Dev tools · alternatives · 2026

24 alternatives to High speed graphics rendering research with tinygrad/tinyJIT

I saw a tweet that tinygrad is so good that you could make a graphics library that wraps tg. So I’ve been hacking on a gtinygrad, and honestly it convinced me it could be used for legit research. The JIT + tensor model ends up being a really nice way to express light transport all in simple python, so I reimplemented some new research papers from SIGGRAPH like REstir PG and SZ and it just works. instead of complicated cpp its just a 200 LOC of python.

Gtinygrad is a graphics rendering library built on tinygrad that enables researchers to implement light transport algorithms in Python. It wraps tinygrad's JIT compiler and tensor operations to simplify complex… Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes.

1
A physically-based GPU ray tracer written in Julia▲198
We ported pbrt-v4 to Julia and built it into a Makie backend. Any Makie plot can now be rendered with physically-based path tracing. Julia compiles user-defined physics directly into GPU kernels, so anyone can extend the ray tracer with new materials and media - a black hole with gravitational lensing is ~200 lines of Julia. Runs on AMD, NVIDIA, and CPU via KernelAbstractions.jl, with Metal coming soon. Demo scenes: github.com/SimonDanisch/RayDemo
Feb 2026 · makie.org · its alternatives →
2
ChartGPU – WebGPU-powered charting library (1M points at 60fps)▲670
Creator here. I built ChartGPU because I kept hitting the same wall: charting libraries that claim to be "fast" but choke past 100K data points. The core insight: Canvas2D is fundamentally CPU-bound. Even WebGL chart libraries still do most computation on the CPU. So I moved everything to the GPU via WebGPU: - LTTB downsampling runs as a compute shader - Hit-testing for tooltips/hover is GPU-accelerated - Rendering uses instanced draws (one draw call per series) The result: 1M points at 60fps with smooth zoom/pan. Live demo:…
Jan 2026 · github.com · its alternatives →
3
StratusGFX, my open-source real-time 3D rendering engine▲483
It's been closed source for a long time while I worked on it on and off as a hobby research project, but yesterday the repo was made public for the first time under the MPL 2.0 license. A feature reel showing its capabilities can be found here: https://ktstephano.github.io/rendering/stratusgfx/feature_re... A technical breakdown of a single frame can be found here: https://ktstephano.github.io/rendering/stratusgfx/frame_anal... It's still in a very beta state (bugs and instability expected), but I felt like it was a good time to make it…
2023 · github.com · its alternatives →
4
I've made a Monte-Carlo raytracer for glTF scenes in WebGPU▲131
This is a GPU "software" raytracer (i.e. using manual ray-scene intersections and not RTX) written using the WebGPU API that renders glTF scenes. It supports many materials, textures, material & normal mapping, and heavily relies on multiple importance sampling to speed up convergence.
2024 · github.com · its alternatives →
5
micro-gl▲101
Run vector graphics on any computer (without GPU or FPU)
2023 · github.com · its alternatives →
6
Run TRELLIS.2 Image-to-3D generation natively on Apple Silicon▲202
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 →
7
LTX.bio▲164
Hey HN, after our 13B release we've been working on a faster version of our open-source video model and we're excited to share it. We started with a 13B base model that already had competitive generation speeds (e.g. 55s for a 5s video on an H100 — faster than any other model out there). But we wanted to push it further to allow everyone to quickly iterate over their video generations. So we built a distilled version focused on speed without sacrificing temporal or spatial coherence. With the Distilled model, you can now generate 5-second 720p videos in about 9.5 seconds on an H100, and…
2021 · lightricks.com · its alternatives →
8
Vaev – A browser engine built from scratch (It renders google.com)▲233
We’ve been working on Vaev, a minimal web browser engine built from scratch. It supports HTML/XHTML, the CSS cascade, @page rules for pagination, and print-to-PDF rendering. It even handles calc(), var(), and percentage units—and yes, it renders Google.com (mostly). This is an experimental project focused on learning and exploration. Networking is basic (http:// and file:// only), and grid layouts aren’t supported yet, but we’re making progress fast. We’d love your thoughts and feedback.
2025 · github.com · its alternatives →
9
TG – Fast geometry library for C▲201
Geometry library for C - Fast point-in-polygon. Contribute to tidwall/tg development by creating an account on GitHub.
2023 · github.com · its alternatives →
10
GPT-2 implemented using graphics shaders▲228
