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Which transformer architecture is best Encoder-only vs Encoder-decoder vs Decoder-only models
Prefill vs Decode explained in 60 seconds
Faster LLMs: Accelerate Inference with Speculative Decoding
Encoder-Only Transformers (like BERT) for RAG, Clearly Explained!!!
Why LLMs Read Fast but Write Slowly - Prefill vs Decode
Decoding Strategies in LLMs (Explained Simply) | How LLMs Choose the Next Token
Transformer models: Encoders
Why Separating Prefill and Decode Makes LLMs Faster | vLLM, LLM-D and NIXL
Transformer models: Encoder-Decoders
Encoder-decoder architecture: Overview
LLM Tokenizers Explained: BPE Encoding, WordPiece and SentencePiece
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Last Updated: October 17, 2026
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This video is an excerpt taken from our Generative AI Nanodegree program: ... In this video, we break down the two fundamental stages of Inference is not one single process. This lesson breaks down its two phases: prefill, where the model reads your entire prompt at ... Try Voice Writer - speak your thoughts and let AI handle the grammar: voicewriter.io The battle of transformer architectures: ... Why does your GPU hit 100% utilization during prefill... then suddenly drop to 20% during generation? Because Prefill and ... Ready to become a certified watsonx AI Assistant Engineer? Register now and use code IBMTechYT20 for 20% off of your exam ... A general high-level introduction to the 00:00 Introduction & Why Prefill/ In this video we talk about three tokenizers that are commonly used when training large language models: (1) the byte-pair ...