1 link tagged with all of: mixture-of-experts + inference-efficiency + deepseek-v4.1 + long-context
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DeepSeek V4.1 Flash is a 552B-parameter mixture-of-experts model that activates only 8B-16B parameters per token and supports a 1M-token context window for handling long documents and agentic workloads. The model cuts KV-cache memory usage by 4x compared to its predecessor while improving coding, reasoning, and agent performance.
- Activates just 8B parameters during input processing and 16B during generation, making it efficient despite the massive 552B backbone
- Reduces memory footprint by roughly 4x versus DeepSeek-V4-Flash-0731 through Compressed Sparse Attention 2 and a Causal Encoder-Decoder architecture
- Offers configurable reasoning-effort levels so developers can adjust latency and cost versus reasoning depth
- Handles multimodal input (text and images) natively with a 1M-token context window, designed for agents processing large amounts of data