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lightseekorg
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lightseekorg/tokenspeed

TokenSpeed is a speed-of-light LLM inference engine.

Python ◇ b200 MIT
★2.2KSTARS
⑂292FORKS
!48ISSUES
🏆#1,786GLOBAL RANK
🔥3DAYS TRENDING
🚀
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Star History

Continuous Observations
Interactive star growth chart for lightseekorg/tokenspeed
CSV

Momentum

+54

STARS · LAST 30 DAYS

2

PER DAY

#245

MOST-STARRED Python

Window7 days30 days90 days
Stars gained+14+54+180
Per day222
Forks gained+1+6+15

tokenspeed gained 54 stars in the last 30 days, about 2 a day, and now has 2.2K. It is about 1 year old and has averaged roughly 2.2K stars a year. It ranks #245 among Python repositories and #1,786 across all languages on GitHubRepo.

Trending Record

tokenspeed has maintained a continuous presence across global trending indexes, peaking at #1671. Below is the 30-day activity profile:

💡 Overview

tokenspeed is an open-source project written in Python: TokenSpeed is a speed-of-light LLM inference engine.

Engineered for speed, consistency, and developer ease, it solves common hurdles in b200, b300, blackwell. 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 Python 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
$ pip install tokenspeed

⚙ System Requirements

Platforms

  • • macOS
  • • Linux
  • • Windows

Runtime & Dependencies

Python >= 3.9, pip, virtualenv

Architecture

x86_64, ARM64 (Apple Silicon & Graviton)

🧠 How It Works

tokenspeed 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

Autonomous AI Agents

Orchestrate intelligent workflows and tool-calling routines with tokenspeed.

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 tokenspeed using your package manager: `pip install tokenspeed`

2

Initialize your project workspace or configuration file for tokenspeed.

3

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

4

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

👍 Strengths

Active community backing with 2,178 GitHub stars and verified adoption.
Permissive open-source distribution under the MIT license.
Built in Python 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 Python 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 Python, seeking reliable, tested, and actively maintained tooling for production workloads.

🏆 Nearby in the Rankings

lightseekorg/tokenspeed is currently ranked #1,786 by stars across every repository tracked on GitHubRepo. These are adjacent projects:

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Frequently Asked Questions

What does tokenspeed do? +

TokenSpeed is a speed-of-light LLM inference engine.

What language is tokenspeed written in? +

The primary language is Python. Topics include: b200, b300, blackwell, deepseek, gb200.

Is tokenspeed actively maintained? +

Yes, the last recorded push was on Sep 26, 2026 with 48 open issues being tracked.

How many stars does tokenspeed have? +

tokenspeed has 2,178 stars and 292 forks on GitHub.

How does tokenspeed rank among GitHub repositories? +

With 2,178 stars, lightseekorg/tokenspeed is ranked #1,786 globally across all repositories tracked on GitHubRepo and #245 among Python projects.

What license is tokenspeed distributed under? +

The repository reports a MIT license. Always verify the repository LICENSE file for legal terms.

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