Model comparison
Compare EmbeddingGemma 2 and text-embedding-3-large using the same provider-sourced embeddings & vector search rubric. No mystery score and no invented benchmark ranking.
Set your usage. Your estimate updates as you type.
Assumes 600 tokens per page, processed separately. Actual token counts vary. This covers embedding only, not storage, search, or generated answers.
Estimates exclude taxes, tools, cache storage/writes, free allowances and custom discounts. Image estimates cover output only, not prompt or reference-image charges. Quality modes differ by model. Unlisted settings are not treated as free.
| Model | Access | Estimated total (USD) |
|---|---|---|
| text-embedding-3-largeOpenAI | OpenAI | $0.0008 |
| EmbeddingGemma 2Google DeepMind | Google DeepMind | No reviewed rate |
Quick take
Google DeepMind's open-weight embedding model for local search across text, code, images, audio, and video.
Open weights do not make compute free. Rebuild and evaluate the index when changing models, use the documented numerical precision, and verify truncated vectors on your own data.
OpenAI's highest-capability text embedding model for semantic search, recommendations, clustering, and retrieval pipelines.
The model embeds text only and does not chunk long documents for you. Your ingestion pipeline still needs a deliberate chunking, metadata, evaluation, and re-indexing strategy.
Compare the published facts
Values use each provider's own published units and limits. A blank means the provider did not publish a directly comparable value in the sources reviewed.
| Embeddings & vector search | EmbeddingGemma 2 | text-embedding-3-large |
|---|---|---|
| Embedding priceCurrent provider price per million input tokens or the closest published billing unit. | Open weights; self-hosted | $0.13 / 1M tokens |
| Input capacityMaximum content accepted in one embedding input, using the provider's documented token basis. | 8,192 shared tokens across text and media | 8,191 input tokens |
| Vector dimensionsSupported output sizes; smaller vectors reduce storage while larger vectors may preserve more information. | 768 default; 512, 256, or 128 with re-normalization | 3,072 default; shorter vectors via dimensions |
| Accepted inputsText, code, image, audio, video, PDF, or document-aware input supported by the endpoint. | Text, code, images, audio, and sampled video frames | Text |
| Retrieval controlsQuery/document modes, task types, truncation, chunking, or other controls that shape vectors for retrieval. | Task prompts, selective encoders, vector truncation, and normalization | Optional dimensions parameter; chunking handled by the application |
| Where it runsDirect API, cloud marketplace, private deployment, or self-hosted route documented by the provider. | Local or self-hosted; Apache 2.0 weights | OpenAI hosted Embeddings API |
How to choose
Start with the job you need to complete, then validate cost, access, and policy details on your exact provider route.
Inference can run locally without sending source content to an embedding API. Data retention and network access depend on the application and services you connect.
OpenAI says business and API data is not used to train its models by default. Abuse-monitoring retention and eligible zero-data-retention controls depend on the endpoint and organization approval.
Provider and API links
Frequently asked questions
EmbeddingGemma 2: Google DeepMind's open-weight embedding model for local search across text, code, images, audio, and video. text-embedding-3-large: OpenAI's highest-capability text embedding model for semantic search, recommendations, clustering, and retrieval pipelines.
Consider EmbeddingGemma 2 when your priority is Local and offline multimodal search. Consider text-embedding-3-large when your priority is High-quality text search and RAG. Test both with your own data and provider route before committing.
No. This comparison aligns provider-published facts for the Embeddings & vector search category. It does not claim a universal winner or combine incompatible third-party benchmark scores.
