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pegainfer-project
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pegainfer-project/pegainfer

Pure Rust + CUDA LLM inference engine — no PyTorch, OpenAI-compatible, serves Qwen3 to Kimi-K2

Rust ◇ cuda Apache-2.0
★712STARS
⑂110FORKS
!68ISSUES
🏆#3,102GLOBAL RANK
🔥5DAYS TRENDING
🚀
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Star History

Continuous Observations
Interactive star growth chart for pegainfer-project/pegainfer
CSV

Momentum

+18

STARS · LAST 30 DAYS

1

PER DAY

#320

MOST-STARRED Rust

Window7 days30 days90 days
Stars gained+7+18+90
Per day111
Forks gained+1+3+10

pegainfer gained 18 stars in the last 30 days, about 1 a day, and now has 712. It is about 1 year old and has averaged roughly 712 stars a year. It ranks #320 among Rust repositories and #3,102 across all languages on GitHubRepo.

Trending Record

pegainfer has maintained a continuous presence across global trending indexes, peaking at #1317. Below is the 30-day activity profile:

💡 Overview

pegainfer is an open-source project written in Rust: Pure Rust + CUDA LLM inference engine — no PyTorch, OpenAI-compatible, serves Qwen3 to Kimi-K2.

Engineered for speed, consistency, and developer ease, it solves common hurdles in cuda, cuda-kernels, deepseek. 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 Rust 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
$ cargo install pegainfer

⚙ System Requirements

Platforms

  • • macOS
  • • Linux
  • • Windows

Runtime & Dependencies

Rust toolchain (rustc / cargo >= 1.70)

Architecture

x86_64, ARM64 (Apple Silicon & Graviton)

🧠 How It Works

pegainfer coordinates its core functionality through a modular Rust 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

Autonomous AI Agents

Orchestrate intelligent workflows and tool-calling routines with pegainfer.

Model Inference & Prompting

Integrate fast, local or cloud-hosted generative AI models directly into production code.

Context Memory & RAG

Augment language models with dynamic vector retrieval and structured project memory.

Developer Productivity

Automate repetitive engineering tasks, code generation, and test creation using AI agents.

🚀 Getting Started

1

Install pegainfer using your package manager: `cargo install pegainfer`

2

Initialize your project workspace or configuration file for pegainfer.

3

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

4

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

👍 Strengths

Active community backing with 712 GitHub stars and verified adoption.
Permissive open-source distribution under the Apache-2.0 license.
Built in Rust 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 Rust 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.

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👥 Who Should Use This

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

🏆 Nearby in the Rankings

pegainfer-project/pegainfer is currently ranked #3,102 by stars across every repository tracked on GitHubRepo. These are adjacent projects:

RankRepositoryLanguageStarsAction
#3,096 jo-duchan/tapflow TypeScript ★ 715 Compare ↗
#3,096 Clearailhc/clearai-dsh JavaScript ★ 715 Compare ↗
#3,099 disposable/disposable-email-domains JavaScript ★ 714 Compare ↗
#3,100 Snd-R/komf Kotlin ★ 713 Compare ↗
#3,100 google/oss-rebuild Go ★ 713 Compare ↗
#3,102 pegainfer-project/pegainfer This Project Rust ★ 712
#3,102 maxlapshin/mysql2postgres Ruby ★ 712 Compare ↗
#3,102 CosmosMind-ai/RSI-Harness TypeScript ★ 712 Compare ↗
#3,105 phpstan/phpstan-strict-rules PHP ★ 711 Compare ↗
#3,105 anishfn/shapeshift TypeScript ★ 711 Compare ↗
#3,107 Steel-Foundation/SteelMC Rust ★ 710 Compare ↗

Frequently Asked Questions

What does pegainfer do? +

Pure Rust + CUDA LLM inference engine — no PyTorch, OpenAI-compatible, serves Qwen3 to Kimi-K2

What language is pegainfer written in? +

The primary language is Rust. Topics include: cuda, cuda-kernels, deepseek, gpu, inference.

Is pegainfer actively maintained? +

Yes, the last recorded push was on Sep 25, 2026 with 68 open issues being tracked.

How many stars does pegainfer have? +

pegainfer has 712 stars and 110 forks on GitHub.

How does pegainfer rank among GitHub repositories? +

With 712 stars, pegainfer-project/pegainfer is ranked #3,102 globally across all repositories tracked on GitHubRepo and #320 among Rust projects.

What license is pegainfer distributed under? +

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

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