Dev tools · alternatives · 2026
24 alternatives to Axiom – C++ tensor library with NumPy API and Metal GPU support
I've been building a C++ tensor library that tries to bring the ergonomics of NumPy/PyTorch to native code. The main goals were: - Familiar API (operator overloading, method chaining, same function names) - Actual GPU acceleration via Metal (not just matmul, but all ops) - Cross-platform with SIMD on x86/ARM/RISC-V via xsimd - einops-style rearrange/reduce patterns It started because I wanted NumPy's API but needed to deploy on edge devices without Python. Ended up going deeper than expected (28k LOC+) into BLAS backends, memory views, and GPU kernels. Some things I'm…
Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes.
- 1
Hi HN, Over the past few months, I've been building `dsc`, a tensor library from scratch in C++/CUDA. My main focus has been on getting the basics right, prioritizing a clean API, simplicity, and clear observability for running small LLMs locally. The key features are: - C++ core with CUDA support written from scratch. - A familiar, PyTorch-like Python API. - Runs real models: it's complete enough to load a model like Qwen from HuggingFace and run inference on both CUDA and CPU with a single line change[1]. - Simple, built-in observability for both Python and C++. Next on the roadmap is…
2025 · github.com · its alternatives →
- 2
TensorZero▲307Hi HN! We're Gabriel & Viraj, and we're excited to open source TensorZero. To be a little cheeky, TensorZero is an open-source platform that helps LLM applications graduate from API wrappers into defensible AI products. 1. Integrate our model gateway 2. Send metrics or feedback 3. Unlock compounding improvements in quality, cost, and latency It enables a data & learning flywheel for LLMs by unifying: • Inference: one API for all LLMs, with <1ms P99 overhead • Observability: inference & feedback → your database • Optimization: better prompts, models, inference strategies • Experimentation:…
2025 · github.com · its alternatives →
- 3
An on-premises, bare-metal solution for deploying GPU-powered applications in containers - emergingstack/es-dev-stack
2016 · github.com · its alternatives →
- 4
Ultra-fast and customizable Python charts. Contribute to reflex-dev/xy development by creating an account on GitHub.
Jul 2026 · github.com · its alternatives →
- 5
Hello Hacker News. I’m Martin, a graduate student from Prague, and I’ve been working on Coros, a C++ library for task-based parallelism. After spending some time with OpenMP and oneTBB, I wanted to try building a library using modern features from the C++ standard library. I’ve used coroutines for task encapsulation and C++23 expected for exception handling, while trying to maintain good performance. Additionally, I’ve implemented monadic-like behavior to allow easy chaining of tasks, similar to the monadic operations in std::expected. You can check out the project here:…
2024 · github.com · its alternatives →
- 6
This started out as a personal effort to learn more about machine learning. It's currently a CLI app where you give it a JSON file specifying your network architecture and hyperparameters and point it to your training data, then invoke it again in 'eval' mode with some data it's not seen before and it will try to classify each sample. I don't see many other people using Vulkan for GPGPU, and there may be many good reasons for that, but I wanted to try something a bit different. I've made every attempt to make the code very clean and readable and I've written up the math in…
2024 · github.com · its alternatives →
- 7PO
Our company Vertex.AI has been working on this for a while but this is the first public release. We're starting with using PlaidML to bring OpenCL support to Keras and more frameworks, platforms, etc are coming. Yes, this means you can use use your AMD GPU for deep learning dev. Sorry, no Mac or Windows support yet although the brave can try building from source (it should work). http://vertex.ai/blog/announcing-plaidml https://github.com/plaidml/plaidml
2017 · its alternatives →
- 8RX
Hi all, long time lurker, first time poster. I want to share with you all something we've been working on for a while at Lambda: the Razer x Lambda Tensorbook: https://www.youtube.com/watch?v=wMh6Dhq7P_Q But before I tell you about it, I want to make this all about me, because I built this for me. See, while I'm genuinely interested in hearing from the community what you think as this is the culmination of a lot of effort from a lot of people across so many different fields (seriously, the number of folks across manufacturing, engineering, design, logistics, and marketing who…
2022 · its alternatives →
- 9
I ported Microsoft's TRELLIS.2 (4B parameter image-to-3D model) to run on Apple Silicon via PyTorch MPS. The original requires CUDA with flash_attn, nvdiffrast, and custom sparse convolution kernels: none of which work on Mac. I replaced the CUDA-specific ops with pure-PyTorch alternatives: a gather-scatter sparse 3D convolution, SDPA attention for sparse transformers, and a Python-based mesh extraction replacing CUDA hashmap operations. Total changes are a few hundred lines across 9 files. Generates ~400K vertex meshes from single photos in about 3.5 minutes on M4 Pro (24GB). Not as fast as…
Apr 2026 · github.com · its alternatives →
- 10
Hi HN, I’m Joe. My friends Matthew, Jake and I are building Luminal (https://luminalai.com/), a GPU compiler for automatically generating fast GPU kernels for AI models. It uses search-based compilation to achieve high performance. We take high level model code, like you'd have in PyTorch, and generate very fast GPU code. We do that without using LLMs or AI - rather, we pose it as a search problem. Our compiler builds a search space, generates millions of possible kernels, and then searches through it to minimize runtime. You can try out a demo in `demos/matmul` on mac to…
2025 · github.com · its alternatives →
- 11
A fast, ergonomic and portable tensor library in Nim with a deep learning focus for CPU, GPU and embedded devices via OpenMP, Cuda and OpenCL backends - mratsim/Arraymancer
2018 · github.com · its alternatives →
- 12
A pipeline that translates Rust GPU code into formal Coq models, as a foundation for memory model proofs - neelsomani/vericuda
Oct 2025 · github.com · its alternatives →
- 13
GPU Raytracer from scratch in C++/CUDA. Contribute to jan-van-bergen/GPU-Raytracer development by creating an account on GitHub.
