GitNova

GitHub seismograph — discoveries and growing interest

google-ai-edge/LiteRT-LM

Language modelsC++#edge-ai#on-device-ai#on-device-llm
Total stars
6,610
Today · UTC
—No data
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LiteRT-LM is Google's production-ready, high-performance, open-source inference framework for deploying Large Language Models on edge devices.

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About the project

Google's framework for running large language models on edge devices — phones, laptops, browsers and IoT — with GPU and NPU acceleration. Supports multimodal inputs, function calling and APIs for Python, Kotlin, Swift, JavaScript, Flutter and C++.

Useful for
  • Run Gemma or Llama locally on a Raspberry Pi via CLI without cloud
  • Embed an on-device LLM into an Android app with Kotlin
  • Serve an OpenAI-compatible embeddings endpoint with litert-lm serve

README summarized by DeepSeek V4.1 Flash. Details may be inaccurate.

2.1 Steady Magnitude out of 10 — how fast interest is growing, not a quality score.

Star growth looks organic. Data as of October 8, 2026, 11:14 UTC.

The star-growth assessment does not verify whether the project is safe to run.

Stars per day

01020July 11, 2026October 8, 2026

Bars show daily stars; the line is a moving average of the available history. Short histories do not yet establish a reliable usual pace. Red marks spike days.

Why it’s trending

  • There are not enough fresh counter measurements for today's UTC day. The gain is unknown.
  • GitHub Trending C++ today: #11, +15 stars.
  • Recent forks include notable developers: @uthumany (1,091 followers), @vaimalaviya1233 (578 followers).

Three GitHub discoveries in each edition

What they do, why they are gaining interest, and what to check before using them.

Editions at 10:00, 16:00, 22:00 MSK.

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Numbers

Total stars
6,610
Today
Not enough measurements today
Forks
745
Issues and pull requests
3,856
Watchers
73
Language
C++
License
Apache-2.0
Latest release
v0.18.0 · October 6, 2026
Created
April 14, 2025
Last push
October 8, 2026

Star trust

Growth looks organic: forks and discussion are in line with active projects, and stars arrive unevenly, the way people give them.

These are heuristics, not a verdict: we judge by the repository’s behavior, not by a list of stargazers.

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GitNova: 2.1 
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