RUNLOCALAIv38
→WILL IT RUNBEST GPUCOMPARETROUBLESHOOTSTARTPULSEMODELSHARDWARETOOLSBENCH
RUNLOCALAI

Operator-grade instrument for local-AI hardware intelligence. Hand-written verdicts. Real benchmarks. Reproducible commands.

OP·Fredoline Eruo
DIR
  • Models
  • Hardware
  • Tools
  • Benchmarks
  • Will it run?
GUIDES
  • Best GPU
  • Best laptop
  • Best Mac
  • Best used GPU
  • Best budget GPU
  • Best GPU for Ollama
  • Best GPU for SD
  • AI PC build $2K
  • CUDA vs ROCm
  • 16 vs 24 GB
  • Compare hardware
  • Custom compare
REF
  • Systems
  • Ecosystem maps
  • Pillar guides
  • Methodology
  • Glossary
  • Errors KB
  • Troubleshooting
  • Resources
  • Public API
EDITOR
  • About
  • About the author
  • Changelog
  • Latest
  • Updates
  • Submit benchmark
  • Send feedback
  • Trust
  • Editorial policy
  • How we make money
  • Contact
LEGAL
  • Privacy
  • Terms
  • Sitemap
MAIL · MONTHLY DIGEST
Get monthly local AI changes
Monthly recap. No spam.
DISCLOSURE

Some links on this site are affiliate links (Amazon Associates and other first-class retailers). When you buy through them, we earn a small commission at no extra cost to you. Affiliate links do not influence our verdicts — there are cards we rate highly that we don't have affiliate relationships with, and cards that sell well that we refuse to recommend. Read more →

SYS · ONLINEUPTIME · 100%2026 · operator-owned
RUNLOCALAI · v38
Glossary / Neural network architectures / Decoder-Only Transformer
Neural network architectures

Decoder-Only Transformer

Decoder-only is the architecture of GPT, Llama, Qwen, Mistral, DeepSeek, and almost every modern open-weight LLM. The model is a stack of transformer decoder blocks (causal self-attention only, no cross-attention to a separate encoder), trained autoregressively on next-token prediction.

The "encoder" doesn't exist as a separate component — input prompt tokens and generated tokens go through the same blocks. The causal mask prevents tokens from attending to future positions.

Decoder-only won the architecture war for generative LLMs because it scales cleanly with parameters and data, and a single model can do everything (chat, code, reasoning, summarization) with prompting alone.

Related terms

Large Language Model (LLM)Encoder-Decoder TransformerTransformer

Reviewed by Fredoline Eruo. See our editorial policy.

Buyer guides
  • Best GPU for local AI →
  • Best laptop for local AI →
  • Best Mac for local AI →
When it doesn't work
  • CUDA out of memory →
  • Ollama running slowly →
  • ROCm not detected →