sophnet/DeepSeek-V3-Fast

DeepSeek-V3 is a flagship open-source language model launched by the DeepSeek team, with its core positioning being to achieve high performance while significantly reducing training costs through innovative architectures and training technologies.

• Excellent Performance: It performs outstandingly in tests such as MMLU and GPQA. Its performance in code and mathematics tasks surpasses that of some closed-source models, and it excels in Chinese factual knowledge tasks.
• Reduced Costs: The training cost is compressed to 2.788 million H800 GPU hours, which is less than 1/3 of traditional solutions.
• Speed Improvement: The inference speed is more than twice that of the previous generation.
• Long Text Support: A 128K context length supports long text processing.

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Core Capabilities

⚙️ Efficient Architecture: Multi-head latent attention reduces inference memory usage, and the DeepSeekMoE architecture achieves load balancing.

🚀 Multi-Token Prediction: Allows the model to predict multiple future tokens at each position, accelerating inference speed by 1.8 times.

💪 FP8 Training: The feasibility is verified for the first time in ultra-large-scale models, reducing memory usage with little performance loss.

⚡ Parallel Framework: Bidirectional pipeline scheduling reduces communication overhead, making training efficiency close to the theoretical upper limit.