在atomic.chat桌面应用的物理模拟测试中，腾讯混元Hy3仅用29,757 tokens（成本$0.006）即实现与Gemini 3.5（23,300 tokens，$0.21）相当的保龄球、空气曲棍球和台球HTML5 Canvas物理效果，碰撞与动量传递真实无穿模。GLM-5.2（25,454 tokens，$0.07）编码能力较强但物理表现一般；DeepSeek-V4消耗50,600 tokens（$0.009）却输出最弱的物理场景。
More good news for local LLMs.
Tencent’s new Hunyuan Hy3 reaches Gemini 3.5-level physics quality for 35x less cost.
Test was done on atomic[.]chat, a desktop app that runs LLMs locally.
The prompt asked 4 models to build bowling, air hockey, and pool simulations. The harder part was preserving physical cause and effect.
A strike needs collision timing, mass transfer, pin rotation, friction, and believable scattering.
A pool break exposes the same weakness, because every wrong angle compounds immediately.
Interestingly, DeepSeek-V4 spent the highest number of tokens (50,600 ), yet produced the weakest visual physics in this test.
New Hunyuan Hy3 hits Gemini 3.5 quality on physics for 35x cheaper! We gave 4 models the same prompt: build three self-contained HTML5 canvas scenes with real physics demos Prompts: - A bowling ball knocking down the pins - An air hockey rally that ends in a goal - A pool break scattering the rack Outputs: Hunyuan Hy3: 29,757 tokens, $0.006 Gemini 3.5: 23,300 tokens, $0.21 GLM-5.2: 25,454 tokens, $0.07 DeepSeek-V4: 50,600 tokens, $0.009 Tencent's Hy3 matched Gemini across all three: clean collisions, the puck bounced true, the pins scattered like a real strike, the rack broke with real momentum, nothing clipped or floated. GLM is genuinely strong on pure coding tasks, but the moment the job steps outside clean code it gives way. DeepSeek was the letdown, it burned the most tokens of anyone (50k, almost 2x Hy3) and still turned in the weakest scenes在 X 查看被引用的帖子
来源：Rohan Paul · x.com