I Asked ChatGPT, Claude and DeepSeek to Build Tetris
I Asked ChatGPT, Claude and DeepSeek to Build Tetris
https://www.kdnuggets.com/i-asked-gpt-claude-and-deepseek-to-build-tetris
Publish Date: 2026-01-06 03:02:06
Source Domain: www.kdnuggets.com
The article explores the performance of three leading AI models—Claude Opus 4.5, GPT-5.2 Pro, and DeepSeek V3.2—in generating code for a playable Tetris game. Each model was evaluated on the success of the first attempt, feature completeness, playability, and cost-effectiveness. The Opus 4.5 model delivered a fully functional, visually appealing, smooth-playing Tetris game on the first try, while GPT-5.2 Pro struggled initially but eventually produced a usable game after multiple iterations. In contrast, DeepSeek V3.2 encountered problems like disappearing pieces and buggy controls, requiring significant debugging to make it playable. On cost, DeepSeek V3.2 emerged as the most economical option, though it came with numerous debugging efforts, while Opus 4.5 was best for its immediate, high-quality results. Overall, Opus 4.5 was deemed the best tool for daily coding tasks, while DeepSeek V3.2 served as an affordable, albeit time-consuming option, and GPT-5.2 Pro proved more suitable for complex reasoning tasks rather than simple coding challenges.
Key Points:
1. Opus 4.5 delivered a fully functional Tetris game on the first attempt, displaying high success and the best user experience among the tested models.
2. Despite initial flaws, GPT-5.2 Pro was ultimately able to produce a playable game after additional iterations, though its user experience was subpar.
3. DeepSeek V3.2 required multiple rounds of debugging for producing a playable game, though it offered significant cost benefits.
4. For coding tasks, Opus 4.5 proved most efficient, whereas DeepSeek V3.2, despite cost advantages, required extensive debugging efforts.
5. GPT-5.2 Pro, while costly, is positioned better for more complex, non-pattern data tasks rather than simple coding endeavors like Tetris.
