Alternatives and similar repositories for Awesome-Efficient-MoE

Users that are interested in Awesome-Efficient-MoE are comparing it to the libraries listed below

• OpenSparseLLMs / Linear-MoE
  ☆113Updated last month
• mdy666 / Qwen-Native-Sparse-Attention
  qwen-nsa
  ☆70Updated 3 months ago
• FFY0 / AdaKV
  The Official Implementation of Ada-KV: Optimizing KV Cache Eviction by Adaptive Budget Allocation for Efficient LLM Inference
  ☆87Updated last month
• lliai / D2MoE
  D^2-MoE: Delta Decompression for MoE-based LLMs Compression
  ☆63Updated 4 months ago
• smart-lty / ParallelSpeculativeDecoding
  [ICLR 2025] PEARL: Parallel Speculative Decoding with Adaptive Draft Length
  ☆101Updated 3 months ago
• Equationliu / Kangaroo
  [NeurIPS 2024] The official implementation of "Kangaroo: Lossless Self-Speculative Decoding for Accelerating LLMs via Double Early Exitin…
  ☆59Updated last year
• NVlabs / COAT
  [ICLR 2025] COAT: Compressing Optimizer States and Activation for Memory-Efficient FP8 Training
  ☆218Updated last month
• NVlabs / Fast-dLLM
  Official implementation of "Fast-dLLM: Training-free Acceleration of Diffusion LLM by Enabling KV Cache and Parallel Decoding"
  ☆320Updated this week
• JieShibo / MoLE
  [ICML 2025 Oral] Mixture of Lookup Experts
  ☆45Updated 2 months ago
• maomaocun / dLLM-cache
  Official PyTorch implementation of the paper "dLLM-Cache: Accelerating Diffusion Large Language Models with Adaptive Caching" (dLLM-Cache…
  ☆130Updated 2 weeks ago
• CASIA-IVA-Lab / FLAP
  [AAAI 2024] Fluctuation-based Adaptive Structured Pruning for Large Language Models
  ☆57Updated last year
• Gaffey / ExCP
  Official implementation of ICML 2024 paper "ExCP: Extreme LLM Checkpoint Compression via Weight-Momentum Joint Shrinking".
  ☆48Updated last year
• microsoft / SeerAttention
  SeerAttention: Learning Intrinsic Sparse Attention in Your LLMs
  ☆141Updated this week
• htqin / IR-QLoRA
  [ICML 2024 Oral] This project is the official implementation of our Accurate LoRA-Finetuning Quantization of LLMs via Information Retenti…
  ☆67Updated last year
• ruikangliu / IntactKV
  [ACL 2024] Official PyTorch implementation of "IntactKV: Improving Large Language Model Quantization by Keeping Pivot Tokens Intact"
  ☆46Updated last year
• ClubieDong / QAQ-KVCacheQuantization
  QAQ: Quality Adaptive Quantization for LLM KV Cache
  ☆52Updated last year
• Dominic789654 / LongGenBench
  Source code for the paper "LongGenBench: Long-context Generation Benchmark"
  ☆22Updated 9 months ago
• Hsu1023 / DuQuant
  [NeurIPS 2024 Oral🔥] DuQuant: Distributing Outliers via Dual Transformation Makes Stronger Quantized LLMs.
  ☆165Updated 10 months ago
• andy-yang-1 / DoubleSparse
  16-fold memory access reduction with nearly no loss
  ☆102Updated 4 months ago
• hahnyuan / ASVD4LLM
  Activation-aware Singular Value Decomposition for Compressing Large Language Models
  ☆74Updated 9 months ago
• ByteDance-Seed / FlexPrefill
  Code for paper: [ICLR2025 Oral] FlexPrefill: A Context-Aware Sparse Attention Mechanism for Efficient Long-Sequence Inference
  ☆124Updated 2 months ago
• machilusZ / FastGen
  This repo contains the source code for: Model Tells You What to Discard: Adaptive KV Cache Compression for LLMs
  ☆38Updated 11 months ago
• mit-han-lab / x-attention
  [ICML 2025] XAttention: Block Sparse Attention with Antidiagonal Scoring
  ☆213Updated 3 weeks ago
• ruikangliu / Quantized-Reasoning-Models
  [COLM 2025] Official PyTorch implementation of "Quantization Hurts Reasoning? An Empirical Study on Quantized Reasoning Models"
  ☆41Updated 3 weeks ago
• LINs-lab / DynMoE
  [ICLR 2025] Dynamic Mixture of Experts: An Auto-Tuning Approach for Efficient Transformer Models
  ☆121Updated 3 weeks ago
• BaiTheBest / SparseLLM
  Official Repo for SparseLLM: Global Pruning of LLMs (NeurIPS 2024)
  ☆64Updated 4 months ago
• thu-nics / MoA
  [CoLM'25] The official implementation of the paper <MoA: Mixture of Sparse Attention for Automatic Large Language Model Compression>
  ☆141Updated 3 weeks ago
• UNITES-Lab / MC-SMoE
  [ICLR 2024 Spotlight] Code for the paper "Merge, Then Compress: Demystify Efficient SMoE with Hints from Its Routing Policy"
  ☆88Updated last month
• dilab-zju / self-speculative-decoding
  Code associated with the paper **Draft & Verify: Lossless Large Language Model Acceleration via Self-Speculative Decoding**
  ☆198Updated 5 months ago
• ZhenweiAn / Dynamic_MoE
  Inference Code for Paper "Harder Tasks Need More Experts: Dynamic Routing in MoE Models"
  ☆60Updated last year