AI · alternatives · 2026
24 alternatives to Google EmbeddingGemma 2
An open, lightweight multimodal embedding model
EmbeddingGemma 2 is Google DeepMind's open-source embedding model that converts text, code, images, video, and audio into a shared space for cross-modal search. With 740M parameters, it runs on-device with minimal RAM… Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes. Prices are shown for the 1 we have checked on their own sites, 1 of them free or with a free tier.
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Google's first natively multimodal embedding model
Mar 2026 · blog.google · its alternatives →
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End-to-end deep dive of the project, spanning a large GPU cluster, distributed RocksDB, and terabytes of sharded HNSW.
2025 · blog.wilsonl.in · its alternatives →
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We’ve recently open-sourced Model2vec, a method to distill sentence transformers into static embeddings that outperform all previous approaches by a large margin on MTEB. Our new models set a new state-of-the-art for static embeddings. Main features: - Our best model (potion-base-8M) has only 8M parameters, which is ~30mb on disk - Inference is ~500x faster than the distilled base model (bge-base), on a CPU - New models can be distilled in 30 seconds on a CPU without requiring a dataset - just a vocabulary - Numpy-only inference: The packaged can be install the package with minimal…
2024 · github.com · its alternatives →
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TranslateGemma ▲275Open translation on Google models, supporting 55 languages
Jan 2026 · blog.google · its alternatives →
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Built a ~9M param LLM from scratch to understand how they actually work. Vanilla transformer, 60K synthetic conversations, ~130 lines of PyTorch. Trains in 5 min on a free Colab T4. The fish thinks the meaning of life is food. Fork it and swap the personality for your own character.
Apr 2026 · github.com · its alternatives →
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After working with LLMs for long enough, I found myself wanting a lightweight utility for doing various small tasks to prepare inputs, locate information and create evaluators. This library is two things: a very simple model and utilities that inference it (eg. fuzzy deduplication). The target platform is CPU, and it’s intended to be light, fast and pip installable — a library that lowers the barrier to working with strings semantically. You don’t need to install pytorch to use it, or any deep learning runtimes. How can this be accomplished? The model is simply token embeddings that are…
2024 · github.com · its alternatives →
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I spent a lot of time and money on this rather big side project of mine that attempts to replicate the mechanistic interpretability research on proprietary LLMs that was quite popular this year and produced great research papers by Anthropic [1], OpenAI [2] and Deepmind [3]. I am quite proud of this project and since I consider myself the target audience for HackerNews did I think that maybe some of you would appreciate this open research replication as well. Happy to answer any questions or face any feedback. Cheers [1]…
2024 · github.com · its alternatives →
- 10WS
We’ve trained a generative AI model to browse the web and answer questions/retrieve code snippets directly. Unlike ChatGPT, it has access to primary sources and is able to cite them when you hover over an answer (click on the text to go to the source being cited). We also show regular Bing results side-by-side with our AI answer. The model is an 11-billion parameter T5-derivative that has been fine-tuned on feedback given on hundreds of thousands of searches done (anonymously) on our platform. Giving the model web access lessens its burden to need to store a snapshot of human knowledge…
2022 · beta.sayhello.so · its alternatives →
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Marengo 3.0 by TwelveLabsfree tier, from $2.5/mo▲359The most powerful embedding model for video understanding
Dec 2025 · twelvelabs.io · its alternatives →
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Embeddable▲446Hi HN, I’m a co‑founder of Embeddable AI. After struggling to add interactive AI experiences to Wix, Shopify, Webflow, WordPress sites, I built this tool to let marketers build chatbots, quizzes or assistants and embed them anywhere with a snippet. Built in React/TypeScript front end and Node.js logic engine. It loads fast and works across CMS platforms. I’d love feedback from builders and marketers on use cases, missing features, or integration ideas.
2025 · embeddable.co · its alternatives →
- 14SM
2016 · sense2vec.spacy.io · its alternatives →
- 15
Hi HN! I've found this visualization tool immensely helpful over the years for getting an intuition for how an LLM "sees" some piece of text, and with a bit of elbow grease decided to move all compute to client side so I could make it publicly available. I've found it particularly useful for - Understanding exactly how repetition and patterns affect a small LM's ability to predict correctly - Understanding different tokenization patterns and how it affects model output - Getting a general sense of how "hard" different prediction tasks are for GPT-style models Known problems (that I probably…
2023 · perplexity.vercel.app · its alternatives →
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The Virtual Feature Store. Turn your existing data infrastructure into a feature store. - featureform/featureform
2021 · github.com · its alternatives →
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Author here. I just wanted a quick and easy way to easily submit strings to a REST API and get back the embedding vectors in JSON using Llama2 and other similar LLMs, so I put this together over the past couple days. It's very quick and easy to set up and totally self-contained and self-hosted. You can easily add new models to it by simply adding the HuggingFace URL to the GGML format model weights. Two models are included by default, and these are automatically downloaded the first time it's run. It lets you not only submit text strings and get back the embeddings, but also to compare two…
2023 · github.com · its alternatives →
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A vision-language model for multiple tasks
2025 · developers.googleblog.com · its alternatives →
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Quantized word vectors that take 8x-16x less space than regular word vectors - agnusmaximus/Word2Bits
2018 · github.com · its alternatives →
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I've been playing with embeddings and wanted to try out what results the embedding layer will produce based on just word-by-word input and addition / subtraction, beyond what many videos / papers mention (like the obvious king-man+woman=queen). So I built something that doesn't just give the first answer, but ranks the matches based on distance / cosine symmetry. I polished it a bit so that others can try it out, too. For now, I only have nouns (and some proper nouns) in the dataset, and pick the most common interpretation among the homographs. Also, it's case sensitive.
2025 · calc.datova.ai · its alternatives →
- 21WA
2018 · wikipedia2vec.github.io · its alternatives →
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Long-context efficiency with DeepSeek Sparse Attention
2025 · huggingface.co · its alternatives →
- 23EA
Hello HN, I'm excited to introduce Emu2, the latest generative multimodal model developed by the Beijing Academy of Artificial Intelligence (BAAI). Emu2 is an open-source initiative that reflects BAAI's commitment to fostering open, secure, and responsible AI research. It's designed to enhance AI's proficiency in handling tasks across various modalities with minimal examples and straightforward instructions. Emu2 has demonstrated superior performance over other large-scale models like Flamingo-80B in few-shot multimodal understanding tasks. It serves as a versatile base model for developers,…
2023 · its alternatives →
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Improved vector search with open-source AI embeddings editor
2023 · its alternatives →
Also compare
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- Building a web search engine from scratch with 3B neural embeddings alternatives
- Model2vec – Lightning-fast Static Embeddings for RAG/Semantic Search alternatives
- TranslateGemma alternatives
- EmbedAI alternatives
- I built a tiny LLM to demystify how language models work alternatives
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 →