to-large scale enterprise applications demanding high-quality processing with reasonable infrastructure costs. The model excels in knowledge management systems, comprehensive analytics, and serves as an excellent foundation for developing industry-specific AI solutions.

Announce Date: 19.09.2024
Parameters: 14B
Context: 131K
Attention Type: Full Attention
VRAM requirements: 30.5 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 Qwen2.5-14B 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.