# huggingface/optimum-nvidia

Repository: https://github.com/huggingface/optimum-nvidia
Canonical: https://ross.abutalabs.com/products/optimum-nvidia
Language: Python
License: Apache-2.0
License Family: permissive
Last push: 2026-05-26T10:32:41+00:00

## Health v2 (maintenance only)
Score: 58/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 84, release rhythm 16, longevity 75
- inputs: {"age_days": 1062, "days_push": 99, "days_rel": 587, "gap_med": 128, "n_releases_24m": 2}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1037, forks 103 (observed 2026-08-28T04:03:19.531032+00:00)

## What it is
Optimum-NVIDIA is a Python library that bridges Hugging Face Transformers with NVIDIA TensorRT-LLM for highly optimized LLM inference on NVIDIA GPUs. It lets users run models like LLaMA 2 significantly faster by changing a single line in existing transformers code.

## Use cases
- run LLM inference faster on NVIDIA GPUs
- accelerate text generation with TensorRT-LLM
- use fp8 quantization for LLM inference
- drop-in replacement for transformers pipelines
- serve LLaMA models at high tokens/second
- optimize Hugging Face models for Hopper and Ampere GPUs

## When to choose
- you already use Hugging Face transformers and want faster inference on NVIDIA GPUs
- you need maximum LLM throughput with minimal code changes
- you run on Linux with CUDA 12.6 and supported NVIDIA hardware

## When to avoid
- you are not on NVIDIA GPUs or Linux
- you need a stable, mature production library
- you want CPU or multi-vendor GPU inference

## Facets
- artifact type: library
- maturity: experimental
- function: llm-inference, machine-learning, sdk
- domain: large-language-models, machine-learning, gpu-computing
- platform: python
- tags: tensorrt-llm, nvidia, hugging-face, transformers, fp8, text-generation, linux, gpu, docker

## Member repositories
- huggingface/optimum-nvidia (main) score 58

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:03:19.531032+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T07:04:23.561841+00:00, confidence not recorded.
  - readme: https://github.com/huggingface/optimum-nvidia (fetched 2026-08-28T04:03:19.531032+00:00, sha b105ce36597b)
  - registry_pypi: https://pypi.org/pypi/optimum-nvidia/json (fetched 2026-08-29T13:05:31.726492+00:00, sha fcdc36032fdd)
- Data as of 2026-08-30T08:39:29.467469+00:00.