PyTorch emulation library for Microscaling (MX)-compatible data formats
☆358Jul 17, 2026Updated this week
Alternatives and similar repositories for microxcaling
Users that are interested in microxcaling are comparing it to the libraries listed below. We may earn a commission when you buy through links labeled 'Ad' on this page.
Sorting:
- Implementation of Microscaling data formats in SystemVerilog.☆34Jul 6, 2025Updated last year
- Official implementation for Training LLMs with MXFP4☆130Apr 25, 2025Updated last year
- ☆114Feb 26, 2026Updated 4 months ago
- ☆16Jun 23, 2023Updated 3 years ago
- ☆127Mar 18, 2026Updated 4 months ago
- Wordpress hosting with auto-scaling - Free Trial Offer • AdFully Managed hosting for WordPress and WooCommerce businesses that need reliable, auto-scalable performance. Cloudways SafeUpdates now available.
- ☆172Mar 9, 2023Updated 3 years ago
- QuTLASS: CUTLASS-Powered Quantized BLAS for Deep Learning☆191Updated this week
- Code for Neurips24 paper: QuaRot, an end-to-end 4-bit inference of large language models.☆523Nov 26, 2024Updated last year
- The official implementation of the EMNLP 2023 paper LLM-FP4☆224Dec 15, 2023Updated 2 years ago
- Code for the papers: “Four Over Six: More Accurate NVFP4 Quantization with Adaptive Block Scaling” and “Adaptive Block-Scaled Data Types”☆198Apr 21, 2026Updated 2 months ago
- ☆52May 20, 2025Updated last year
- BitBLAS is a library to support mixed-precision matrix multiplications, especially for quantized LLM deployment.☆769Aug 6, 2025Updated 11 months ago
- [ICML 2026]A framework to compare low-bit integer and float-point formats☆81May 6, 2026Updated 2 months ago
- An efficient GPU support for LLM inference with x-bit quantization (e.g. FP6,FP5).☆282Jul 16, 2025Updated last year
- Serverless GPU API endpoints on Runpod - Get Bonus Credits • AdSkip the infrastructure headaches. Auto-scaling, pay-as-you-go, no-ops approach lets you focus on innovating your application.
- Fast Hadamard transform in CUDA, with a PyTorch interface☆340Mar 10, 2026Updated 4 months ago
- LLM Inference with Microscaling Format☆35Nov 12, 2024Updated last year
- Unit Scaling demo and experimentation code☆16Mar 12, 2024Updated 2 years ago
- Microsoft Automatic Mixed Precision Library☆636Dec 1, 2025Updated 7 months ago
- [MLSys'25] QServe: W4A8KV4 Quantization and System Co-design for Efficient LLM Serving; [MLSys'25] LServe: Efficient Long-sequence LLM Se…☆850Mar 6, 2025Updated last year
- ☆600Oct 29, 2024Updated last year
- [ICML 2024 Oral] Any-Precision LLM: Low-Cost Deployment of Multiple, Different-Sized LLMs☆130Jul 4, 2025Updated last year
- This repository contains the experimental PyTorch native float8 training UX☆226Aug 1, 2024Updated last year
- A library for accelerating Transformer models on NVIDIA GPUs, including using 8-bit and 4-bit floating point (FP8 and FP4) precision on H…☆3,435Updated this week
- End-to-end encrypted email - Proton Mail • AdSpecial offer: 40% Off Yearly / 80% Off First Month. All Proton services are open source and independently audited for security.
- Fast low-bit matmul kernels in Triton☆477Updated this week
- [MLSys'24] Atom: Low-bit Quantization for Efficient and Accurate LLM Serving☆343Jul 2, 2024Updated 2 years ago
- CUDA Templates and Python DSLs for High-Performance Linear Algebra☆10,104Updated this week
- Code repo for the paper "SpinQuant LLM quantization with learned rotations"☆415Feb 14, 2025Updated last year
- ☆65Apr 26, 2025Updated last year
- [ACL 2026 Main] Code for the paper "ARCQuant: Boosting NVFP4 Quantization with Augmented Residual Channels for LLMs"☆28Jun 1, 2026Updated last month
- AFPQ code implementation☆23Nov 6, 2023Updated 2 years ago
- Debug print operator for cudagraph debugging☆18Aug 2, 2024Updated last year
- [ICML 2025] Official PyTorch implementation of "FlatQuant: Flatness Matters for LLM Quantization"☆223Nov 25, 2025Updated 7 months ago
- AI Agents on DigitalOcean Gradient AI Platform • AdBuild production-ready AI agents using customizable tools or access multiple LLMs through a single endpoint. Create custom knowledge bases or connect external data.
- [ACL 2025 Main] EfficientQAT: Efficient Quantization-Aware Training for Large Language Models☆342Apr 10, 2026Updated 3 months ago
- Pytorch implementation of our paper accepted by NeurIPS 2022 -- Learning Best Combination for Efficient N:M Sparsity☆22Jan 13, 2023Updated 3 years ago
- [NeurIPS 2025] Speculate Deep and Accurate☆21Jan 16, 2026Updated 6 months ago
- ☆35Dec 22, 2025Updated 6 months ago
- ☆20Feb 12, 2025Updated last year
- [ICLR2024 spotlight] OmniQuant is a simple and powerful quantization technique for LLMs.☆901Nov 26, 2025Updated 7 months ago
- PyTorch native quantization and sparsity for training and inference☆2,909Updated this week