Kimi K 3.1 Pro vs Opus 5.5: The RESULTS Will SHOCK YOU!

Summary

The video compares Kimi K 3.1 Pro with Claude Opus 5.5 by giving both models the same text-only coding prompts and reviewing the websites they produce.

Models and test setup

• The presenter describes Kimi K 3.1 Pro as an open-weight model with 3 trillion parameters and a 1-million-token active context window. The video also mentions a high-speed variant said to process tokens two to three times faster.
• The presenter cites Artificial Analysis, where Kimi is shown in fourth place with a score of about 55. These are presented as leaderboard results and are not independently verified in the video.
• Kimi was run through OpenCode and OpenRouter at high effort. Opus was run through Claude Code, also at high effort.
• Each model received two prompts:
  1. Build a procedural cyberpunk city in Three.js.
  2. Create a landing page for a fictional spatial-computing headset inspired by Apple Vision Pro.

Results

Cyberpunk city

Kimi produced a navigable city with street, aerial, and cinematic modes, skyscrapers, flying cars, and rain. The presenter liked the overall result but criticized its level of detail, water ripples, and reflections.

Opus’s city was judged substantially more polished, with richer scenery, stronger lighting and reflections, and more convincing cinematic sequences.

Headset landing page

Kimi’s page included working interactions and color choices, but the presenter found its layout and product details less convincing and noted overlapping text.

Opus’s page was praised for its detailed product presentation, smooth animation, color choices, layout, and interactive elements.

Costs and conclusion

Kimi’s reported API costs were approximately $1.57 for the city and $0.63 for the landing page. The video does not provide corresponding Opus costs.

The presenter concludes that Kimi is impressive for an open-weight model, but Opus 5.5 performed much better in these two text-only creative coding tests. The presenter speculates that Kimi might do better with external references or assets, as in examples on Kimi’s blog, but does not test that possibility.

Workflow and product mention

The video demonstrates a side-by-side workflow: submit identical prompts to both coding agents, let them build the projects, then inspect and interact with the results.

It also includes a sponsored segment on TestSprite, described as an autonomous AI software-testing agent. The presenter says it can run front-end or back-end tests through a CLI, produce reports and screen recordings, and connect to GitHub so tests can run on pull requests and block merges when issues are found.

Main speaker and sources

• Speaker: Astro K Joseph, the video’s presenter.
• Sources and tools referenced: Kimi’s official blog, Artificial Analysis, OpenCode, OpenRouter, Claude Code, and TestSprite.