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Ask HN: What benchmarks do you trust most when comparing large LLMs?

1•QubridAI•5m ago•0 comments

LLMs: Using a single Unix-style tool instead of multiple tools/function calling

https://old.reddit.com/r/LocalLLaMA/comments/1rrisqn/i_was_backend_lead_at_manus_after_building_a...
4•drtse4•10m ago•0 comments

Atlassian Is Not Collapsing – But Its Business Model Might Be

https://www.ctol.digital/news/atlassian-credibility-crisis-not-a-collapse/
1•donutshop•13m ago•0 comments

Ask HN: Resources for a conceptual model of LLMs as applicable to coding?

1•pramodbiligiri•19m ago•0 comments

Cockroach Milk: Yes. You Read That Right

https://www.npr.org/sections/thesalt/2016/08/06/488861223/cockroach-milk-yes-you-read-that-right
1•thunderbong•20m ago•0 comments

Same Chat App, 4 Frameworks: Pydantic AI vs. LangChain vs. LangGraph vs. CrewAI

https://oss.vstorm.co/blog/same-chat-app-4-frameworks/
1•kacper-vstorm•22m ago•1 comments

World Vibe Web: a distributed, open-source app store

https://wvw.dev
2•semioz•24m ago•0 comments

Country Filter for X/Twitter

https://geofilterx.com/
1•hgarg•25m ago•0 comments

Shopify/liquid: Performance: 53% faster parse+render, 61% fewer allocations

https://simonwillison.net/2026/Mar/13/liquid/
1•duck•30m ago•0 comments

Agentic, fully-automated reverse engineering

https://github.com/amruth-sn/kong
1•amruth-•33m ago•0 comments

A record number of objects went into space in 2025

https://ourworldindata.org/data-insights/a-record-number-of-objects-went-into-space-in-2023
1•jonbaer•33m ago•0 comments

National Dex

https://nationaldex.io/
2•timlang1024•34m ago•0 comments

Waller – Game that teaches the fundamentals of drystone walling

https://www.orthodoxmasonry.com/waller
1•helloplanets•35m ago•0 comments

Show HN: High-Precision Companion Matrix Root Finder

https://github.com/ratwolfzero/Poly_Root
1•ratwolf•36m ago•0 comments

Pirate Bananagrams

https://piratebanana.com/
1•hihellokath•39m ago•1 comments

Texico – Learn the principles of programming, for kids

https://www3.nhk.or.jp/nhkworld/en/shows/texico/
2•LeoPanthera•39m ago•0 comments

Ceno, browse the web without internet access

https://ceno.app/en/index.html?
1•mohsen1•40m ago•0 comments

Show HN: From Claude Code to OpenCode – My Evolution in Vibe AI Engineering

1•denis4inet•43m ago•0 comments

Hedley Davis (Amiga 3000, 3DO, Xbox, UDel prof) has died

https://www.daniels-hutchison.com/obituaries/Hedley-Combs-Davis?obId=47519295
1•pcherna•43m ago•1 comments

Private Credit's 'Back Leverage' Is Another Pain Point for Funds

https://www.bloomberg.com/news/articles/2026-03-12/private-credit-s-back-leverage-is-another-pain...
1•petethomas•44m ago•0 comments

FP-Go V2: Enhanced Functional Programming for Go 1.24

https://github.com/IBM/fp-go/blob/main/v2/README.md
1•mroche•48m ago•1 comments

ShowHN: Turn PDFs, notes and spreadsheets into business briefs

https://gixo.ai/gixo-briefs
2•hardikparikh29•51m ago•1 comments

Chrome extension adjusts video speed based on how fast the speaker is talking

https://github.com/ywong137/speech-speed
1•MrBuddyCasino•53m ago•0 comments

The Autonomous Battlefield

https://www.foreignaffairs.com/middle-east/autonomous-battlefield
3•anjel•55m ago•2 comments

I traced $2B in nonprofit grants for Meta and Age Verification lobbying

4•theseusares•56m ago•1 comments

Dwarkesh on the Anthropic situation

https://www.youtube.com/watch?v=KBPOTklFTiU
1•musha68k•56m ago•0 comments

Emergency sirens in SF won't sound alarm even during Iranian drone threat

https://www.sfgate.com/bayarea/article/emergency-siren-iran-drone-22073043.php
4•mikhael•1h ago•0 comments

Show HN: SiMM – Distributed KV Cache for the Long-Context and Agent Era

https://github.com/scitix/SiMM
1•SherryWong•1h ago•0 comments

Palantir CEO Makes Confession on Disrupting Democratic Power

https://newrepublic.com/post/207693/palantir-ceo-karp-disrupting-democratic-power
6•mindracer•1h ago•2 comments

Feng Shui Refactoring

https://alganet.github.io/blog/2026-03-12-20-Feng-Shui-Refactoring.html
1•chmaynard•1h ago•0 comments
Open in hackernews

Ask HN: Is there a general, multi-PL programming task dataset?

