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NVIDIA
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NVIDIA/nvcf

Platform for deploying and routing GPU-accelerated inference, streaming, and batch workloads at scale.

Go ◇ cloud-functions Apache-2.0
★237STARS
⑂94FORKS
!524ISSUES
🏆#12,075GLOBAL RANK
🔥3DAYS TRENDING
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Momentum

+10

STARS · LAST 30 DAYS

1

PER DAY

#1,316

MOST-STARRED Go

Window7 days30 days90 days
Stars gained+7+10+90
Per day111
Forks gained+1+3+10

nvcf gained 10 stars in the last 30 days, about 1 a day, and now has 237. It is about 1 year old and has averaged roughly 237 stars a year. It ranks #1,316 among Go repositories and #12,075 across all languages on GitHubRepo.

Trending Record

nvcf has maintained a continuous presence across global trending indexes, peaking at #11531. Below is the 30-day activity profile:

💡 Overview

nvcf is an open-source project written in Go: Platform for deploying and routing GPU-accelerated inference, streaming, and batch workloads at scale.

Engineered for speed, consistency, and developer ease, it solves common hurdles in cloud-functions, gpu, inference. It provides clear interfaces, comprehensive configuration options, and seamless integration with existing tools across the modern development stack.

⚡ Key Features

1

Optimized execution pipeline written in Go for predictable speed.

2

Zero-friction configuration with comprehensive sensible defaults out of the box.

3

Cross-platform runtime support across Linux, macOS, and Windows environments.

4

Strong typing and modular architecture designed for easy extension and maintainability.

5

Standardized CLI and API interfaces for smooth integration into CI/CD workflows.

6

Active community maintenance with regular dependency updates and security patches.

📥 Installation

terminal
$ go install github.com/NVIDIA/nvcf@latest

⚙ System Requirements

Platforms

  • • macOS
  • • Linux
  • • Windows

Runtime & Dependencies

Go >= 1.21 runtime environment

Architecture

x86_64, ARM64 (Apple Silicon & Graviton)

🧠 How It Works

nvcf coordinates its core functionality through a modular Go 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 nvcf into Go 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

1

Install nvcf using your package manager: `go install github.com/NVIDIA/nvcf@latest`

2

Initialize your project workspace or configuration file for nvcf.

3

Import nvcf into your codebase or invoke it directly from your terminal.

4

Execute your test suite or run `nvcf --help` to verify successful setup.

👍 Strengths

Active community backing with 237 GitHub stars and verified adoption.
Permissive open-source distribution under the Apache-2.0 license.
Built in Go for high execution speed and developer familiarity.
Cross-platform compatibility across modern Linux, macOS, and Windows environments.
Clean modular design allowing flexible configuration and pipeline integration.

⚠️ Considerations

Requires familiarity with Go and modern CLI workflows.
Ecosystem extensions may require manual configuration depending on environment constraints.
Active development roadmap means breaking API changes may occur across major versions.

⇄ Alternatives & Direct Competitors

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👥 Who Should Use This

Developers and engineering teams building with Go, seeking reliable, tested, and actively maintained tooling for production workloads.

🏆 Nearby in the Rankings

NVIDIA/nvcf is currently ranked #12,075 by stars across every repository tracked on GitHubRepo. These are adjacent projects:

RankRepositoryLanguageStarsAction
#12,048 ayushh0110/ScreenMind Python ★ 238 Compare ↗
#12,048 microsoft/XBOX-Godot-Sample C++ ★ 238 Compare ↗
#12,048 PixelPlayerHQ/PixelPlayerOSS Kotlin ★ 238 Compare ↗
#12,048 rcieri/glab-tui Rust ★ 238 Compare ↗
#12,048 Oleafly/Oleafly TypeScript ★ 238 Compare ↗
#12,075 NVIDIA/nvcf This Project Go ★ 237
#12,075 stjernstrom/capistrano_colors Ruby ★ 237 Compare ↗
#12,075 oUF-wow/oUF Lua ★ 237 Compare ↗
#12,075 jeetsukumaran/DendroPy Python ★ 237 Compare ↗
#12,075 jfahrenkrug/VertexHelper Objective-C ★ 237 Compare ↗
#12,075 signumsoftware/framework C# ★ 237 Compare ↗
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Frequently Asked Questions

What does nvcf do? +

Platform for deploying and routing GPU-accelerated inference, streaming, and batch workloads at scale.

What language is nvcf written in? +

The primary language is Go. Topics include: cloud-functions, gpu, inference, kubernetes, nvidia.

Is nvcf actively maintained? +

Yes, the last recorded push was on Oct 15, 2026 with 524 open issues being tracked.

How many stars does nvcf have? +

nvcf has 237 stars and 94 forks on GitHub.

How does nvcf rank among GitHub repositories? +

With 237 stars, NVIDIA/nvcf is ranked #12,075 globally across all repositories tracked on GitHubRepo and #1,316 among Go projects.

What license is nvcf distributed under? +

The repository reports a Apache-2.0 license. Always verify the repository LICENSE file for legal terms.

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