Compare DeepSeek V4.1 Flash and Qwen3 Embedding 8B on key metrics including price, context length, throughput, and other model features.
DeepSeek V4.1 Flash is a sparse mixture-of-experts model from DeepSeek, and the first built on the company's Causal Encoder-Decoder (CED) architecture. It activates 8B parameters on input and 16B on output from a 552B-parameter backbone, an asymmetric split that keeps per-token compute low relative to the model's total size. Image understanding is native to the architecture, with visual and text embeddings trained jointly from the start of pre-training rather than added afterward as in the earlier experimental V4 Flash Vision Exp.
The Qwen3 Embedding model series is the newest proprietary addition to the Qwen family, purpose-built for text embedding and ranking applications. Leveraging the strong multilingual abilities, long-context comprehension, and reasoning prowess of its base model, Qwen3 Embedding delivers impressive progress across various embedding and ranking tasks. These include text retrieval, code search, text classification, clustering, and bitext mining.