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Compact mode

Mamba vs RetNet

Core Classification Comparison

Industry Relevance Comparison

  • Modern Relevance Score 🚀

    Current importance and adoption level in 2025 machine learning landscape
    Mamba
    • 10
      Current importance and adoption level in 2025 machine learning landscape (30%)
    RetNet
    • 9
      Current importance and adoption level in 2025 machine learning landscape (30%)
  • Industry Adoption Rate 🏢

    Current level of adoption and usage across industries
    Both*

Basic Information Comparison

Historical Information Comparison

Performance Metrics Comparison

Application Domain Comparison

Technical Characteristics Comparison

Evaluation Comparison

Facts Comparison

  • Interesting Fact 🤓

    Fascinating trivia or lesser-known information about the algorithm
    Mamba
    • Processes sequences faster than Transformers with linear memory
    RetNet
    • Achieves similar performance to Transformers with significantly better efficiency
Alternatives to Mamba
RWKV
Known for Linear Scaling Attention
🔧 is easier to implement than RetNet
learns faster than RetNet
State Space Models V3
Known for Long Sequence Processing
🔧 is easier to implement than RetNet
learns faster than RetNet
Hyena
Known for Subquadratic Scaling
🔧 is easier to implement than RetNet
learns faster than RetNet
SVD-Enhanced Transformers
Known for Mathematical Reasoning
🔧 is easier to implement than RetNet
MambaByte
Known for Efficient Long Sequences
🔧 is easier to implement than RetNet
learns faster than RetNet
S4
Known for Long Sequence Modeling
🔧 is easier to implement than RetNet
QLoRA (Quantized LoRA)
Known for Memory Efficiency
🔧 is easier to implement than RetNet
learns faster than RetNet
RoPE Scaling
Known for Long Context Handling
🔧 is easier to implement than RetNet
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