BGE-M3 or Jina Embeddings: which embedding model to pick
Both models search by meaning across many languages, including Russian, and run on a CPU. BGE-M3 is a single 568M release from 2024-01 under MIT, available in Ollama, so it installs in one command and sits comfortably in a commercial product. Jina moves faster: a range from 33M to 3.8B, long context, and a recent v5-omni from 2026-05 that handles text, images and audio. The licenses need reading though: v2 is Apache 2.0, v4 uses the Qwen Research License, and v3 and v5 are CC-BY-NC, so a business needs a paid license. For production without legal questions BGE-M3 is simpler; for search across images and scans Jina is stronger.
Comparison based on catalog data
| Parameter | BGE-M3 | Jina Embeddings |
|---|---|---|
| Category | Search and RAG | Search and RAG |
| Developer | BAAI, China | Jina AI, Germany |
| Releases | Jan 2024 – Jan 2024 | Sep 2023 – May 2026 |
| Sizes | 568M | 33M – 3.8B |
| Hardware | Laptop | Laptop, 1 GPU |
| Commercial use | Commercial use allowed | Commercial use with conditions |
| License | MIT | v2: Apache 2.0; v3 and v5: CC-BY-NC (non-commercial only, businesses need a paid license); v4: Qwen Research License |
| Russian | Supported | Supported |
| Ollama | Yes | No |
| Without GPU | Yes | Yes |
| Tasks |
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Choose BGE-M3 if
- You need an unconditional MIT license for a commercial product
- You want a one-command install through Ollama
- Classic RAG over a text knowledge base in Russian and other languages
Choose Jina Embeddings if
- You need search across images, scans and audio, not just text
- You need a very small model from 33M, or a large one up to 3.8B
- The project is non-commercial, or you are ready to buy a paid license
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