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AI · alternatives · 2026

24 alternatives to Gemma

Google’s new state-of-the-art open source LLMs

Gemma is a family of open source large language models built by Google using the same research and technology behind its Gemini models. Designed for developers, these lightweight models aim to deliver high performance… Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes. Gemma launched in 2024; newer entries below may have overtaken it.

  1. 1
    Gemma 2▲279

    Lightweight, state-of-the-art open models from Google

    2024 · blog.google · its alternatives →

  2. 2

    Google's most intelligent open models to date

    Apr 2026 · blog.google · its alternatives →

  3. 3

    New state-of-the-art open models

    2024 · deepmind.google · its alternatives →

  4. 4
    Gemma 3▲200

    Build with multimodal AI from Google

    2025 · deepmind.google · its alternatives →

  5. 5
    Gemma 3n▲199

    Run powerful multimodal AI right on your phone

    2025 · developers.googleblog.com · its alternatives →

  6. 6

    Gemma Gem is a Chrome extension that loads Google's Gemma 4 (2B) through WebGPU in an offscreen document and gives it tools to interact with any webpage: read content, take screenshots, click elements, type text, scroll, and run JavaScript. You get a small chat overlay on every page. Ask it about the page and it (usually) figures out which tools to call. It has a thinking mode that shows chain-of-thought reasoning as it works. It's a 2B model in a browser. It works for simple page questions and running JavaScript, but multi-step tool chains are unreliable and it sometimes ignores its tools…

    Apr 2026 · github.com · its alternatives →

  7. 7

    Hey HN, Henry & Roman here from Cactus. A small, on-device model is fast and private, but sometimes wrong, but frontier models are getting expensive pretty fast. So, we post-trained Gemma 4 E2B post-trained to know when it's wrong. Every response comes with a confidence score between 0 and 1. Developers can accept the on-device when it's high, hand off to a bigger cloud model when it's low. By routing only 15-35% of queries to Gemini 3.1 Flash-Lite, Gemma-4-E2B matches Gemini 3.1 Flash-Lite on most benchmarks. - ChartQA: 15-20% - LibriSpeech: 25-30% - MMBench, GigaSpeech, MMAU: 30-35% -…

    Jul 2026 · github.com · its alternatives →

  8. 8
    Gemini▲528

    Google's answer to GPT-4

    2023 · blog.google · its alternatives →

  9. 9

    A simple weekend project, to check if chat conversation could be used on CLI. Uses Google Gemini's gemini-2.0-flash model. Configs will make it nicer, but I wanted to keep it simple to test and launch for now. I can add things for you :) Please give it a try!

    2025 · blog.google · its alternatives →

  10. 10
    Gemini 3▲1,016

    Bring any idea to life with multimodal capabilities

    Nov 2025 · blog.google · its alternatives →

  11. 11

    Google Gemma Chat Free

    2024 · its alternatives →

  12. 12

    Hi HN, I built a specialized inference engine for running 4-bit Gemma 4 26B-A4B-IT on any M-series Mac using about 2 GB of RAM. It is called TurboFieldfare and is written in Swift and Metal. I have always adored on-device AI. It feels like magic that you can run a powerful NN on your Mac or iPhone. So I wanted to push the limits a bit and run a model whose weights don’t fit in memory. The model’s 4-bit quantized weights occupy roughly 14 GB, which makes running it with conventional inference tools almost impossible on an 8 GB or even 16 GB Mac once the OS, applications, and KV cache are…

    Jul 2026 · github.com · its alternatives →

  13. 13

    Open translation on Google models, supporting 55 languages

    Jan 2026 · blog.google · its alternatives →

  14. 14

    Try google's most advanced open model for free

    2025 · its alternatives →

  15. 15

    Chatbot powered by Google's Gemma 7B & Supervised Max models

    2024 · its alternatives →

  16. 16

    Hey HN, Henry here from Cactus. We open-sourced Needle, a 26M parameter function-calling (tool use) model. It runs at 6000 tok/s prefill and 1200 tok/s decode on consumer devices. We were always frustrated by the little effort made towards building agentic models that run on budget phones, so we conducted investigations that led to an observation: agentic experiences are built upon tool calling, and massive models are overkill for it. Tool calling is fundamentally retrieval-and-assembly (match query to tool name, extract argument values, emit JSON), not reasoning. Cross-attention…

    May 2026 · github.com · its alternatives →

  17. 17IR
  18. 18
    TxGemma▲134

    AI models for faster drug development

    2025 · developers.googleblog.com · its alternatives →

  19. 19

    Google's first natively multimodal embedding model

    Mar 2026 · blog.google · its alternatives →

  20. 20
    ROMA▲121

    The backbone for open-source meta-agents

    2025 · sentient.xyz · its alternatives →

  21. 21

    Fine-tuned Gemma 2: 2B model for Kazakh Instructions (SLLM)

    2025 · huggingface.co · its alternatives →

  22. 22

    About six months ago, I started working on a project to fine-tune Whisper locally on my M2 Ultra Mac Studio with a limited compute budget. I got into it. The problem I had at the time was I had 15,000 hours of audio data in Google Cloud Storage, and there was no way I could fit all the audio onto my local machine, so I built a system to stream data from my GCS to my machine during training. Gemma 3n came out, so I added that. Kinda went nuts, tbh. Then I put it on the shelf. When Gemma 4 came out a few days ago, I dusted it off, cleaned it up, broke out the Gemma part from the Whisper…

    Apr 2026 · github.com · its alternatives →

  23. 23

    Computer use but with OpenAI and Gemini models

    2024 · github.com · its alternatives →

  24. 24

    Run leading vision models locally with the new engine

    2025 · ollama.com · its alternatives →

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Ranked by how close each launch is in meaning, then by votes. Prices were read from each product’s own site when checked and can change. Refine with your own description →