2021 · github.com · its alternatives →
- 14
Hi HN, We’re a small team of OS, virtualization, and ML engineers, and after three years of development, we’re thrilled to launch the beta of our CUDA abstraction layer! We decouple the Kernel Shader execution from applications that use CUDA into a Wooly Abstraction layer. In this abstraction layer, we compile these to a new binary, and Shaders are compiled into a Wooly Instruction Set. At runtime, Kernel Shader launch events initiate a transfer of Shader over the network from a CPU host to a GPU host, where they are recompiled. Their execution is managed by Wooly Server software to achieve…
2025 · woolyai.com · its alternatives →
- 15
Hey HN, I am the founder of Tensorlake. Prototyping LLM applications have become a lot easier, building decision making LLM applications that work on constantly updating data is still very challenging in production settings. The systems engineering problems that we have seen people face are - 1. Reliably process ingested content in real time if the application is sensitive to freshness of information. 2. Being able to bring in any kind of model, and run different parts of the pipeline on GPUs and CPUs. 3. Fault Tolerance to ingestion spike, compute infrastructure failure. 4. Scaling compute,…
2024 · getindexify.ai · its alternatives →
- 16
Txeo is a lightweight and intuitive C++ wrapper for TensorFlow, designed to simplify TensorFlow C++ development while preserving high performance and flexibility. Built entirely with Modern C++, Txeo allows developers to use TensorFlow with the ease of a high-level API, eliminating the complexity of its low-level C++ interface.
2025 · github.com · its alternatives →
- 17
I'm a machine learning engineer and researcher. I got fed up with how difficult it is to understand why neural networks behave the way they do, so i wrote a library to help with it. Comgra (computation graph analysis) is a library you can use with pytorch to extract all the tensor data you care about and visualize it graphically in a browser. This allows for a much more detailed analysis of what is happening than the usual approach of using tensorboard. You can go investigate tensors as training proceeds, drill down into individual neurons, inspect single data sets that are of special…
2023 · github.com · its alternatives →
- 18
Hi HN, I'm a 19-year-old aerospace student. I spent the last 13 months building a custom Linux distro from scratch because I wanted to see if we could treat the OS kernel as a mathematical engine rather than a deterministic administrator. The Stack: Flux (The Shell): A custom math-native shell where x² and ∑ are valid syntax. It parses mathematical notation directly into optimized SIMD instructions (no Python wrapper). Tenet (The Scheduler): Written in Tenet (my custom DSL for game theory). The scheduler is a Nash Equilibrium solver compiled to native code. In my benchmarks (Ryzen 7 5800HS),…
Feb 2026 · fawazishola.ca · its alternatives →
- 19
Keep Python on your laptop. Run PyTorch operations and hold tensors on a remote GPU, including from a Mac with no CUDA installation. - ymcrcat/rgpu
14d ago · github.com · its alternatives →
- 20
A C++17 library for reading and writing NumPy .npy files, with optional .npz (zip) archive support - symisc/sy-numpy-cpp
Apr 2026 · github.com · its alternatives →
- 21
Hi HN! I've built [CXXStateTree](https://github.com/ZigRazor/CXXStateTree), a modern C++ header-only library to create hierarchical state machines with clean, intuitive APIs. It supports: - Deeply nested states - Entry/exit handlers - State transitions with guards and actions - Asynchronous transitions with `co_await` (C++20 coroutines) - Optional runtime type identification for flexibility It's ideal for complex control logic, embedded systems, games, robotics, and anywhere you'd use a finite state machine. I’d love feedback, use cases, or contributions from the…
2025 · github.com · its alternatives →
- 22
C++ tensors with broadcasting and lazy computing. Contribute to xtensor-stack/xtensor development by creating an account on GitHub.
2017 · github.com · its alternatives →
- 23RT
Hello everyone! I've created a programming language named Atlas in C, and I'm excited to share it with you. After many years of thinking about how to bridge CPU and GPU programming more effectively, I decided to build a minimalist language that focuses on a single structure: a stack of (up to 4-dimensional) tensors. Atlas is designed to be simple and efficient—it generalizes many of the concepts behind WebGL while offering some unique features. For example, it runs on Windows 10/11 and in browsers via emscripten, and it even has the capability to render directly to the Windows desktop.…
Nov 2025 · banditcat.github.io · its alternatives →
- 24
Also compare
- I built a tensor library from scratch in C++/CUDA alternatives
- TensorZero alternatives
- Dockerized GPU Deep Learning Solution (Code and Blog and TensorFlow Demo) alternatives
- XY – A Fast, composable, GPU-accelerated interactive plotting library alternatives
- Coros – A Modern C++ Library for Task Parallelism alternatives
- Richard – A CNN written in C++ and Vulkan (no ML or math libs) alternatives
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 →