Optimum

Optimum is an open source toolkit that provides hardware optimization tools to accelerate inference and training.

Optimum is an extension of Transformers, Diffusers, TIMM, and Sentence-Transformers that provides a set of optimization tools for targeted hardware. It enables maximum efficiency to train and run models while keeping things easy to use. The toolkit supports multiple ecosystems and hardware providers including ONNX Runtime, OpenVINO, ExecuTorch, Intel Gaudi, AWS Trainium and Inferentia, and NVIDIA TensorRT-LLM. Users can export models, perform graph optimization, apply quantization, and run accelerated inference or training both programmatically and via a command line interface. It is designed for developers and engineers working with machine learning models who need to deploy efficiently on specific hardware backends.

Optimum at a glance

Best for: Software engineer
Runs on: Linux, Windows, macOS, CLI, open source
Pricing: Free
Released: July 2021
Category: AI coding tool
Website: github.com/huggingface/optimum

Key features

Model export to ONNX and ExecuTorch formats
Graph optimization and quantization
Command line interface for exports and optimizations
Wrappers for Transformers Trainer for accelerated training
Support for Intel Gaudi, AWS Trainium, and ONNX Runtime
Python classes for running ONNX models with ONNX Runtime

Use it for

Exporting Transformer and Diffuser models to ONNX
Running optimized model inference on edge devices with ExecuTorch
Training models on Intel Gaudi and AWS Trainium hardware
Quantizing PyTorch models using Quanto

Alternatives to Optimum

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OptiLLM — Increases LLM reasoning accuracy by up to 10x without model training.
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Strata — Runs large AI models locally on consumer gaming PCs without server reliance.
TensorRT — Speeds up inference by 36X compared to CPU-only platforms.
MNN — It delivers high-performance inference and training with a lightweight footprint.
Reactive Optimizers — It automatically adapts to new tasks and architectures without a pre-tuned recipe.
Muse Wonder — Explore performance benchmarks for Muse Code and Muse Spark.
fal — Access 1,000+ generative models and high-performance serverless GPUs.
OpenEvolve — Automates algorithmic discovery and optimization without human guidance.
Opik — It offers comprehensive tracing, automated evaluations, and open-source flexibility.
AirLLM — Runs massive 70B+ parameter models on small 4GB consumer GPUs.

All Optimum alternatives