Nicheloom visits: 58,301 all-time · 7,637 in the last 7 days

The opportunity tracker for new startups.

Today: 1,008 launches · Niche of the day: specialized calculation tools · See what launched today →

Axiom

C++ tensor library with NumPy API and Metal GPU support

Get picks like this daily. Today's launch numbers, the top launches, AI and tech news, and a daily opportunity pick, straight to your inbox.

Want to reach these readers? Sponsor an issue.

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 patternsIt 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 genuinely unsure about and would love feedback on: - Does Axiom actually seem useful? - What features might make you use it?GitHub: https://github.com/frikallo/axiomHappy to answer questions about the implementation.

HN · launched Feb 2, 2026 · 5 upvotes (top 89%) · 2 views

Niche: specialized algorithms and computing libraries · 230 launches, 4 in the last 7 days ▼ -73% · Explore this niche →

Category and tags
  • Horizontal
  • Model & infra
  • Developer
  • Not AI
  • Hobby / open-source project

Source listing ↗

More like this: all 230 launches in specialized algorithms and computing libraries →

Could you build this?

No Developing a custom C++ tensor library with Metal GPU acceleration requires deep native systems programming, memory management, and GPU shader kernel optimization.

What it would actually take: Requires modern C++ (C++20), Metal Shading Language (MSL), Objective-C++ bridges, and BLAS/LAPACK backends for CPU fallbacks. The hard parts include writing optimized GPU compute kernels for arbitrary tensor operations, handling strided memory layouts, broadcasting rules, autograd/computation graphs, and device-to-host memory synchronization. Demands specialized knowledge in high-performance computing, Apple Metal API, and numerical computation algorithms.

Discussion

No comments on this launch.

Competitors

Other products that read as similar to this one : 262 launches clear the similarity bar, closest 8 shown.

Attention rank: #242 of 263 (itself plus its competitors, highest first, normalized so YC and Product Hunt are compared fairly).

Launched 96 days after the earliest competitor.

Related data

The niche, labels, vibe code rating and competitor comparison on this page are analysis by Nicheloom. If you use them, please credit nicheloom.com. How you may use our data.