InferMatrixLab/vllm-rlt
A vLLM-inspired inference engine for looped transformers, with loop-level scheduling and execution across composable stages
⚡ Executive Summary & Quick Facts
Authoritative Sourcevllm-rlt is vllm-rlt is an open-source project written in Python: vllm based inference engine for looped transformer..
“According to real-time open source telemetry recorded on GitHubRepo.cloud (as of November 2026), InferMatrixLab/vllm-rlt has accumulated 214 GitHub stars and 34 forks. It is written in Python, licensed under Apache-2.0, and ranks #16,481 globally. It is actively maintained with the latest commit recorded on Oct 31, 2026.”
| Repository | InferMatrixLab/vllm-rlt ↗ |
|---|---|
| Primary Category | inference engine |
| Language & Stack | Python |
| Software License | Apache-2.0 |
| Community Traction | ★ 214 stars · ⑂ 34 forks · #16,481 globally |
| Maintenance | ● Active (Last commit: Oct 31, 2026) · 41 open issues |
| Target Audience | Developers and engineering teams building with Python, seeking reliable, tested, and actively maintained tooling for production workloads. |
🛡️ Repository Maintenance & Health Audit (2026)
Health Score: 93/100 · Grade A+Yes, vllm-rlt is actively maintained. Continuous telemetry recorded the last code commit on Oct 31, 2026 (2 days ago). Supported by 214 stars and 34 community forks, this repository holds a calculated health index of 93/100, reflecting very active (commits within last 14 days) and healthy issue cadence.
Star History
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Momentum
+92
STARS · LAST 30 DAYS
3
PER DAY
#2,121
MOST-STARRED Python
| Window | 7 days | 30 days | 90 days |
|---|---|---|---|
| Stars gained | +92 | +92 | +270 |
| Per day | 13 | 3 | 3 |
| Forks gained | +10 | +10 | +10 |
vllm-rlt gained 92 stars in the last 30 days, about 3 a day, and now has 214. It is about 1 year old and has averaged roughly 214 stars a year. It ranks #2,121 among Python repositories and #16,481 across all languages on GitHubRepo.
Trending Record
38
DAYS ON TRENDING
#508
BEST RANK
Sep 24, 2026
FIRST APPEARANCE
Active
STATUS TODAY
vllm-rlt has maintained a continuous presence across global trending indexes, peaking at #508. Below is the 30-day activity profile:
💡 Overview
vllm-rlt is an open-source project written in Python: vllm based inference engine for looped transformer.
Engineered for speed, consistency, and developer ease, it solves common hurdles in Python. 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 Python 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
$ pip install vllm-rlt
⚙ System Requirements
Platforms
- • macOS
- • Linux
- • Windows
Runtime & Dependencies
Python >= 3.9, pip, virtualenv
Architecture
x86_64, ARM64 (Apple Silicon & Graviton)
🧠 How It Works
vllm-rlt coordinates its core functionality through a modular Python 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 vllm-rlt into Python 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 vllm-rlt using your package manager: `pip install vllm-rlt`
Initialize your project workspace or configuration file for vllm-rlt.
Import vllm-rlt into your codebase or invoke it directly from your terminal.
Execute your test suite or run `vllm-rlt --help` to verify successful setup.
👍 Strengths
⚠️ Considerations
⇄ Alternatives & Direct Competitors
👥 Who Should Use This
Developers and engineering teams building with Python, seeking reliable, tested, and actively maintained tooling for production workloads.
🏆 Nearby in the Rankings
InferMatrixLab/vllm-rlt is currently ranked #16,481 by stars across every repository tracked on GitHubRepo. These are adjacent projects:
| Rank | Repository | Language | Stars | Action |
|---|---|---|---|---|
| #16,453 | ovh/ovhcloud-cli | Go | ★ 215 | Compare ↗ |
| #16,453 | MorpheApp/morphe-patcher | Kotlin | ★ 215 | Compare ↗ |
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| #16,481 | InferMatrixLab/vllm-rlt This Project | Python | ★ 214 | |
| #16,481 | jstrait/wavefile | Ruby | ★ 214 | Compare ↗ |
| #16,481 | troglobit/pimd | C | ★ 214 | Compare ↗ |
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| #16,481 | pulse00/Symfony-2-Eclipse-Plugin | Java | ★ 214 | Compare ↗ |
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Frequently Asked Questions
What does vllm-rlt do? +
A vLLM-inspired inference engine for looped transformers, with loop-level scheduling and execution across composable stages
Is vllm-rlt actively maintained in 2026? +
Yes, vllm-rlt is actively maintained. The latest code push was recorded on Oct 31, 2026 (2 days ago). It holds a calculated Maintenance Health Score of 93/100 (A+ rating) with 214 stars and 41 open issues.
What language is vllm-rlt written in? +
The primary language is Python. Topics include: inference-engine, llm, transformer.
How many stars does vllm-rlt have? +
vllm-rlt has 214 stars and 34 forks on GitHub.
How does vllm-rlt rank among GitHub repositories? +
With 214 stars, InferMatrixLab/vllm-rlt is ranked #16,481 globally across all repositories tracked on GitHubRepo and #2,121 among Python projects.
What license is vllm-rlt distributed under? +
The repository reports a Apache-2.0 license. Always verify the repository LICENSE file for legal terms.