miniF2F VS hasktorch

Compare miniF2F vs hasktorch and see what are their differences.


Formal to Formal Mathematics Benchmark (by openai)


Tensors and neural networks in Haskell (by hasktorch)
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miniF2F hasktorch
4 15
262 1,026
3.9% 1.9%
0.0 7.2
10 months ago 8 days ago
Objective-C++ Haskell
- BSD 3-clause "New" or "Revised" License
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.


Posts with mentions or reviews of miniF2F. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-02-11.


Posts with mentions or reviews of hasktorch. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-03-13.
  • BLAS GPU bindings
    1 project | /r/haskell | 6 Dec 2023
  • Trying out Hasktorch but ghc supported versions conflicts on MacOS M1/2
    2 projects | /r/haskell | 13 Mar 2023
    I assume you are getting I suspect you need to upgrade to GHC 9.2 to work reliably on M1.
  • Is Haskell okay for prototyping machine learning models for research (discovery and exploration)
    4 projects | /r/haskell | 27 Feb 2023
    You might find the Deep Learning From The First Principles tutorials by Bogdan Penkovsky an interesting survey of native Haskell implementations of deep neural networks, and a bit more. It demonstrates some native charting capabilities, and Day 9 uses Hasktorch.
  • Need help Integrating Hasktorch into my Haskell Jupyter environment using Nix
    2 projects | /r/NixOS | 26 Feb 2023
    I'm new to Nix and I'm trying to set up a Jupyter notebook environment for Haskell that includes the Hasktorch package. I'm using the jupyenv project from Tweag as the foundation, and I've been able to get it working with some basic Haskell packages. However, I'm running into issues when I try to add Hasktorch to the mix.
  • [D] Have their been any attempts to create a programming language specifically for machine learning?
    12 projects | /r/MachineLearning | 11 Feb 2023
    That said, there are some things that try to do this. Haskell has a port of torch called HaskTorch that includes this kind of typed tensor shapes, and calls the Z3 theorem prover on the backend to solve type inference. It can get away with this because of the LiquidHaskell compiler extension, which has refinement types capable of solving this kind of typing problem, and is already pretty mature. Dex is a research language from Google that's based on Haskell and built to explore this kind of typechecking. Really you'd want to do this in Rust, because that's where the tradeoff of speed and safety for convenience makes the most sense, but rust is just barely on the edge of having a type system capable of this. You have to get really clever with the type system to make it work at all, and there's been no sustained push from any company to develop this into a mature solution. Hopefully something better comes along soon
  • Haskell deep learning tutorials [Blog]
    4 projects | /r/haskell | 23 Jan 2023
    As rightfully pointed u/gelisam, both Hasktorch and Pytorch are essentially the same things (bindings to existing Torch library). Therefore, it should be generally possible to use existing pretrained models. Here is an example.
  • base case
    2 projects | /r/haskell | 19 Dec 2022
    I think it's likely that is the library you will want to use for AI models, once you feel comfortable with Haskell.
  • looking for simple regression (or classification) library
    5 projects | /r/haskell | 28 Oct 2022
    IF (big if) it turns out you do need deep learning then doing it in Hasktorch could be a fun learning project. The team making it is super nice and responsive, too
  • Haskell for Artificial Intelligence?
    6 projects | /r/haskell | 30 May 2022
    This said, if you want do do deep learning Python is the obvious choice atm, if only for copy-pasting code from examples (however do you know HaskTorch? )
  • GPU-based deep learning in Haskell
    1 project | /r/haskell | 26 Jan 2022

What are some alternatives?

When comparing miniF2F and hasktorch you can also consider the following projects:

tensor_annotations - Annotating tensor shapes using Python types

grenade - Deep Learning in Haskell

einops - Flexible and powerful tensor operations for readable and reliable code (for pytorch, jax, TF and others)

dex-lang - Research language for array processing in the Haskell/ML family

torchtyping - Type annotations and dynamic checking for a tensor's shape, dtype, names, etc.

finito - A constraint solver for finite domains, written in Haskell.

FL - FL language specification and reference implementations

tensor-safe - A Haskell framework to define valid deep learning models and export them to other frameworks like TensorFlow JS or Keras.

Etage - A general data-flow framework featuring nondeterminism, laziness and neurological pseudo-terminology.

jaxtyping - Type annotations and runtime checking for shape and dtype of JAX/NumPy/PyTorch/etc. arrays.

futhark - :boom::computer::boom: A data-parallel functional programming language