DownloadDeepSeek-V4.1-Flash is an open-weight multimodal AI model developed by DeepSeek, designed for advanced reasoning, software engineering, agentic workflows, and long-context processing. Built on a Mixture-of-Experts (MoE) architecture with 763 billion total parameters, including a 552-billion-parameter backbone, the model combines high-performance intelligence with efficient inference through selective parameter activation. It supports a context window of up to 1 million tokens, enabling developers to analyze extensive codebases, lengthy documents, and complex multi-step tasks. DeepSeek-V4.1-Flash introduces a Causal Encoder-Decoder architecture, Compressed Sparse Attention 2, and advanced KV cache compression to reduce memory requirements and computational costs, particularly for input-heavy AI applications. The model also features native image understanding, configurable reasoning effort from 1 to 100, and enhanced agentic capabilities for autonomous coding and tool calling.
Features
- Advanced Reasoning and Problem-Solving: Supports complex mathematical reasoning, logical analysis, technical problem-solving, and adjustable reasoning effort from 1 to 100.
- Agentic AI and Software Engineering: Enables autonomous coding, debugging, repository-level development, tool calling, and multi-step AI agent workflows.
- 1 Million Token Context Window: Processes extensive documents, large software repositories, long conversations, and complex contextual information.
- Native Multimodal Understanding: Analyzes images and text together for document interpretation, chart understanding, visual reasoning, and image-based question answering.
- Efficient Mixture-of-Experts Architecture: Combines 763 billion total parameters with selective activation of 8 billion parameters during prefill and 16 billion during decoding, alongside advanced KV cache compression for efficient inference.
- - Open-Weight Deployment and Integration: MIT-licensed model weights support self-hosting, customization, and integration with vLLM, SGLang, Hugging Face Transformers, and OpenAI-compatible APIs.
Project Samples
