❯ DeepSeek Launches V4.1 Flash, Using a 552-Billion-Parameter Architecture to Cut Inference Costs

New architectureDeepSeek released DeepSeek-V4.1-Flash with 552 billion backbone parameters and a one-million-token context window. The company calls it the smallest model in its new architecture family and says a larger Pro model will follow.

Inference designTechnical materials describe a causal encoder-decoder architecture with different active parameter counts during prefill and decoding, targeting inference efficiency and cache use. DeepSeek’s agentic, coding and cybersecurity benchmarks put it ahead of several larger models, but they remain vendor results that require testing under consistent prompts, output budgets and real tasks.

Product positionFlash uses a smaller active footprint for long-context and agent workloads. Developers need to compare task completion, output length and cost per task; a low token price can disappear through retries. Its price-performance edge will also need another test when the larger Pro model arrives.

▪ SIGNALDeepSeek is debuting its new architecture in a low-priced Flash model, leaving real-world task costs to determine whether the efficiency gain holds.