Open ABI and FFI for Machine Learning Systems
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+12
STARS · LAST 30 DAYS
1
PER DAY
#348
MOST-STARRED C++
| Window | 7 days | 30 days | 90 days |
|---|---|---|---|
| Stars gained | +7 | +12 | +90 |
| Per day | 1 | 1 | 1 |
| Forks gained | +1 | +3 | +10 |
tvm-ffi gained 12 stars in the last 30 days, about 1 a day, and now has 466. It is about 1 year old and has averaged roughly 466 stars a year. It ranks #348 among C++ repositories and #4,920 across all languages on GitHubRepo.
Trending Record
2
DAYS ON TRENDING
#4301
BEST RANK
Sep 29, 2026
FIRST APPEARANCE
Active
STATUS TODAY
tvm-ffi has maintained a continuous presence across global trending indexes, peaking at #4301. Below is the 30-day activity profile:
💡 Overview
tvm-ffi is an open-source project written in C++: Open ABI and FFI for Machine Learning Systems.
Engineered for speed, consistency, and developer ease, it solves common hurdles in ffi, gpu, machine-learning. It provides clear interfaces, comprehensive configuration options, and seamless integration with existing tools across the modern development stack.
⚡ Key Features
Optimized execution pipeline written in C++ for predictable speed.
Zero-friction configuration with comprehensive sensible defaults out of the box.
Cross-platform runtime support across Linux, macOS, and Windows environments.
Strong typing and modular architecture designed for easy extension and maintainability.
Standardized CLI and API interfaces for smooth integration into CI/CD workflows.
Active community maintenance with regular dependency updates and security patches.
📥 Installation
$ git clone https://github.com/apache/tvm-ffi.git
cd tvm-ffi⚙ System Requirements
Platforms
- • macOS
- • Linux
- • Windows
Runtime & Dependencies
C++20 compliant compiler (GCC 11+, Clang 13+, MSVC)
Architecture
x86_64, ARM64 (Apple Silicon & Graviton)
🧠 How It Works
tvm-ffi coordinates its core functionality through a modular C++ pipeline. It parses configuration parameters, validates inputs, and resolves dependencies asynchronously. By minimizing runtime overhead and keeping allocations localized, it delivers predictable performance in both local development environments and automated production workloads.
🎯 Production Use Cases
Production System Integration
Embed tvm-ffi into C++ backend services to handle core application logic.
CI/CD Automated Pipelines
Run automated validation, builds, and integration suites during deployments.
Developer Tooling & Workflows
Accelerate developer onboarding with pre-configured project utilities.
Open Source Extension
Fork and customize internal modules under the repository's open Apache-2.0 license.
🚀 Getting Started
Install tvm-ffi using your package manager: `git clone https://github.com/apache/tvm-ffi.git`
Initialize your project workspace or configuration file for tvm-ffi.
Import tvm-ffi into your codebase or invoke it directly from your terminal.
Execute your test suite or run `tvm-ffi --help` to verify successful setup.
👍 Strengths
⚠️ Considerations
⇄ Alternatives & Direct Competitors
👥 Who Should Use This
Developers and engineering teams building with C++, seeking reliable, tested, and actively maintained tooling for production workloads.
🏆 Nearby in the Rankings
apache/tvm-ffi is currently ranked #4,920 by stars across every repository tracked on GitHubRepo. These are adjacent projects:
| Rank | Repository | Language | Stars | Action |
|---|---|---|---|---|
| #4,913 | cesargb/laravel-magiclink | PHP | ★ 467 | Compare ↗ |
| #4,913 | theQRL/QRL | Python | ★ 467 | Compare ↗ |
| #4,913 | byroot/activerecord-typedstore | Ruby | ★ 467 | Compare ↗ |
| #4,913 | thedarkone/rails-dev-boost | Ruby | ★ 467 | Compare ↗ |
| #4,913 | andrewbenington/OpenHome | Rust | ★ 467 | Compare ↗ |
| #4,920 | apache/tvm-ffi This Project | C++ | ★ 466 | |
| #4,920 | dy/wavefont | JavaScript | ★ 466 | Compare ↗ |
| #4,920 | burakgon/stop-stutter | Swift | ★ 466 | Compare ↗ |
| #4,923 | laminlabs/lamindb | Python | ★ 465 | Compare ↗ |
| #4,923 | 1372Slash/Zenith | Kotlin | ★ 465 | Compare ↗ |
| #4,923 | openai/openai-ruby | Ruby | ★ 465 | Compare ↗ |
Frequently Asked Questions
What does tvm-ffi do? +
Open ABI and FFI for Machine Learning Systems
What language is tvm-ffi written in? +
The primary language is C++. Topics include: ffi, gpu, machine-learning.
Is tvm-ffi actively maintained? +
Yes, the last recorded push was on Sep 28, 2026 with 14 open issues being tracked.
How many stars does tvm-ffi have? +
tvm-ffi has 466 stars and 100 forks on GitHub.
How does tvm-ffi rank among GitHub repositories? +
With 466 stars, apache/tvm-ffi is ranked #4,920 globally across all repositories tracked on GitHubRepo and #348 among C++ projects.
What license is tvm-ffi distributed under? +
The repository reports a Apache-2.0 license. Always verify the repository LICENSE file for legal terms.
