NVIDIA/earth2studio
Open-source deep-learning framework for exploring, building and deploying AI weather/climate workflows.
Build with Backblaze B2
SDKs, agent skills, IDE extensions, and reference pipelines from Backblaze Labs. All open source.
Loading star history...
Where it stands
Rank, growth pace and release cadence relative to everything GStars tracks.
3 releases in the last 90 days, the latest 7 days ago, with 66 contributors on GitHub.
Use Cases & Benefits
- Provides a Python-based framework to build, explore, and deploy AI-driven weather and climate science workflows.
- Offers a unified API to seamlessly integrate diverse AI models, data sources, and tools for flexible and composable weather and climate pipelines.
- Use for rapid prototyping and deployment of state-of-the-art AI weather forecast models like FourCastNet3 and GraphCast.
- Use for developing diagnostic pipelines to predict specific climate phenomena such as precipitation, tropical cyclones, and solar radiation.
- Use for accessing and processing heterogeneous weather and climate datasets from operational models, reanalysis, and AI-generated sources with optimized data handling.
Should you depend on it?
License terms, project hygiene and risks, from GitHub metadata and GStars' snapshots.
License
Apache 2.0
Permissive: commercial use, modification and redistribution are allowed with attribution; includes an explicit patent grant from contributors.
Community files
- README: present
- Contributing guide: present
Watch-outs
No watch-outs from GStars' checks.
General guidance from repository metadata, not legal advice. How we score
From the README
Earth2Studio is a Python-based package designed to get users up and running with AI Earth system models fast. Our mission is to enable everyone to build, research and explore AI driven weather and climate science.
Running AI weather prediction can be done with just a few lines of code.
Daily snapshots
Stars gained per day, and how forks and open issues moved, from GStars' daily snapshots
Forks
290+50
Open issues
47+11
Compared with peers in AI
Fastest-growing repositories GStars tracks in this cohort for the week of Nov 1, by 7-day star growth
| Repository | Stars | +7d | Health | Last release |
|---|---|---|---|---|
| thedotmack/claude-mem | 113.6K | +8.8K | 35 | today |
| D4Vinci/Scrapling | 98.1K | +6.9K | 65 | 1 day ago |
| Leonxlnx/taste-skill | 110.7K | +5.2K | 55 | 1 day ago |
| calesthio/OpenMontage | 77.2K | +4.2K | 40 | — |
| heygen-com/hyperframes | 79.6K | +4.1K | 45 | today |
| NVIDIA/earth2studio | 1.2K | — | 60 | 7 days ago |
| Category median | 98.1K | +5.2K | 45 | — |
Also by NVIDIA
Other repositories from this maintainer that GStars tracks
- Python24.5K stars
SkillSpector
Security scanner for AI agent skills. Detect vulnerabilities, malicious patterns, security risks, prompt injection, data exfiltration, and supply-chain risks in Claude Code, Codex, and MCP skills before you install them.
- TypeScript22.8K stars
NemoClaw
Run agents like Hermes, LangChain Deep Agents, and OpenClaw more securely inside NVIDIA OpenShell with managed inference
- Rust21.2K stars
OpenShell
OpenShell is the safe, private runtime for autonomous AI agents.
- Python18.3K stars
Megatron-LM
Ongoing research training transformer models at scale
- Python15.0K stars
TensorRT-LLM
TensorRT LLM provides users with an easy-to-use Python API to define Large Language Models (LLMs) and supports state-of-the-art optimizations to perform inference efficiently on NVIDIA GPUs. TensorRT LLM also contains components to create Python and C++ runtimes that orchestrate the inference execution in a performant way.
Discover Repositories
Search across tracked repositories by name or description