nvidia-modelopt
NVIDIAgithub.com/NVIDIA/Model-Optimizer
Nvidia Model Optimizer: A unified library of SOTA model optimization techniques like quantization, pruning, Neural Architecture Search (NAS), distillation, speculative decoding, etc. It compresses deep learning models for downstream deployment frameworks like TensorRT-LLM, Tensor
Updated 3 h ago · first seen 11 Sept 2026
lib_01M29ACMJWRC1DW2CVBHEHNMNN
- Version
- 0.46.1
- T2 · 3 h ago
- Released
- 9 Sept 2026
- T2 · 3 h ago
- License
- Apache-2.0
- T2 · 3 h ago
Specification
- License
- Apache-2.0
Source:PyPI public package metadataT2observed 3 h agomedium
- Repository
Source:PyPI public package metadataT2observed 3 h agomedium
- Author
- NVIDIA Corporation
Source:PyPI public package metadataT2observed 3 h agomedium
- Homepage
- https://github.com/NVIDIA/Model-Optimizer
Source:PyPI public package metadataT2observed 3 h agomedium
- Latest release
- 9 Sept 2026
Source:PyPI public package metadataT2observed 3 h agomedium
- Latest version
- 0.46.1
Source:PyPI public package metadataT2observed 3 h agomedium
- Releases
- 39
Source:PyPI public package metadataT2observed 3 h agomedium
- PyPI
- nvidia-modelopt
Source:PyPI public package metadataT2observed 3 h agomedium
- Pypi license
- Apache-2.0
Source:PyPI public package metadataT2observed 3 h agomedium
- Pypi release at
- 9 Sept 2026
Source:PyPI public package metadataT2observed 3 h agomedium
- Pypi url
- https://pypi.org/project/nvidia-modelopt/
Source:PyPI public package metadataT2observed 3 h agomedium
- Pypi version
- 0.46.1
Source:PyPI public package metadataT2observed 3 h agomedium
- Python classifiers
- Programming Language :: Python :: 3.10, Programming Language :: Python :: 3.11, Programming Language :: Python :: 3.12, Programming Language :: Python :: 3.13
Source:PyPI public package metadataT2observed 3 h agomedium
- Requires python
- <3.15,>=3.10
Source:PyPI public package metadataT2observed 3 h agomedium
Each value shows its source, tier and observation time. Conflicting claims are kept side by side and flagged — never averaged. How AI Atlas records facts →
Provenance
Attributed facts
15
Source tiers
T215
Freshest observation
3 h ago
Conflicts
None
- Developed by
- NVIDIA
As of
Rewind the record: see this entity's attributes exactly as AI Atlas knew them on a given day.
Claim history · Python classifiers
Python classifierspython_classifiers1
| Value | Valid from → to | Status | Source | Confidence | Extractor |
|---|---|---|---|---|---|
| Programming Language :: Python :: 3.10, Programming Language :: Python :: 3.11, Programming Language :: Python :: 3.12, Programming Language :: Python :: 3.13 | → current | current | PyPI public package metadataT2 | medium | deterministic |
Claims are temporal and append-only: a new observation closes the previous claim (valid_to) instead of overwriting it. Conflicting claims from different sources are kept side by side and flagged — never averaged. Methodology →
| Source | Document | Type | Tier | Last observed | Snapshots |
|---|---|---|---|---|---|
| PyPI public package metadata | pypi.org/pypi/nvidia-modelopt/json | package | T2· Quality secondary | 3 h ago | 1 |
Tier 1 = official/primary, 2 = quality secondary, 3 = community, 4 = unverified. Every snapshot is archived; see all sources and the methodology.