1•quartztz•10mo ago
Hello!

Being a student interested in PL design, I have had this idea floating around for a while: the gist is finding out what programming languages LLMs might be the most proficient in, to study their design choices and syntactic features with the goal of designing the perfect language for LLMs. This is, of course, gimmicky, but I entertained the idea for a while as a fun afterschool project.

The challenge is: what would be the best way to evaluate programming performance _in specific languages_? There are two main hypotheses here:

1. There are intrinsic syntactic/structural features that the transformer architecture is uniquely able to parse/reproduce/understand best, leading to higher quality code generated. For example: Lisp dialects make parsing code structure and blocks very easy, so one could assume an LLM can "understand their code better" 2. There is so much Python/JS out there that the question isn't even worth asking, and the performance in those will beat whatever other language you throw at it. This is probably not as much of a point thanks to newer transformer architectures but the question is still up.

I suspect the answer can be made somewhat interesting by considering performance relative to language popularity, but the ground question is: is there a general dataset containing different programming challenges, of varying difficulty, in multiple languages, with standard solutions? I couldn't find anything when I looked around, but I might have missed something obvious. It wouldn't be impossible to build a simple website to crowdsource, but I'm thinking that if I missed something obvious I'd rather find out early than late. Also, if you have any input on the project itself, I'd love to hear your ideas!

Comments

Someone•10mo ago
> For example: Lisp dialects make parsing code structure and blocks very easy, so one could assume an LLM can "understand their code better"

I would expect the reverse: lisp has no syntactic sugar, making it harder for a LLM to glue code fragments together in a way that produces valid lisp code. Even guaranteeing that parentheses are correctly nested already can be a challenge.

As to a set of programs: they aren’t exactly what you’re looking for, but I would consider https://projecteuler.net (does not contain solutions, but searching for project Euler solutions” finds some) or https://benchmarksgame-team.pages.debian.net/benchmarksgame.

sargstuff•10mo ago
Very open ended questions. Geeks for Geeks loosely organized around computer science topics of study : https://www.geeksforgeeks.org/

nit-pick details:

Ignoring hardware differences, "performance" comparisons can be based on differences between algorithm(s) used vs. how algorithm is implimented. For a given language, "algorithm implimentation performance" can be defined as the trade-offs on how a a given algorithm is implimented in a language (compared to other programming languages, but also easy use/flexibility based on 'language generation level -> https://www.geeksforgeeks.org/generation-programming-languag... )

----------------------

1) General computation language specialty 'modules' not withstanding; "languages" are built/optimised around core algorithmic concepts / anticipated area/concentration of targeted professional environment. aka opencl (gpu), R (statistics), Lisp (engineering design), C (OS level), sql (data selection), jasper reports, cobol (business), etc. Languages tend to be 'popular' because of the ecosystem provided around/for a given language.

snarky side note -> can always write a more standard language that compiles to an esolang & provide appropriate emacs/vim/sed/spacemacs ide support.: https://esolangs.org/wiki/Main_Page

  LLM's are very useful at curating information and recognizing/summarizing "statisical" relevance. aka apl is great for engineering mind set, not so good for business use cases aka cobal.  LLM might recognize a language for a given user that combines commonly used 'apl' aspecs of user and commonly used 'cobal' aspecs of user and recommend a language(s) with suitable commonalities for given user. 


2) Search engine topic 'coding challenges' 'algorithmic coding challenges' brings up many types of answers/sites for honing one's coding skills (various languages, beginner to expert, etc). Coding 'algorithms' vs. coming up with algorithm(s) to code is sort of a side aspect. Also differences in 'competition' challenges vs. 'technical challenges' (aka 512 c64 vs. 1 raspberry pi) ; vs. "computer science coding challenges" vs. 'computational genomic challenges'

     ?? how easy / hard based on 'profession' aka artist vs. software designer 20 years experience programming in scheme; environment -- NASA vs. google vs. insurance company.

   ?? from scratch : https://synoptek.com/insights/it-blogs/10-challenges-every-software-product-developer-faces/

   ?? based on industry standards ?? ; just trying to keep skills honed ??