SWE-bench is the coding benchmark that measures whether an AI can fix real GitHub issues, not just write clean functions.
Most coding benchmarks test the easy version of the job: here is a function signature, now write the function. Real software engineering is messier. You get a vague bug report, you dig through an unfamiliar repo, and you fix the right thing without breaking everything else. We break down how SWE-bench tries to measure that, why the Verified subset exists, and the reason even it is starting to lose its signal.
? What you'll learn:
1️⃣ Why HumanEval and CodeForces-style benchmarks only test the clean version of coding
2️⃣ How SWE-bench turns real GitHub issues into a test the model has to actually solve
3️⃣ The difference between SWE-bench Full, Lite, and Verified, and why Verified was needed
4️⃣ How SWE-bench compares to LiveCodeBench, Aider Polyglot, and Terminal-bench
5️⃣ What saturation and contamination mean, and why OpenAI walked away from Verified
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⏰ Timestamps:
00:00 - What HumanEval and CodeForces actually test
00:52 - What SWE-bench measures
02:05 - SWE-bench Full, Lite, and Verified
02:31 - Why SWE-bench Verified exists
03:20 - SWE-bench vs LiveCodeBench, Polyglot, and Terminal-bench
03:55 - Saturation and contamination
04:26 - Why SWE-bench still matters and what comes next
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