Run large AI chat models privately on your own NVIDIA RTX 50 or RTX PRO graphics card. On one RTX 5090, Qwen3.8-27B writes about 70 words per second, 1.4x faster than vLLM. Even a model almost four times larger than the card's memory runs. Works with apps made for ChatGPT or Claude. Starts with one docker command.
⚡ Executive Summary & Quick Facts
Authoritative Sourceimp is imp is an open-source project written in C++: Run large AI chat models privately on your own NVIDIA RTX 50 or RTX PRO graphics card. On one RTX 5090, Qwen3.8-27B writes about 70 words per second, 1.4x faster than vLLM. Even a model almost four times larger than the card's memory runs. Works with apps made for ChatGPT or Claude. Starts with one docker command..
“According to real-time open source telemetry recorded on GitHubRepo.cloud (as of November 2026), kekzl/imp has accumulated 124 GitHub stars and 5 forks. It is written in C++, licensed under MIT, and ranks #22,426 globally. It is actively maintained with the latest commit recorded on Nov 1, 2026.”
| Repository | kekzl/imp ↗ |
|---|---|
| Primary Category | ai agents |
| Language & Stack | C++ |
| Software License | MIT |
| Community Traction | ★ 124 stars · ⑂ 5 forks · #22,426 globally |
| Maintenance | ● Active (Last commit: Nov 1, 2026) · 0 open issues |
| Target Audience | Developers and engineering teams building with C++, seeking reliable, tested, and actively maintained tooling for production workloads. |
🛡️ Repository Maintenance & Health Audit (2026)
Health Score: 93/100 · Grade A+Yes, imp is actively maintained. Continuous telemetry recorded the last code commit on Nov 1, 2026 (7 days ago). Supported by 124 stars and 5 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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+10
STARS · LAST 30 DAYS
1
PER DAY
#1,738
MOST-STARRED C++
| Window | 7 days | 30 days | 90 days |
|---|---|---|---|
| Stars gained | +0 | +10 | +90 |
| Per day | 1 | 1 | 1 |
| Forks gained | +0 | +3 | +10 |
imp gained 10 stars in the last 30 days, about 1 a day, and now has 124. It is about 1 year old and has averaged roughly 124 stars a year. It ranks #1,738 among C++ repositories and #22,426 across all languages on GitHubRepo.
Trending Record
6
DAYS ON TRENDING
#19629
BEST RANK
Nov 1, 2026
FIRST APPEARANCE
Active
STATUS TODAY
imp has maintained a continuous presence across global trending indexes, peaking at #19629. Below is the 30-day activity profile:
💡 Overview
imp is an open-source project written in C++: Run large AI chat models privately on your own NVIDIA RTX 50 or RTX PRO graphics card. On one RTX 5090, Qwen3.8-27B writes about 70 words per second, 1.4x faster than vLLM. Even a model almost four times larger than the card's memory runs. Works with apps made for ChatGPT or Claude. Starts with one docker command.
Engineered for speed, consistency, and developer ease, it solves common hurdles in ai-agents, blackwell, cuda. 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/kekzl/imp.git
cd imp⚙ 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
imp 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
Autonomous AI Agents
Orchestrate intelligent workflows and tool-calling routines with imp.
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
Install imp using your package manager: `git clone https://github.com/kekzl/imp.git`
Initialize your project workspace or configuration file for imp.
Import imp into your codebase or invoke it directly from your terminal.
Execute your test suite or run `imp --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
kekzl/imp is currently ranked #22,426 by stars across every repository tracked on GitHubRepo. These are adjacent projects:
| Rank | Repository | Language | Stars | Action |
|---|---|---|---|---|
| #22,344 | adhiprib/humanizer-indonesia | Python | ★ 125 | Compare ↗ |
| #22,344 | Pranjal2041/swarmchat | Python | ★ 125 | Compare ↗ |
| #22,344 | 4yk5/Ghostman | Python | ★ 125 | Compare ↗ |
| #22,344 | Aevonix/FlashAlign | Python | ★ 125 | Compare ↗ |
| #22,344 | ItzMeShadow999/BadgeMaxxer | Python | ★ 125 | Compare ↗ |
| #22,426 | kekzl/imp This Project | C++ | ★ 124 | |
| #22,426 | ruphy/speedcrunch | C++ | ★ 124 | Compare ↗ |
| #22,426 | jdf/peasycam | Java | ★ 124 | Compare ↗ |
| #22,426 | grimen/dry_scaffold | Ruby | ★ 124 | Compare ↗ |
| #22,426 | larrytheliquid/dataflow | Ruby | ★ 124 | Compare ↗ |
| #22,426 | ThomasHabets/injcode | C++ | ★ 124 | Compare ↗ |
Frequently Asked Questions
What does imp do? +
Run large AI chat models privately on your own NVIDIA RTX 50 or RTX PRO graphics card. On one RTX 5090, Qwen3.8-27B writes about 70 words per second, 1.4x faster than vLLM. Even a model almost four times larger than the card's memory runs. Works with apps made for ChatGPT or Claude. Starts with one docker command.
Is imp actively maintained in 2026? +
Yes, imp is actively maintained. The latest code push was recorded on Nov 1, 2026 (7 days ago). It holds a calculated Maintenance Health Score of 93/100 (A+ rating) with 124 stars and 0 open issues.
What language is imp written in? +
The primary language is C++. Topics include: ai-agents, blackwell, cuda, inference-engine, llm-inference.
How many stars does imp have? +
imp has 124 stars and 5 forks on GitHub.
How does imp rank among GitHub repositories? +
With 124 stars, kekzl/imp is ranked #22,426 globally across all repositories tracked on GitHubRepo and #1,738 among C++ projects.
What license is imp distributed under? +
The repository reports a MIT license. Always verify the repository LICENSE file for legal terms.
