Life & fun · alternatives · 2026
24 alternatives to Simplexhc – Haskell to LLVM compiler (design phase)
Simplexhc is a Haskell to LLVM compiler currently in the design phase. It is for developers interested in compiling Haskell code to LLVM intermediate representation. The project focuses on creating a compiler that… Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes. Simplexhc – Haskell to LLVM compiler (design phase) launched in 2017; newer entries below may have overtaken it.
- 1

A Pascal to LLVM compiler in Haskell . Contribute to sam46/Paskell development by creating an account on GitHub.
2020 · github.com · its alternatives →
- 2

A complete compiler for a simple language (in less than 150 LoC) - 00_readme.md
2022 · gist.github.com · its alternatives →
- 3

GitHub Gist: instantly share code, notes, and snippets.
2011 · gist.github.com · its alternatives →
- 4

We heard your requests for Haskell and today we're excited to finally announce Haskell as yet another language we support. We've decided to put our focus...
2017 · repl.it · its alternatives →
- 5

Functional programming without the hassle.
2015 · haskellformac.com · its alternatives →
- 6

Merry Christmas, everyone! Now you can compile Haskell code on Windows 11 ARM. It will run full speed if you use UTM/QEmu on Apple silicon. :-) It's a very draft version, but it works well. Any ideas?
2024 · gitlab.haskell.org · its alternatives →
- 7

Simple blockchain server written in Haskell for educational purposes - aviaviavi/legion
2017 · github.com · its alternatives →
- 8

Generate Erlang VM byte code from Haskell. Contribute to kofigumbs/codec-beam development by creating an account on GitHub.
2018 · github.com · its alternatives →
- 9

This is a Python package that allows you to write function signatures to define LLM queries. This makes it easy to mix regular code with calls to LLMs, which enables you to use the LLM for its creativity and reasoning while also enforcing structure/logic as necessary. LLM output is parsed for you according to the return type annotation of the function, including complex return types such as streaming an array of structured objects. I built this to show that we can think about using LLMs more fluidly than just chains and chats, i.e. more interchangeably with regular code, and to make it…
2023 · github.com · its alternatives →
- 10

🔬 a C++ compiler middle-end, using an LLVM backend - artagnon/rhine
2016 · github.com · its alternatives →
- 11

This is rather a mature project. It began out of curiosity: I wanted to test if Haskell FFI was powerful and expressive enough to interconnect C and Haskell code flawlessly. Particularly, if C strings generated inside Nginx can be shared within Haskell code and what must be done to respect their lifetimes etc. Recently, I released version 3.2.0 with revamped README (with a lot of examples) and a new approach to building Haskell handlers using the modernized cabal v2-build for dependencies.
2023 · github.com · its alternatives →
- 12

🂺 A Multiplayer Poker App Crafted with Haskell and React - therewillbecode/poker-maison
2019 · github.com · its alternatives →
- 13

:ramen: A tasty Haskell web and mobile framework. Contribute to dmjio/miso development by creating an account on GitHub.
2017 · github.com · its alternatives →
- 14

See what it’s like to program in a language without null.
2015 · books.thoughtbot.com · its alternatives →
- 15

Great book with a low barrier to entry for learning Haskell
2016 · haskellbook.com · its alternatives →
- 16

Hey HN! We're excited to share our new open-source project, Marvin. Marvin is a high-level library for building AI-powered software. We developed it to address the challenges of integrating LLMs into more traditional applications. One of the biggest issues is the fact that LLMs only deal with strings (and conversational strings at that), so using them to process structured data is especially difficult. Marvin introduces a new concept called AI Functions. These look and feel just like regular Python functions: you provide typed inputs, outputs, and docstrings. However, instead of relying on…
2023 · github.com · its alternatives →
- 17

A BASIC interpreter written in golang. Contribute to skx/gobasic development by creating an account on GitHub.
2018 · github.com · its alternatives →
- 18

2025 · github.com · its alternatives →
- 19

Library for interacting with LLVM IR in pure Go. Contribute to llir/llvm development by creating an account on GitHub.
2017 · github.com · its alternatives →
- 20SI
Hey HN, this is a small Haskell learning project that I wanted to share. It's just a website where you can see how many people write the exact same text as you (thought it was a fun idea). It's built using Scotty, SQLite, Redis and Caddy. Currently it's running in a small DigitalOcean droplet (1 Gb RAM). Using Haskell for web development (specifically with Scotty) was slightly easier than I thought, but still a relatively hard task compared to other languages. One of my main friction points was Haskell's multiple string-like types: String, Text (& lazy), ByteString (& lazy), and each library…
Jan 2026 · subth.ink · its alternatives →
- 21

Haskell for FPGA Hardware Design: Use abstractions like monads and lenses to implement 1970
2021 · unsafeperform.io · its alternatives →
- 22

G'day, HN! I'm one of the maintainers of `llm`. I've been working alongside a trusty group of contributors to bring this project to life, and we're now at a point where we're ready to share it with the world. Large language models (LLMs) are taking the computing world by storm due to their emergent abilities that allow them to perform a wide variety of tasks, including translation, summarization, code generation, and even some degree of reasoning. However, the ecosystem around LLMs is still in its infancy, and it can be difficult to get started with these models. `llm` is a one-stop shop for…
2023 · github.com · its alternatives →
- 23

We’re Robin, Louis, and Thomas. Pipelex is a DSL and a Python runtime for repeatable AI workflows. Think Dockerfile/SQL for multi-step LLM pipelines: you declare steps and interfaces; any model/provider can fill them. Why this instead of yet another workflow builder? - Declarative, not glue code: you state what to do; the runtime figures out how. - Agent-first: each step carries natural-language context (purpose, inputs/outputs with meaning) so LLMs can follow, audit, and optimize. Our MCP server enables agents to run pipelines but also to build new pipelines on demand. - Open…
Oct 2025 · github.com · its alternatives →
- 249H
2015 · 99haskell.org · its alternatives →
Also compare
Ranked by how close each launch is in meaning, then by votes. Prices were read from each product’s own site when checked and can change. Refine with your own description →