# 本地LLM游戏开发对决：Gemma 4 31B 在效率与逻辑上胜过 Qwen 3.6 27B

- 来源：Chubby♨️ (@kimmonismus)
- 发布时间：2026-05-01 04:02
- AIHOT 分数：60
- AIHOT 链接：https://aihot.virxact.com/items/cmolx83ay031esll9jv2987xy
- 原文链接：https://x.com/kimmonismus/status/2049942439147004196

## AI 摘要

在@atomic_chat_hq平台的本地LLM游戏开发竞赛中，Gemma 4 31B与Qwen 3.6 27B于MacBook Pro M5 Max上对决。尽管Qwen生成速度更快（32 tokens/秒）且回答更具创意，但Gemma仅用3分51秒和6209个token，输出了更简短、清晰、逻辑性强的答案。在具体的吃豆人游戏逻辑实现上，Gemma在点击反应、与墙壁/幽灵的交互及粒子效果处理方面表现更优。作者强调此为单次测试，Qwen或可通过调整设置提升表现，并邀请社区验证。

## 正文

/1 Gemma 4 31B just crushed Qwen 3.6 27B in a local LLM gamedev contest inside @atomic_chat_hq （prompt is below）

Device： MacBook Pro M5 Max， 64GB RAM

Results：
Qwen 3.6 27B： 32 tokens/sec · 18m 04s · 33，946 tokens
Gemma 4 31B： 27 tokens/sec · 3m 51s · 6，209 tokens

So what is more important： tokens per second， or the quality of the final answer？

Qwen made a very long response and showed more creativity and visual style. But Gemma gave a shorter， clearer， and more logical answer in much less time. In this one-shot Pac-Man gamedev contest， Gemma 4 31B was the clear winner. Its game logic was stronger： click reactions were smoother， and it handled interactions with elements like walls， ghosts， and particle effects better.

But this was only one test. Maybe Qwen 3.6 27B can show better results with better settings. Open the comments， try our prompt， and share your result below.