Different versions of the DeepSeek model (such as 1.5B, 7B, 8B, 14B, 32B, 70B, 671B) primarily differ in the number of parameters.
The larger the parameter count, the more complex and capable the model typically is, but this also comes with higher computational resource demands and training costs.
1. DeepSeek 1.5B (1.5 Billion Parameters)
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Use Cases: Lightweight tasks, such as text generation and simple Q&A.
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CPU Deployment:
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Memory: 16GB RAM
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Storage: 10GB disk space (for model and cache)
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CPU: Modern processor with 4+ cores (e.g., Intel i5 or AMD Ryzen 5)
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GPU Deployment (Optional):
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GPU: NVIDIA GTX 1660 or higher (4GB VRAM)
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Memory: 16GB RAM
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Storage: 10GB disk space
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2. DeepSeek 7B (7 Billion Parameters)
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Use Cases: Medium-complexity tasks, such as text generation, translation, and summarization.
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CPU Deployment:
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Memory: 32GB RAM
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Storage: 20GB disk space
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CPU: Modern processor with 8+ cores (e.g., Intel i7 or AMD Ryzen 7)
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GPU Deployment (Recommended):
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GPU: NVIDIA RTX 3060 or higher (12GB VRAM)
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Memory: 32GB RAM
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Storage: 20GB disk space
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3. DeepSeek 14B (14 Billion Parameters)
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Use Cases: More complex tasks, such as long-form text generation and complex Q&A.
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CPU Deployment:
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Memory: 64GB RAM
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Storage: 40GB disk space
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CPU: Modern processor with 16+ cores (e.g., Intel Xeon or AMD Ryzen 9)
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GPU Deployment (Recommended):
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GPU: NVIDIA RTX 3090 or higher (24GB VRAM)
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Memory: 64GB RAM
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Storage: 40GB disk space
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4. DeepSeek 32B (32 Billion Parameters)
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Use Cases: High-performance tasks, such as large-scale text generation and complex reasoning.
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CPU Deployment:
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Memory: 128GB RAM
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Storage: 100GB disk space
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CPU: Server-grade processor with 32+ cores (e.g., AMD EPYC or Intel Xeon)
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GPU Deployment (Recommended):
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GPU: NVIDIA A100 or higher (40GB VRAM)
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Memory: 128GB RAM
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Storage: 100GB disk space
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5. DeepSeek 70B (70 Billion Parameters)
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Use Cases: Top-tier performance tasks, such as large-scale language understanding and complex reasoning.
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CPU Deployment:
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Memory: 256GB RAM
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Storage: 200GB disk space
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CPU: Server-grade processor with 64+ cores
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GPU Deployment (Recommended):
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GPU: Multiple NVIDIA A100 (80GB VRAM) or H100
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Memory: 256GB RAM
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Storage: 200GB disk space
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6. DeepSeek 671B (671 Billion Parameters)
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Use Cases: Ultra-large-scale tasks, such as very long text generation and complex scientific research.
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CPU Deployment:
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Memory: 1TB RAM or higher
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Storage: 1TB disk space
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CPU: Multi-socket server-grade processor (e.g., AMD EPYC or Intel Xeon)
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GPU Deployment (Recommended):
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GPU: Multiple NVIDIA H100 or A100 (80GB VRAM)
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Memory: 1TB RAM or higher
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Storage: 1TB disk space
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General Recommendations
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GPU Acceleration:
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For models 7B and above, GPU acceleration is strongly recommended, especially with high-performance NVIDIA GPUs (such as RTX 3090, A100, H100).
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The larger the VRAM, the larger the supported batch size for inference, resulting in faster speeds.
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Memory Requirements:
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The larger the model parameter count, the higher the memory requirement. If memory is insufficient, inference speed will drop significantly, and the model may even fail to run.
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