It was never that great, it seems. For all of 2025 there was virtually no improvement in the rate at which models produced quality code. They only got better at passing automated tests. https://entropicthoughts.com/no-swe-bench-improvement
SWE-bench Verified no longer measures frontier coding capabilities
111–120 of 209 posts
Re: SWE-bench Verified no longer measures frontier coding capabilities
#112I think an Olympiad format is better. But the financial incentive is such that it might be near impossible to stop leaks. I.e. A panel comes up with a series of problems. Like advent of code or project Euler but more complex and constricted. Benchmark outcomes could be performance points and measure of cost, time to solution (well token count really). A couple times per year it's run. It avoids overfitting. Overtime…
Further, olympiad style benchmarks are arguably easier to contaminate / memorize unless you refresh it regularly; but that goes for SWE-bench too.
Re: SWE-bench Verified no longer measures frontier coding capabilities
#113This feels very much like "we are now moving the goal posts".
Re: SWE-bench Verified no longer measures frontier coding capabilities
#114Earlier quoted context omitted.
I have worked on similar problems. See e.g. [1]. The LLMs I have tested have terrible world models and intuitions for how actions change the environment. They're also not great at discerning and pursuing the right goals. They're like an infinitely patient five-year old with amazing vocabulary. [1]: https://entropicthoughts.com/updated-llm-benchmark (more descriptions available in earlier evaluations referenced from t…
I'm going to ignore all that and tell my developers working in complicated codebases that they have to use AI. I'm sure comprehending side effects in a world building text adventure is completely different that understanding spaghetti code
Re: SWE-bench Verified no longer measures frontier coding capabilities
#115Re: SWE-bench Verified no longer measures frontier coding capabilities
#116Benchmarks/evals are really hard and they become harder when there’s huge incentive to game them at an industry scale. ELT-Bench is another recent example. It was the first serious attempt at a benchmark for data engineering workloads, published about a year ago. A few days ago, a follow-up paper from a group that includes one of the original authors audited the benchmark itself. The team gfound that the benchmark ha…
It’s just hard to make them not part of the training data. We see this a bit with BrowseComp plus and other deep research datasets. Not because frontier labs are trying to cheat, but just from training on the full web. You need new datasets perpetually.
Re: SWE-bench Verified no longer measures frontier coding capabilities
#117Earlier quoted context omitted.
It’s just hard to make them not part of the training data. We see this a bit with BrowseComp plus and other deep research datasets. Not because frontier labs are trying to cheat, but just from training on the full web. You need new datasets perpetually.
Or hidden benchmarks, though it's then harder to get people to trust the results.
Re: SWE-bench Verified no longer measures frontier coding capabilities
#118Earlier quoted context omitted.
Both of them look pretty old?
code clash I think would be quite hard to game or contaminate unintentionally; considering that models need to compete against one another
An industry-standard benchmark shouldn't be hosted or designed by a lab producing the models, regardless.
Re: SWE-bench Verified no longer measures frontier coding capabilities
#119That doesn't help for measuring coding ability specifically (you fundamentally need a code-correctness oracle), but for capability axes where the "answer" is a stated position rather than a verifiable fact, public + stable can still be useful. The SWE-bench problem isn't really "public", it's "public + has a fixed correct answer".
Re: SWE-bench Verified no longer measures frontier coding capabilities
#120> We audited a 27.6% subset of the dataset that models often failed to solve and found that at least 59.4% of the audited problems have flawed test cases that reject functionally correct submissions, despite our best efforts in improving on this in the initial creation of SWE-bench Verified. Is this saying a quarter* of the questions and answers were wrong, this whole time?! If so, how was this ever, in any way, a va…
> Is this saying a quarter of the questions and answers were wrong, this whole time?! No, they're saying 59.4% of the 27.6% subset had flawed test cases I think. > If so, how was this ever, in any way, a valid measurement? Benchmarks essentially aren't, for practical concerns anyways. They don't represent your use case, and they don't represent any and all use cases, they're valid for measuring exactly what's include…
That being said, they didn't audit the other 72.4%, right? So it's likely that there are way more flawed problems throughout the full set?