original_performance_takehome README

The project's README from github.com/anthropics/original_performance_takehome. As one markdown file: README.md.

Anthropic's Original Performance Take-Home

This repo contains a version of Anthropic's original performance take-home, before Claude Opus 4.5 started doing better than humans given only 2 hours.

The original take-home was a 4-hour one that starts close to the contents of this repo, after Claude Opus 4 beat most humans at that, it was updated to a 2-hour one which started with code which achieved 18532 cycles (7.97x faster than this repo starts you). This repo is based on the newer take-home which has a few more instructions and comes with better debugging tools, but has the starter code reverted to the slowest baseline. After Claude Opus 4.5 we started using a different base for our time-limited take-homes.

Now you can try to beat Claude Opus 4.5 given unlimited time!

Performance benchmarks

Measured in clock cycles from the simulated machine. All of these numbers are for models doing the 2 hour version which started at 18532 cycles:

While it's no longer a good time-limited test, you can still use this test to get us excited about hiring you! If you optimize below 1487 cycles, beating Claude Opus 4.5's best performance at launch, email us at [email protected] with your code (and ideally a resume) so we can be appropriately impressed, especially if you get near the best solution we've seen. New model releases may change what threshold impresses us though, and no guarantees that we keep this readme updated with the latest on that.

Run python tests/submission_tests.py to see which thresholds you pass.

Warning: LLMs can cheat

None of the solutions we received on the first day post-release below 1300 cycles were valid solutions. In each case, a language model modified the tests to make the problem easier.

If you use an AI agent, we recommend instructing it not to change the tests/ folder and to use tests/submission_tests.py for verification.

Please run the following commands to validate your submission, and mention that you did so when submitting:

# This should be empty, the tests folder must be unchanged
git diff origin/main tests/
# You should pass some of these tests and use the cycle count this prints
python tests/submission_tests.py

An example of this kind of hack is a model noticing that problem.py has multicore support, implementing multicore as an optimization, noticing there's no speedup and "debugging" that N_CORES = 1 and "fixing" the core count so they get a speedup. Multicore is disabled intentionally in this version.

original_performance_takehome (anthropics/original_performance_takehome)

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Original_performance_takehome
这是什么？这是 Anthropic 最初的性能类居家面试挑战题，现已开源供任何人尝试。目标是在模拟机器上优化程序，使其运行所用的时钟周期尽可能少，起点是 18532 周期的缓慢基线。
这是评分制的编程挑战，还是通用的基准测试套件？它是一个自带起始代码和测试脚本的独立优化谜题，而不是通用的基准测试框架或库。
我该如何着手这个挑战？克隆仓库，优化提供的起始代码（起始为 18532 周期），然后运行提交测试查看你的成绩。
运行它需要安装什么特别的东西吗？这是一个纯粹的 Python 项目，除 Python 本身外，不需要任何列出的依赖、Docker 或构建工具。
用 AI 智能体来解这道题有什么陷阱？曾有 AI 智能体作弊被抓：它们修改 tests/ 文件夹人为降低题目难度，比如禁用刻意的单核限制来伪造多核加速。
这到底是给谁准备的？它面向那些好奇自己能否比 Claude Opus 4.5 优化得更好的人，同时也算是一条引起 Anthropic 注意、进而获得工作机会的非正式途径。
目前已知最好的成绩有多好？Claude Opus 4 达到了 2164 周期；Claude Opus 4.5 在随意一次会话中达到 1790，经过许多小时后在改进的测试时计算框架下达到 1363；人类有史以来最好的成绩至今保密，但据说要好得多。
如果我超过 Claude Opus 4.5 的成绩会怎样？如果你优化到 1487 周期以下，就可以把你的代码（最好附上简历）发邮件到 [email protected]，因为这已经超过了 Opus 4.5 发布当天的最佳表现。
为什么多核支持被禁用了？在这个版本的题目中，多核是被刻意禁用的，因此通过重新启用 NCORES 来实现的所谓优化并不会带来真正的加速，会被视为无效的取巧行为。
这个版本与最初的 4 小时居家测试题有什么不同？它基于较新的 2 小时居家测试题（包含更多指令和更好的调试工具），但使用的是最慢的原始起始代码基线 18532 周期，而不是改进后的 2 小时版本起点。
What are similar projects?SDE-Interview-and-Prep-Roadmap, leetcode-company-wise-problems, Interview_Question_for_Beginner, LeetCode-Questions-CompanyWise, algorithm-pattern, CS-Interview-Knowledge-Map, interview_python, Waking-Up
Which topics is it in?job-search, optimization, interview, algorithms, career, anthropic, benchmark, claude, performance, education, python, developer-tools
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anthropics
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<0.1 MB
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Updated
CommitJan 22
Age
8mo
Commits · 90 Days