flash-linear-attention vs caveman
A neutral, constraint-first comparison - live GitHub stats and typed relationships, not marketing.
| flash-linear-attention | caveman | |
|---|---|---|
| Tagline | Efficient implementations for emerging model architectures | Cuts 65% of tokens in AI coding agent responses. |
| Stars | 5.3k | 86k |
| Forks | 571 | 4.8k |
| Open issues | 67 | 370 |
| Language | Python | JavaScript |
| License | MIT | MIT |
| Last pushed | Jul 7, 2026 | Jul 3, 2026 |
| Categories | LLM Frameworks | Developer Tools, LLM Frameworks |
flash-linear-attention
Flash Linear Attention provides hardware-efficient building blocks, training-ready layers, and components for modern sequence models, supporting various attention mechanisms and hybrid LLM architectures.
Python
caveman
A skill/plugin for various AI agents, including Claude Code and other platforms, reducing output tokens for more concise, direct communication while maintaining accuracy.
JavaScript