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Consistency diffusion language models: Up to 14x faster, no quality loss
research
11 min read
Consistency diffusion language models (CDLM) achieve up to 14.5x faster inference by utilizing consistency-based multi-token finalization and block-wise KV caching. These models provide a viable alternative to autoregressive language models for tasks such as math and coding.