Alternatives and similar repositories for QUIK

Users that are interested in QUIK are comparing it to the libraries listed below

• Cornell-RelaxML / QuIP
  Code for paper: "QuIP: 2-Bit Quantization of Large Language Models With Guarantees"
  ☆385Updated last year
• IST-DASLab / qmoe
  Code for the paper "QMoE: Practical Sub-1-Bit Compression of Trillion-Parameter Models".
  ☆277Updated 2 years ago
• SqueezeAILab / KVQuant
  [NeurIPS 2024] KVQuant: Towards 10 Million Context Length LLM Inference with KV Cache Quantization
  ☆390Updated last year
• efeslab / Atom
  [MLSys'24] Atom: Low-bit Quantization for Efficient and Accurate LLM Serving
  ☆327Updated last year
• hahnyuan / PB-LLM
  PB-LLM: Partially Binarized Large Language Models
  ☆156Updated last year
• IST-DASLab / Sparse-Marlin
  Boosting 4-bit inference kernels with 2:4 Sparsity
  ☆85Updated last year
• Infini-AI-Lab / Sequoia
  scalable and robust tree-based speculative decoding algorithm
  ☆361Updated 9 months ago
• dropbox / gemlite
  Fast low-bit matmul kernels in Triton
  ☆392Updated 2 weeks ago
• spcl / QuaRot
  Code for Neurips24 paper: QuaRot, an end-to-end 4-bit inference of large language models.
  ☆443Updated 11 months ago
• fpgaminer / GPTQ-triton
  GPTQ inference Triton kernel
  ☆313Updated 2 years ago
• hahnyuan / RPTQ4LLM
  Reorder-based post-training quantization for large language model
  ☆194Updated 2 years ago
• usyd-fsalab / fp6_llm
  An efficient GPU support for LLM inference with x-bit quantization (e.g. FP6,FP5).
  ☆271Updated 3 months ago
• haochengxi / Train_Transformers_with_INT4
  ☆156Updated 2 years ago
• meta-pytorch / float8_experimental
  This repository contains the experimental PyTorch native float8 training UX
  ☆223Updated last year
• Cornell-RelaxML / quip-sharp
  ☆564Updated last year
• efeslab / fiddler
  [ICLR'25] Fast Inference of MoE Models with CPU-GPU Orchestration
  ☆240Updated 11 months ago
• jy-yuan / KIVI
  [ICML 2024] KIVI: A Tuning-Free Asymmetric 2bit Quantization for KV Cache
  ☆331Updated last month
• nbasyl / LLM-FP4
  The official implementation of the EMNLP 2023 paper LLM-FP4
  ☆217Updated last year
• Aaronhuang-778 / BiLLM
  [ICML 2024] BiLLM: Pushing the Limit of Post-Training Quantization for LLMs
  ☆227Updated 10 months ago
• SqueezeBits / QUICK
  QUICK: Quantization-aware Interleaving and Conflict-free Kernel for efficient LLM inference
  ☆118Updated last year
• SqueezeAILab / SqueezeLLM
  [ICML 2024] SqueezeLLM: Dense-and-Sparse Quantization
  ☆704Updated last year
• apple / ml-recurrent-drafter
  ☆218Updated 9 months ago
• mlc-ai / llm-perf-bench
  ☆120Updated last year
• Cornell-RelaxML / qtip
  ☆152Updated 4 months ago
• GATECH-EIC / ShiftAddLLM
  ShiftAddLLM: Accelerating Pretrained LLMs via Post-Training Multiplication-Less Reparameterization
  ☆110Updated last year
• neuralmagic / nm-vllm
  A high-throughput and memory-efficient inference and serving engine for LLMs
  ☆266Updated last year
• shawntan / scattermoe
  Triton-based implementation of Sparse Mixture of Experts.
  ☆248Updated last month
• AnswerDotAI / cold-compress
  Cold Compress is a hackable, lightweight, and open-source toolkit for creating and benchmarking cache compression methods built on top of…
  ☆147Updated last year
• wangsiping97 / FastGEMV
  High-speed GEMV kernels, at most 2.7x speedup compared to pytorch baseline.
  ☆120Updated last year
• NVIDIA / tilus
  Tilus is a tile-level kernel programming language with explicit control over shared memory and registers.
  ☆396Updated this week