bytedance/byteir
A model compilation solution for various hardware
ByteIR provides a complete system for optimizing and running machine learning models on various hardware like CPUs, GPUs, and specialized AI chips. It takes models from popular frameworks like TensorFlow, PyTorch, or ONNX, processes them to be highly efficient, and then outputs optimized code that runs faster on your chosen hardware. This is for AI/ML engineers and researchers who need to deploy and accelerate deep learning models.
465 stars. No commits in the last 6 months.
Use this if you are developing or deploying AI models and need to accelerate their performance across different types of hardware accelerators.
Not ideal if you are looking for highly specialized, pre-tuned kernels for a very specific, niche hardware architecture, as this project is still in its early phase.
Stars
465
Forks
53
Language
MLIR
License
Apache-2.0
Category
Last pushed
Aug 20, 2025
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/transformers/bytedance/byteir"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
vllm-project/vllm
A high-throughput and memory-efficient inference and serving engine for LLMs
sgl-project/sglang
SGLang is a high-performance serving framework for large language models and multimodal models.
alibaba/MNN
MNN: A blazing-fast, lightweight inference engine battle-tested by Alibaba, powering...
xorbitsai/inference
Swap GPT for any LLM by changing a single line of code. Xinference lets you run open-source,...
tensorzero/tensorzero
TensorZero is an open-source stack for industrial-grade LLM applications. It unifies an LLM...