Topics / #aarch64

Aarch64 projects on GitHub

64-bit ARM architecture software, from low-level systems to embedded projects.

As of , the most-starred Aarch64 projects on GitHub are simdjson (24.4K stars), sherpa-onnx (15.4K stars) and rust-raspberrypi-OS-tutorials (14.7K stars). GitHub.Locker tracks 13 Aarch64 repositories with 63.7K stars combined. The fastest-growing on October 18 was d2r-mobile, with +204 stars in a day.

13Projects
63.7KStars in total
+303Stars in a day

Hot right now

Most stars gained in a day · Oct 18

The all-time top

13 projects · by stars

  1. #1 · simdjson/simdjson

    simdjson

    A C++ library that parses JSON at gigabytes-per-second speed using SIMD instructions and microparallel algorithms. It ships in production systems like Node.js, ClickHouse and Meta Velox.

    24.4K
  2. #2 · k2-fsa/sherpa-onnx

    sherpa-onnx

    sherpa-onnx is an offline toolkit for speech-to-text, text-to-speech, speaker diarization, speaker identification/verification, spoken language identification, audio tagging, VAD, speech enhancement, keyword spotting and source separation, built on next-gen Kaldi and ONNX Runtime, with no internet connection required.

    15.4K
  3. #3 · rust-embedded/rust-raspberrypi-OS-tutorials

    rust-raspberrypi-OS-tutorials

    A step-by-step tutorial series that teaches you how to write your own embedded Operating System kernel from scratch in Rust, targeting the Raspberry Pi 3 and 4.

    14.7K
  1. 4

    d2r-mobile

    3.8Kjhaizhou-ops/d2r-mobile · C

    D2R Mobile is an open-source iOS compatibility layer that lets you run your own Switch copy of Diablo II: Resurrected (with the Reign of the Warlock expansion) natively on iPhone and iPad, with full touch controls and 60 fps.

  2. 5

    try-omarchy

    2.7Komacom/try-omarchy · Swift

    Try Omarchy lets you run the Omarchy Arch Linux desktop as a native, hardware-accelerated macOS app on Apple Silicon, with no manual VM setup required.

  3. 6

    ir

    509dstogov/ir · C

    IR is a lightweight framework for building JIT compilers in medium-size projects. It gives you an intermediate representation, an API to construct it, and passes for optimization, scheduling, register allocation and machine code generation that can be executed directly in memory.

  4. 7

    Qwen3.8-27B-SGLang-DGX-Spark

    474MiaAI-Lab/Qwen3.8-27B-SGLang-DGX-Spark · Shell

    A set of opinionated, ready-to-run Docker scripts that serve the Qwen3.8-27B model through SGLang on an NVIDIA DGX Spark (GB10, aarch64), offering three swap-in speculative-decoding modes — EAGLE/MTP, DSpark, and DFlash2 — each tuned with on-device measurements rather than guesses.

  5. 8

    qwen3.8-Flash-DGX

    459blazux/qwen3.8-Flash-DGX · Python

    A recipe (scripts plus a patched Docker image) for serving the ~176B-parameter Qwen3.8-Flash-Next model with vLLM on a single NVIDIA DGX Spark (GB10). It solves the problem that the 126 GiB NVFP4 checkpoint doesn't fit next to a usable KV cache in the Spark's 128 GB unified memory, by streaming a 48 GiB lookup table from NVMe via mmap instead of keeping it resident.

  6. 9

    SuperMarioWonderRecomp

    283BelmanteGu/SuperMarioWonderRecomp · C++

    A static recompilation of Super Mario Bros. Wonder (Nintendo Switch) into native C++, with Nintendo's NVN graphics API reimplemented on Vulkan (MoltenVK on Mac). It lets the game run natively on macOS, Windows, Linux and Android without an emulator.

  7. 10

    suyu-v0.0.4

    281suyu-emu/suyu-v0.0.4 · C++

    suyu is a Nintendo Switch emulator and AArch64 native recompiler written in C++, preserved at its final public release v0.04.

  8. 11

    m4-sme-exploration

    245tzakharko/m4-sme-exploration · C

    A research project that microbenchmarks the Scalable Matrix Extension (SME) of Apple's M4 chip, measuring peak compute throughput for common matrix and vector operations and memory transfer rates.

  9. 12

    Qwen3.8-27B-DFlash2-EXL3-5.0bpw

    232MiaAI-Lab/Qwen3.8-27B-DFlash2-EXL3-5.0bpw · Python

    A deployment kit for serving Qwen3.8-27B (quantized to EXL3 3.5bpw) through an OpenAI-compatible server, using speculative decoding to speed up generation. It bundles the launcher, server, and config; the model weights live on Hugging Face and inference runs on the team's exllamav3 fork.

  10. 13

    twinspark

    176raullenchai/twinspark · Shell

    This is a production-grade deployment recipe for running DeepSeek-V4-Flash-0731 (a 284B-parameter MoE model) across two networked NVIDIA DGX Spark machines, using a self-healing 2-node vLLM cluster tuned for speculative decoding.

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