by AlexBuz · Agent Tool · ★ 315
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
llama-zip llama-zip is a lossless compression utility that leverages a user-provided LLM (large language model) as the probabilistic model for an arithmetic coder. This allows llama-zip to achieve high compression ratios on structured or natural language text, since few bits are needed to encode tokens that the model predicts with high confidence. By employing a sliding context window, llama-zip is not limited by the context length of the LLM and can compress strings of arbitrary length. Furthermore, by encoding invalid UTF-8 bytes using code points in Unicode's private use areas, llama-zip is not limited to text inputs and can handle arbitrary binary data, albeit with reduced compression ratios compared to text inputs. Compression Performance In the table below, the compression ratios achieved by llama-zip on the text files of the Calgary Corpus (as well as on llama-zip's own source code, ) are compared with other popular or high-performance compression utilities. Compression ratios are calculated by dividing the number of bytes in the uncompressed input by the number of bytes in the compressed output, so higher values indicate more effective compression.
| Stars | 315 |
| Forks | 18 |
| Language | Python |
| Category | Agent Tool |
| Quality Score | 66.719362911354/100 |
| Last Updated | 2026-06-16 |
| Created | 2024-06-06 |
| Platforms | python |
| Est. Tokens | ~16k |
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llama-zip is LLM-powered lossless compression tool. It is categorized as a Agent Tool with 315 GitHub stars.
llama-zip is primarily written in Python.
You can find installation instructions and usage details in the llama-zip GitHub repository at github.com/AlexBuz/llama-zip. The project has 315 stars and 18 forks, indicating an active community.
The top alternatives to llama-zip on Agent Skills Hub include claude-forge, excalidraw-diagram-skill, agent-skills. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.