What Are the Key Differences Between DeepSeek Model Versions (1.5B, 7B, 8B, 14B, 32B, 70B, 671B)?

The different versions of the DeepSeek model (such as 1.5B, 7B, 8B, 14B, 32B, 70B, 671B) mainly differ in the number of parameters.

Generally, the larger the parameter count, the more complex and capable the model, but the higher the computational resource requirements and training costs.
Below are the main differences between each version:

1. 1.5B

   • Parameters: 1.5 billion

   • Characteristics: Lightweight, suitable for scenarios with limited resources or low performance demands. Fast inference speed, but average performance on complex tasks.

2. 7B

   • Parameters: 7 billion

   • Characteristics: Medium scale, suitable for most general tasks. Good performance with moderate resource requirements.

3. 8B

   • Parameters: 8 billion

   • Characteristics: Similar to 7B, with slightly improved performance. Suitable for tasks requiring a bit more capability.

4. 14B

   • Parameters: 14 billion

   • Characteristics: Further performance improvement, suitable for more complex tasks. Higher resource requirements.

5. 32B

   • Parameters: 32 billion

   • Characteristics: High performance, suitable for complex tasks. Significant resource demands with high training and inference costs.

6. 70B

   • Parameters: 70 billion

   • Characteristics: Near top-tier performance, suitable for highly demanding complex tasks. Very high resource requirements.