Independent AI Researcher | Energy Efficiency & Sustainable Computing
| Asset | Type | Impact | Link |
|---|---|---|---|
| ๐ค HuggingFace Optimum Integration | Official Documentation | Trusted by thousands of HF developers | View Docs โ |
| ๐ Complete Energy Dataset | Research Benchmark | 360+ configurations, 5 precision methods | Explore Data โ |
| ๐ฆพ EcoCompute AI Assistant | Interactive Tool | Conversational energy advisor on ClawHub | Try EcoCompute โ |
| ๐๏ธ MLCommons Power WG Discussion | Industry Recognition | Invited to contribute to MLPerf power measurement standards | View Discussion โ |
Quantization only saves energy for models > 3.2โ4.6B parameters.
For smaller models, FP16 is actually more energy-efficient.
โ Measured on RTX 4090D, RTX 5090, A800 with NVML power sampling.
This finding challenges the default assumption that "quantize everything = green." Our benchmark data is open and reproducible.
Key Findings:
- NF4 crossover: 3.2โ3.9B parameters (hardware-dependent)
- INT8 crossover: 4.0โ4.6B parameters (hardware-dependent)
- Below threshold: Quantization adds 25โ55% energy overhead
- Above threshold: Quantization saves 15โ23% energy
| ๐ Live Demo | EcoCompute Dashboard โ |
| ๐ What it does | Compare AI models by Accuracy ร Cost ร Carbon in one dashboard |
| โก Data source | Real GPU benchmarks โ PyTorch 2.10 + CUDA 12.8, 10 runs per config |
| Achievement | Details |
|---|---|
| ๐ค HuggingFace Official | Quantization energy findings integrated into Optimum documentation |
| ๐๏ธ MLCommons Invited | Contributing to MLPerf Power Working Group on quantization energy metrics |
| ๐ Open Dataset | 360 configurations, 270 analyzed + 90 FP8 reserved for future work |
| ๐ Zenodo Archive | Permanent DOI: 10.5281/zenodo.18900289 |
| ๐ Research Paper | "When Does Quantization Save Energy?" โ arXiv submission in progress |
- โ HuggingFace Integration โ Official documentation published
- โ MLCommons Engagement โ Invited to Power Working Group
- ๐ arXiv Publication โ Seeking endorsement for cs.LG submission
- ๐ก๏ธ VS Code Extension โ Real-time energy linting before code merges
- ๐ค Enterprise Pilots โ Seeking design partners for carbon-aware CI/CD
I'm looking for design partners, early adopters, arXiv endorsers, and grant sponsors to take EcoCompute from research to production.
| Action | Link |
|---|---|
| โญ Star the repo | quantization-energy-crossover |
| ๐ Try the demo | Live Dashboard โ |
| ๐ง arXiv Endorsement | Email me โ |
| ๐ค Become a design partner | Email me โ |
| ๐ผ Invest / Grant | Email me โ |
- Research Paper: "When Does Quantization Save Energy? Empirical Analysis of the Energy-Efficiency Crossover Effect Across GPU Generations"
- Dataset: GitHub | Zenodo DOI
- HuggingFace Docs: Optimum Energy Efficiency Guide
- MLCommons Discussion: Issue #2558
๐ Making AI development more sustainable, one model at a time.