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vit.cpp

staghado/vit.cpp

Inference Vision Transformer in C/C++ with ggml

GitHub

GraphCanon updated Sep 25, 2026 · GitHub synced Sep 25, 2026

44views this month

320 stars28 forksLast push Apr 11, 2024 C++ MIT

Decision brief

vit.cpp is an optimized C/C++ implementation for Vision Transformer inference that leverages ggml to enhance performance and maintain lightweight, dependency-free operation.

Good fit when

Use vit.cpp when you need fast startup times for serverless deployments as it addresses cold start issues inherent in common deep learning frameworks.
Select this tool for edge computing tasks due to its efficient use of CPU resources and support for different quantization levels, including 4-bit precision.

Avoid when

Avoid using vit.cpp if you require GPU acceleration since it is primarily optimized for CPU performance with ggml.
Do not choose vit.cpp if your project depends on rich ecosystem features or libraries unavailable in this standalone implementation lacking extra dependencies.

Observed Jul 16, 2026 · Source: enrich:decision_facts

vit.cpp alternatives Trust report

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Maintenance and security

Full trust report

Maintenance: Dormant (896d since push); As of Sep 25, 2026
Provenance: Not a fork · Personal account; As of Sep 25, 2026
Security (OSV): No lockfile; As of Jul 11, 2026

Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.

Install

git clone https://github.com/staghado/vit.cpp

How it fits your stack(1)

Typed graph edges - alternatives, integrations, successors, and dependencies. Ranked by relationship type, not raw GitHub stars.

Integrates

whisper.cpp

Both projects use ggml for inference and are implemented in C/C++, making them compatible technologies that could integrate with each other for multi-modal applications.

integrates

Relationship graph

Optional deeper exploration of typed edges and category neighbours.

Similar tools

Same-category neighbours not already linked as typed edges.

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Evidence and technical details

Sourced facts, taxonomy, compatibility claims, README excerpt, and machine-readable endpoints.

Overview

A standalone implementation of the Vision Transformer (ViT) model for inference tasks using plain C/C++ and ggml.

Capability facts

Languages: c++
Source: github.language · Sep 25, 2026

Compatibility

Sourced claims from the README excerpt - not unsourced marketing copy.

Python runtimePython

Source: README excerpt (regex_v1, Sep 25, 2026)

python convert-pth-to-ggml.py --list

Source link

README

vit.cpp Inference Vision Transformer (ViT) in plain C/C++ using ggml without any extra dependencies Description This project presents a standalone implementation of the well known Vision Transformer (ViT) model family, used in a broad spectrum of applications and SOTA models like...

For agents

This page has a .md twin and JSON over the API.

/tools/staghado-vit-cpp.md GET /api/graphcanon/tools/staghado-vit-cpp GET /api/graphcanon/graph?tool=staghado-vit-cpp