What is Model1
Model1 is DeepSeek in the FlashMLA code repository, a mysterious model that has been updated and exposed, and may be the internal codename or the first engineering version of the next-generation flagship model DeepSeek-V4. The model has made multiple technological innovations, including returning to a 512-dimensional standard architecture, fully adapting to NVIDIA's Blackwell architecture (SM100), and introducing new mechanisms such as Token-level sparse MLA and VVPA, optimizing performance, improving long-text processing capability, and hardware adaptability. Currently, Model1 is still in the development stage, and specific details and capabilities await confirmation by DeepSeek's official release.
Main features of Model1
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High-performance computing: Fully adapts to NVIDIA's Blackwell architecture (SM100), and sparse operators on B200 GPUs have reached 350 TFlops, significantly improving computational efficiency.
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Long-text processing: Introduces Token-level sparse MLA and an FP8 KV Cache mixed-precision scheme, reducing memory pressure through sparse inference and improving long-text inference speed.
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Position awareness capability: Adopts the VVPA (numeric vector position awareness) mechanism to solve the problem of position information decay in traditional MLA in long-text scenarios, enhancing the model's ability to understand and generate long texts.
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Distributed storage optimization: Introduces the Engram mechanism for distributed storage or KV compression, working with high-throughput requirements to optimize the model's storage and computational efficiency.
Technical principles of Model1
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Architecture returns to 512 dimensions standard: Model1's core architecture returns to 512 dimensions, different from DeepSeek-V3 's 576-dimensional architecture. Returning to the architecture is intended to better adapt to the computing power alignment of next-generation hardware (such as the Blackwell architecture), or to optimize the Latent compression ratio.
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Sparsification and mixed-precision inference: Model1 introduces Token-level sparse MLA (multi-head self-attention mechanism), uses FP8 to store KV Cache during inference, and uses bfloat16 in matrix multiplication calculations to ensure precision. This sparsification and mixed-precision scheme significantly reduces memory usage and improves inference speed.
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Position awareness mechanism (VVPA): To solve the problem of position information decay in long texts, Model1 introduces the VVPA mechanism, enhancing the model's ability to perceive position information and improving long-text processing results.
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Hardware adaptation and optimization: Model1 has undergone extensive optimization for NVIDIA's Blackwell architecture (SM100), including dedicated CUDA instruction set optimization and support for CUDA 12.9, ensuring optimal performance on next-generation hardware.
Model1 project address
- GitHub repository：https://github.com/deepseek-ai/FlashMLA
Application scenarios of Model1
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Natural language processing (NLP): Model1 can be used for high-quality text generation, machine translation, and sentiment analysis. With its long-text processing capability, it can generate coherent and logically strong content, suitable for tasks such as news reporting, creative copywriting, and multilingual translation.
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Intelligent customer service: Model1 supports intelligent question answering and multi-turn dialogue, can quickly understand user intent and provide personalized solutions, suitable for real-time customer support and answering complex questions.
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Content creation: Model1 can assist creative writing and video script generation, providing inspiration and structured content support for writers and screenwriters, improving creative efficiency.
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Education field: Model1 can generate personalized learning suggestions, practice questions, and explanations, providing students with intelligent tutoring while assisting with language learning and grammar correction.
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Healthcare: Model1 can be used to analyze medical reports and medical records, assist doctors in diagnosis and treatment plan formulation, and provide patients with health consultation and preliminary diagnosis suggestions.