DeepSeek V4 Flash (NovitaAI)

DeepSeek V4 Flash is designed as a speed and efficiency-oriented variant within the DeepSeek V4 family, retaining the DeepSeekMoE framework and Multi-Token Prediction strategy carried forward from DeepSeek V3. Its total parameter count sits at 285B, but only 13B activate per token during inference, a structure that allows the model to deliver capable language modeling while keeping the per-request compute footprint relatively modest. The architecture also introduces innovations aimed at long-context performance, combining Compressed Sparse Attention with DeepSeek Sparse Attention for moderately long spans and a Heavily Compressed Attention path for more aggressive compression, alongside Manifold-Constrained Hyper-Connections that constrain residual mappings onto doubly stochastic matrices to stabilize signal propagation during training and inference.

The model is intended for developers who want reasoning behavior without sacrificing context scale or throughput. It supports three reasoning modes ranging from fast, non-thinking responses to extended, maximum-depth analysis, making it flexible for both latency-sensitive chat and deliberate multi-step problem solving. DeepSeek V4 Flash is distributed with open weights, and a refreshed serving version was re-post-trained in late July 2026 without requiring developers to change model identifiers, rewrite prompts, or revise cost assumptions, an important practical consideration for teams that need stable deployment alongside ongoing improvements. Its fit is strongest for use cases that pair long inputs with controlled reasoning depth, where the MoE design helps balance quality against operational cost.