在 atomic_chat 桌面应用中，Grok 4.5 免费版在机器人对战、液压机压碎和卡车跳峡谷三个浏览器物理演示中达到 GPT-5.6 Sol 水平。测试要求模型生成自包含 HTML5 Canvas 代码，处理重力、碰撞检测和帧控制。输出对比：GPT-5.6 Sol 12.9K tokens/$0.51（约7分钟），Grok 4.5 10.8K tokens/免费（约5分钟），Muse Spark 1.1 26.8K tokens/$0.12（约7.5分钟），GLM 5.2 10.9K tokens/$0.02（约12分钟）。物理演示暴露了普通编码基准隐藏的弱点：模型可能用更多 token 描述丰富场景，却难以维持跨帧的力、动量、碰撞时序和可信物体行为。Grok 4.5 目前仅通过 Grok Build 和 Cursor 免费使用。
Grok 4.5 reached GPT-5.6 Sol level across 3 browser physics demos for free.
Prompts were for robot combat, hydraulic pressing, and a canyon-jumping truck.
Test was done on atomic chat (@atomic_chat_hq), a desktop app that runs LLMs locally.
Each answer had to package rendering and physics inside self-contained HTML5 canvas code.
These tasks force generated JavaScript to draw frames, apply gravity, detect collisions, and manage controls.
Outputs:
GPT-5.6 Sol: 12.9K tokens, $0.51 (~7 min)
Grok 4.5: 10.8K tokens, $0 (~5 min)
Muse Spark 1.1: 26.8K tokens, $0.12 (~7.5 min)
GLM 5.2: 10.9K tokens, $0.02 (~12 min)
Physics demos expose a weakness that ordinary coding benchmarks often hide: a model can spend more tokens describing a richer scene while still failing the hard part, which is maintaining force, momentum, collision timing, and believable object behavior across frames.
(Note, Grok 4.5 is currently free only through Grok Build and Cursor)
Grok 4.5 performed GPT Sol level for free! We gave 4 models the same prompt: build three self-contained HTML5 canvas scenes with real physics demos Prompts: -robot deathmatch, Tombstone vs Minotaur -a hydraulic press flattening stuff on a conveyor -a semi truck jumping a canyon Outputs: GPT-5.6 Sol: 12.9K tokens, $0.51 (~7 min) Grok 4.5: 10.8K tokens, $0 (~5 min) Muse Spark 1.1: 26.8K tokens, $0.12 (~7.5 min) GLM 5.2: 10.9K tokens, $0.02 (~12 min) Grok 4.5 handled all three scenes genuinely well and got surprisingly close to GPT-5.6 this round. On top of that, it ran on the free tier. GPT-5.6 Sol, the frontier model, put out solid but not standout work. GLM 5.2 rendered all three scenes for pennies, but it came out the roughest of the four. Meta's new Muse Spark burned the most tokens yet still stayed cheap, delivering an average result.在 X 查看被引用的帖子
来源：Rohan Paul · x.com