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Re:MaxxBench – "Nice DeepSWE score. But is it true?" by anonymous908213 on Saturday November 07, 2026 @05:08PM (#50408513)
Funny, I was just talking about this on HN a couple of days ago[0..2] and had a thread full of anklebiters telling me I'm using Luna wrong. It's clear that the vast majority of people never privately benchmark, because anyone who does knows models like Luna aren't remotely close to the performance the published benchmarks claim, immediately failing when even a single unexpected constraint is introduced, no matter how trivial it is, exactly like Maxxbench's "filename must be loweercase". It's nice to have a public one to point to, but unfortunately every time you publish your private benchmarks they become targets for the next round, and as soon as the next generation of models releases you're back to arguing with people who take benchmaxxed results at face value.

[0] https://news.ycombinator.com/item?id=50373961 [1] https://news.ycombinator.com/item?id=50374111

Re:MaxxBench – "Nice DeepSWE score. But is it true?" by slopinthebag on Saturday November 07, 2026 @05:43PM (#50408738)
you completely missed the point that the "ankle biters" were making - smaller models can still be useful despite being less intelligent. nobody makes the argument that luna is just as smart as opus, but they do make the argument that someone sufficiently knowledgeable and skilled can use smaller models to great effect. just because you and others require the maximally powerful models to make sense of vague, underspecified prompts, to hold your hand throughout the entire development lifecycle and make decisions for you, does not mean we all do.
Re:MaxxBench – "Nice DeepSWE score. But is it true?" by anonymous908213 on Saturday November 07, 2026 @05:46PM (#50408751)
> underspecified prompts

This is the same stupid argument trotted out repeatedly in the thread, and it doesn't hold up to reality. Would you care to explain how adding specifications helps a model that demonstrably ignores specifications? A model that cannot even handle the trivial specification of "the filename must be lowercase" is not going to get better when you add more specifications it ignores. I would actually guess that you're underspecifying relative to me. Perhaps you're happy with whatever slop you get and don't notice Luna's overwhelming incapability to actually provide what one requires, because you don't have requirements.

Re:MaxxBench – "Nice DeepSWE score. But is it true?" by slopinthebag on Saturday November 07, 2026 @06:08PM (#50408926)
yes, your prompts are underspecified relative to the size of changes you are making. you want to write a handful of paragraphs and have a sota model vibe out a +1000loc diff, where it makes all sorts of decisions and architectural/functional choices for you (that you didn't even realise needed to be made). if you use a smaller model, it's just not going to be sufficient. you need to work more iteratively with the model, with more steering and more human judgement. astra/opus can do this relatively well in some domains, especially the relatively simple ones like web, agent harnesses, etc. but someone with intention and skill can make use of the less powerful models, it's just a different workflow (and one that I prefer, when I'm not being lazy).
Re:MaxxBench – "Nice DeepSWE score. But is it true?" by anonymous908213 on Saturday November 07, 2026 @06:13PM (#50408953)
> you want to write a handful of paragraphs and have a sota model vibe out a +1000loc diff

Wrong. What I want Luna to be able to do is ~deterministically make small edits or generations of 1~10 LoC according to a specification, and it literally cannot even do that. It violates specifications no matter how small you aim.

Re:MaxxBench – "Nice DeepSWE score. But is it true?" by slopinthebag on Saturday November 07, 2026 @06:16PM (#50408967)
skill issue mate
Re:MaxxBench – "Nice DeepSWE score. But is it true?" by anonymous908213 on Saturday November 07, 2026 @06:31PM (#50409049)
The specification constrains the implementation details. Repeating the demonstrated example, again: filename must be lowercase is a perfect example of such a specification. You can have a hundred different tasks that require different things but all require that common specification.

> there is nothing deterministic about using llm's for codegen

And if you're okay with that, you're more like a farmer eating the slop meant for his pigs than an engineer. Using Sol Max, you can get near-deterministic output for a much wider range of tasks and specifications. Not all specifications; at a certain degree of sufficiently detailed specification it will begin failing again. But some, which is better than none.

Re:MaxxBench – "Nice DeepSWE score. But is it true?" by slopinthebag on Saturday November 07, 2026 @06:34PM (#50409069)
i just asked luna to write a function that transformed a file path, and threw when the filename wasn't lowercase. completed that task just fine. i see no reason it wouldn't work if i asked it for 99 other functions with that same constraint.

you just aren't using it right man. stick to the big guns, you apparently need it.

Re:MaxxBench – "Nice DeepSWE score. But is it true?" by anonymous908213 on Saturday November 07, 2026 @06:40PM (#50409112)
You are sorely missing the point. You made the constraint the specific and only focus of the task. The example from the OP pertains to non-filename-related-tasks that have an additional specification added on to them. If your filenames need to be lowercase for all tasks, not just specifically filename-related tasks, you start running into problems.

> you're expecting to use it without steering

If I have to manually "steer" every mistake it makes on every trivial task, instead of being able to deterministically eliminate classes of failures so that fixing the task one time ensures that failure never happens again on similar future tasks, it is in fact faster to just type the fucking code myself.

Re:MaxxBench – "Nice DeepSWE score. But is it true?" by slopinthebag on Saturday November 07, 2026 @06:48PM (#50409148)
op's tests are underspecified one-shot tasks. it's entirely expected that smaller models perform poorly.

but your claim was about file name invariants when generating code, especially small amounts of code, which is not what they were doing with DeepSWE, so you've confused two different things.

anyways, this is a pointless argument. if you can't figure out how to effectively use smaller models in your workflow, fine. but don't come on here talking shit about people who can. have fun slopping out yet another ai harness at your startup.

Re:MaxxBench – "Nice DeepSWE score. But is it true?" by anonymous908213 on Saturday November 07, 2026 @06:53PM (#50409179)
While OP's tests are indeed of the vague DeepSWE variety, I still reference them because the exact same failure mode occurs in my own tests even for trivial scope tasks, down to the level of having one single constraint for a variety of <10 LoC tasks. As you say, though, this is a pointless argument, and I'm not going to burn my existing benchmarks to try to convince anyone.
Re:MaxxBench – "Nice DeepSWE score. But is it true?" by za_creature on Sunday November 08, 2026 @05:39AM (#50412053)
> it is in fact faster to just type the fucking code myself.

shhhhhhh, not so loud!

Re:MaxxBench – "Nice DeepSWE score. But is it true?" by easterncalculus on Saturday November 07, 2026 @10:36PM (#50410213)
The leap to a conclusion about points not even mentioned in the original comment could win a gold medal
Re:MaxxBench – "Nice DeepSWE score. But is it true?" by slopinthebag on Sunday November 08, 2026 @12:12AM (#50410577)
what are you even talking about
Re:MaxxBench – "Nice DeepSWE score. But is it true?" by lisplist on Sunday November 08, 2026 @12:16AM (#50410603)
Yeah Luna has been extremely disappointing for me despite what the benchmark numbers show