Back in the old days, people used to do general-purpose GPU programming by using shaders like GLSL. This is what inspired NVIDIA (and other companies) to eventually create CUDA (and friends). This is an implementation of GPT-2 using WebGL and shaders. Enjoy!
2025 · github.com · its alternatives →
11
I built a tensor library from scratch in C++/CUDA▲119
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 →
12
Fully client-side GPT2 prediction visualizer▲153
Hi HN! I've found this visualization tool immensely helpful over the years for getting an intuition for how an LLM "sees" some piece of text, and with a bit of elbow grease decided to move all compute to client side so I could make it publicly available. I've found it particularly useful for - Understanding exactly how repetition and patterns affect a small LM's ability to predict correctly - Understanding different tokenization patterns and how it affects model output - Getting a general sense of how "hard" different prediction tasks are for GPT-style models Known problems (that I probably…
2023 · perplexity.vercel.app · its alternatives →
13
I wrote a C++ ray tracer from scratch without AI▲155
C++ Path Tracer from scratch with zero third-party libraries. - themartiano/luz
Jun 2026 · github.com · its alternatives →
14
Tiny Diffusion – A character-level text diffusion model from scratch▲172
I previously posted this a month and a half ago: https://news.ycombinator.com/item?id=45876742 I have rewritten it to be much more simple, from 951 lines of code to just 364, with no loss in core functionality or generation quality. I also added a tiny GPT implementation as a comparison (inspired by Andrej Karpathy's code). The two model implementations are ~80% identical, with the core differences being the generate and get_batch functions. The model architecture, training loop, etc, differ in only 19 lines of code. Trained weights are included, so you can just clone and run…
Nov 2025 · github.com · its alternatives →
15
Luminal – Open-source, search-based GPU compiler▲153
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 →
16
a Rust ray tracer that runs on any GPU – even in the browser▲95
I’ve been experimenting with Rust lately and wanted a project that would help me explore some of its lower-level and performance-oriented features. Inspired by Sebastian Lague’s videos, I decided to implement my own ray tracer from scratch. The initial goal was just to render a simple 3D scene in the browser at a reasonable frame rate. It evolved into a small renderer that can: • Run locally or on the web using wgpu and WebAssembly • Perform mesh rendering with a Bounding Volume Hierarchy (BVH) for acceleration • Simulate both direct and indirect illumination for photorealistic results • Be…
Nov 2025 · github.com · its alternatives →
17
XY – A Fast, composable, GPU-accelerated interactive plotting library▲136
Ultra-fast and customizable Python charts. Contribute to reflex-dev/xy development by creating an account on GitHub.
Jul 2026 · github.com · its alternatives →
18
Free and open-source home for art made with code▲144
Browse and share GPU-made GIFs. Explore GLSL shader experiments, search by topic, and open any piece in the editor to learn or remix.
2018 · shadergif.com · its alternatives →
19
Physically-Based GPU Pathtracer with Mitsuba XML Support▲63
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 →
20
Shadergarden: Create reloadable graphical pipelines with Lisp and GLSL▲47
Create evolving artistic images with hot-code-reloaded Lisp and GLSL.
2021 · blog.tonari.no · its alternatives →
21
TinyGPT – A Simple, Educational Deep Learning Library▲13
A tiny version of GPT fully implemented in Python with zero dependencies - isaacperez/tinygpt
2024 · github.com · its alternatives →
22
Synthesize TikZ Graphics Programs for Scientific Figures and Sketches▲132
Creating high-quality scientific figures can be time-consuming and challenging, even though sketching ideas on paper is relatively easy. Furthermore, recreating existing figures that are not stored in formats preserving semantic information is equally complex. To tackle this problem, we introduce DeTikZify, a novel multimodal language model that automatically synthesizes scientific figures as semantics-preserving TikZ graphics programs based on sketches and existing figures. We also introduce a Monte Carlo Tree Search-based inference algorithm that enables DeTikZify to iteratively refine its…
2024 · github.com · its alternatives →
23
Comgra: A library for debugging and understanding neural networks▲66
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 →
24
3DGS.cpp – performant, cross platform Gaussian Splatting with Vulkan▲50
[deleted]
2024 · github.com · its alternatives →

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