Model Card on HF 🤗: https://huggingface.co/FinancialSupport/NanoGPT
NanoGPT Benchmarks
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
What is the LLM Explorer Rank (Score)
NanoGPT Parameters and Internals
| LLM Name | NanoGPT |
| Repository 🤗 | https://huggingface.co/FinancialSupport/NanoGPT |
| Required VRAM | 0.5 GB |
| Updated | 2025-08-18 |
| Maintainer | FinancialSupport |
| Model Type | gpt2 |
| Model Files | |
| Model Architecture | AutoModel |
| License | mit |
| Is Biased | 1 |
| Vocabulary Size | 50257 |
Best Alternatives to NanoGPT
Best Alternatives |
Context / RAM |
Downloads |
Likes |
|---|---|---|---|
| Distil Longformer Base 4096 | 4K / 0.4 GB | 5 | 0 |
| Daedalus 1 | 1K / GB | 3 | 1 |
| Tiny Random Detr | 1K / 0.2 GB | 5 | 0 |
| Opengpt2 Pytorch Backward | 1K / 6 GB | 25 | 1 |
| Opengpt2 Pytorch Forward | 1K / 6 GB | 2 | 1 |
| Finsent Transformer | 0.5K / 0.4 GB | 1 | 1 |
| Bert Chinese L 12 H 768 A 12 | 0.5K / 0.4 GB | 4 | 1 |
| Simbert Chinese Tiny | 0.5K / 0 GB | 6 | 0 |
| Simbert Chinese Base | 0.5K / 0.4 GB | 5 | 0 |
| All MiniLM L12 V2 | 0.5K / GB | 1612 | 4 |
Note: green Score (e.g. "73.2") means that the model is better than FinancialSupport/NanoGPT .
Rank the NanoGPT Capabilities
🆘 Have you tried this model? Rate its performance. This feedback would greatly assist ML community in identifying the most suitable model for their needs. Your contribution really does make a difference! 🌟
What open-source LLMs or SLMs are you in search of? 50729 in total.
Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241124