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---
license: llama3
---
# 🔹 Key Highlights:
- 29% Fewer Parameters: nyun-c2-llama3-50B comprises approximately 29% fewer parameters than the popular Llama-3-70B.
- Comparable Performance: Despite having far fewer parameters, this model undergoes minimal performance degredation.
- No Fine-Tuning Required: This model undergoes no fine-tuning, showcasing the raw potential of our optimization techniques.
## Pipeline and Collaboration
For insights into the pipeline and the list of methods used to optimize these models, check out our PruneGPT repository (https://github.com/nyunAI/PruneGPT).
We invite companies and organizations interested in joining forces with us to release more such open-source variants to reach out at [email protected].
### Model Performance
| Dataset | nyun-c2-llama3-50B | Meta-Llama3-70B | Meta-Llama2-70B | MBZUAI K2-65B |
| --- | --- | --- | --- | --- |
| MMLU (5-shot) | 78.4 | 79.5 | 69.7 | 67.9 |
| Winogrande (5-shot) | 85.3 | 83.1 | 81.8 | 77.0 |
| BoolQ (0-shot) | 83.9 | 79.0 | 73.1 | 83.0 |
| Hellaswag (10-shot) | 85.4 | 88.0 | 86.9 | 85.5 |
| Arc Challenge (25-shot) | 65.4 | 68.8 | 67.2 | 64.8 |
| GSM8K (5-shot) | 64.7 | 76.9 | 52.6 | 50.2 |
| Average | 77.2 | 79.2 | 71.9 | 71.4 |
- **Developed by:** [Nyun AI](https://nyunai.com/)
- **Repository:** [Github](https://github.com/nyunAI/PruneGPT) |