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Explore Kimi K3.1 Pro and Opus 5.5 Made the Same 13 Apps (Raw Results) with 74,791 views, 961 likes, and 93 comments. Experience the impact of this video content that has captured audience attention.

Kimi K3.1 Pro vs Claude Opus 5.5 on 13 long-horizon agentic coding tasks. Both models ran in the same Claude Code harness, with the same prompts, the same effort setting and the same grading scripts. Only the model string changed. Kimi K3.1 Pro is listed at half the price of Opus 5.5 ($2 / $10 per million input / output tokens vs $4 / $20). Across all 13 tasks it cost $45.91 against Opus's $83.46, about 55% of the bill, and between 28% and 93% depending on the task. The reason is caching: about 98% of everything both models read came from the cache, and cached tokens cost $0.20 per million on both. What I tested: - Research replication: Growing Neural Cellular Automata, PPO from scratch on MuJoCo Ant, a Milky Way and Andromeda collision - 3D in code with no 3D software: an SDF dragon from one concept image, a living planet, a portal physics lab, a mechanical watch - An external tool: two Blender scenes built and refined from Python - Front end: three websites rebuilt from a single screenshot, and a site built to a 33-rule spec Some results: - Ant-v5: Opus 7,435 vs Kimi 5,023 (Opus trained 4x as many steps) - SDF dragon silhouette match: Opus 0.85 / 0.82 vs Kimi 0.65 / 0.62 - Galaxy: Kimi picked the approximate method, and its angular momentum changed by 31.85% - Blender reading room: Kimi's image is the stronger one in my view, at 77% of Opus's cost - 33-rule brief: Opus passed 33/33; Kimi passed 31/33 but reported 33/33 Chapters: 0:00 Kimi K3.1 Pro vs Opus 5.5 1:23 What a long-horizon task is 2:00 The four task groups 2:27 Setup: same Claude Code, only the model changes 3:22 Research: Growing Neural Cellular Automata 4:36 Reinforcement learning: Ant vs HalfCheetah 5:42 Ant vs Ant rematch 6:46 Galaxy collision and energy conservation 8:35 3D in code: the SDF dragon 10:18 WebGL worlds: planet, portal and watch 11:39 Why Kimi took 3-4x longer on 3D 13:16 Blender: reading room and keyboard 15:54 Front end: websites from one screenshot 16:58 The 33-rule brief and the false 33/33 18:28 The real cost of all 13 tasks 19:36 Why half price is not half the bill: caching 21:58 Caveats 22:57 Four rules for using Kimi K3.1 Pro in Claude Code Credits: - SDF dragon experiment: Keenan Crane. Concept art: Inigo Quilez (CC0). - Growing Neural Cellular Automata: Mordvintsev et al., Distill 2020. https://distill.pub/2020/growing-ca/ - Kimi K3.1 Pro pricing: https://platform.kimi.ai Gemini 4 Argon on many of the same tasks: https://youtu.be/yksrd5uNxcw #Kimi #ClaudeCode #AIcoding

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