Alternatives and similar repositories for Awesome-Efficient-AIGC

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

• Hsu1023 / DuQuant
  [NeurIPS 2024 Oral🔥] DuQuant: Distributing Outliers via Dual Transformation Makes Stronger Quantized LLMs.
  ☆176Updated last year
• thu-nics / qllm-eval
  Code Repository of Evaluating Quantized Large Language Models
  ☆135Updated last year
• 42Shawn / PTQ4DM
  Implementation of Post-training Quantization on Diffusion Models (CVPR 2023)
  ☆139Updated 2 years ago
• ruikangliu / FlatQuant
  [ICML 2025] Official PyTorch implementation of "FlatQuant: Flatness Matters for LLM Quantization"
  ☆190Updated last month
• IST-DASLab / OBC
  Code for the NeurIPS 2022 paper "Optimal Brain Compression: A Framework for Accurate Post-Training Quantization and Pruning".
  ☆129Updated 2 years ago
• Intelligent-Computing-Lab-Panda / GPTAQ
  Code implementation of GPTAQ (https://arxiv.org/abs/2504.02692)
  ☆75Updated 3 months ago
• thu-nics / ViDiT-Q
  [ICLR'25] ViDiT-Q: Efficient and Accurate Quantization of Diffusion Transformers for Image and Video Generation
  ☆132Updated 7 months ago
• thu-nics / MBQ
  The code repository of "MBQ: Modality-Balanced Quantization for Large Vision-Language Models"
  ☆66Updated 8 months ago
• wimh966 / QDrop
  The official PyTorch implementation of the ICLR2022 paper, QDrop: Randomly Dropping Quantization for Extremely Low-bit Post-Training Quan…
  ☆124Updated last month
• ModelTC / TFMQ-DM
  [CVPR 2024 Highlight & TPAMI 2025] This is the official PyTorch implementation of "TFMQ-DM: Temporal Feature Maintenance Quantization for…
  ☆109Updated last month
• ChenMnZ / PrefixQuant
  An algorithm for weight-activation quantization (W4A4, W4A8) of LLMs, supporting both static and dynamic quantization
  ☆164Updated 2 weeks ago
• AboveParadise / LLMCBench
  ☆26Updated 11 months ago
• adreamwu / PTQ4DiT
  PyTorch implementation of PTQ4DiT https://arxiv.org/abs/2405.16005
  ☆40Updated last year
• pprp / Awesome-Efficient-MoE
  Efficient Mixture of Experts for LLM Paper List
  ☆143Updated last month
• BrotherHappy / OSTQuant
  [ICLR2025]: OSTQuant: Refining Large Language Model Quantization with Orthogonal and Scaling Transformations for Better Distribution Fitt…
  ☆82Updated 7 months ago
• Juanerx / Q-DiT
  [CVPR 2025] Q-DiT: Accurate Post-Training Quantization for Diffusion Transformers
  ☆72Updated last year
• Hao840 / Awesome-Low-Precision-Training
  A collection of research papers on low-precision training methods
  ☆43Updated 6 months ago
• ZHITENGLI / ARB-LLM
  [ICLR'25] ARB-LLM: Alternating Refined Binarizations for Large Language Models
  ☆27Updated 3 months ago
• pprp / Awesome-LLM-Quantization
  Awesome list for LLM quantization
  ☆353Updated last month
• pprp / Awesome-LLM-Prune
  Awesome list for LLM pruning.
  ☆273Updated last month
• nbasyl / OFQ
  The official implementation of the ICML 2023 paper OFQ-ViT
  ☆33Updated 2 years ago
• A-suozhang / Awesome-Efficient-Diffusion
  Curated list of methods that focuses on improving the efficiency of diffusion models
  ☆44Updated last year
• SNU-ARC / any-precision-llm
  [ICML 2024 Oral] Any-Precision LLM: Low-Cost Deployment of Multiple, Different-Sized LLMs
  ☆121Updated 4 months ago
• hatchetProject / QuEST
  [ICCV 2025] QuEST: Efficient Finetuning for Low-bit Diffusion Models
  ☆55Updated 4 months ago
• Guangxuan-Xiao / torch-int
  This repository contains integer operators on GPUs for PyTorch.
  ☆222Updated 2 years ago
• hustvl / PD-Quant
  [CVPR 2023] PD-Quant: Post-Training Quantization Based on Prediction Difference Metric
  ☆60Updated 2 years ago
• liyunqianggyn / Awesome-LLMs-Pruning
  Awesome LLM pruning papers all-in-one repository with integrating all useful resources and insights.
  ☆132Updated 3 months ago
• xvyaward / owq
  Code for the AAAI 2024 Oral paper "OWQ: Outlier-Aware Weight Quantization for Efficient Fine-Tuning and Inference of Large Language Model…
  ☆67Updated last year
• ruikangliu / Quantized-Reasoning-Models
  [COLM 2025] Official PyTorch implementation of "Quantization Hurts Reasoning? An Empirical Study on Quantized Reasoning Models"
  ☆57Updated 4 months ago
• megvii-research / FQ-ViT
  [IJCAI 2022] FQ-ViT: Post-Training Quantization for Fully Quantized Vision Transformer
  ☆354Updated 2 years ago