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Compare Embedding Models

Side-by-side comparison of embedding model specifications

Gemini Embedding 001▾
Jina Embeddings v4 Jina Embeddings v3 Qwen3-Embedding-8B✓ Gemini Embedding 001 mxbai-embed-large-v1 Cohere Embed v4 Cohere Embed English v3 Cohere Embed Multilingual v3 Voyage 3 Large GTE-Qwen2-7B-instruct Linq-Embed-Mistral LFM2-ColBERT-350M Jina Embeddings v5 Omni Small Jina Embeddings v5 Omni Nano Jina Embeddings v5 Omni Nano Text-Matching Jina Embeddings v5 Text Small Jina Embeddings v5 Text Nano Jina Embeddings v5 Text Small Text-Matching
Gemini Embedding 001Google
Gemini Embedding 001▾
Jina Embeddings v4 Jina Embeddings v3 Qwen3-Embedding-8B✓ Gemini Embedding 001 mxbai-embed-large-v1 Cohere Embed v4 Cohere Embed English v3 Cohere Embed Multilingual v3 Voyage 3 Large GTE-Qwen2-7B-instruct Linq-Embed-Mistral LFM2-ColBERT-350M Jina Embeddings v5 Omni Small Jina Embeddings v5 Omni Nano Jina Embeddings v5 Omni Nano Text-Matching Jina Embeddings v5 Text Small Jina Embeddings v5 Text Nano Jina Embeddings v5 Text Small Text-Matching
Gemini Embedding 001Google
Jina Embeddings v5 Text Small▾
Jina Embeddings v4 Jina Embeddings v3 Qwen3-Embedding-8B Gemini Embedding 001 mxbai-embed-large-v1 Cohere Embed v4 Cohere Embed English v3 Cohere Embed Multilingual v3 Voyage 3 Large GTE-Qwen2-7B-instruct Linq-Embed-Mistral LFM2-ColBERT-350M Jina Embeddings v5 Omni Small Jina Embeddings v5 Omni Nano Jina Embeddings v5 Omni Nano Text-Matching✓ Jina Embeddings v5 Text Small Jina Embeddings v5 Text Nano Jina Embeddings v5 Text Small Text-Matching
Jina Embeddings v5 Text SmallJina AI
Cohere Embed English v3▾
Jina Embeddings v4 Jina Embeddings v3 Qwen3-Embedding-8B Gemini Embedding 001 mxbai-embed-large-v1 Cohere Embed v4✓ Cohere Embed English v3 Cohere Embed Multilingual v3 Voyage 3 Large GTE-Qwen2-7B-instruct Linq-Embed-Mistral LFM2-ColBERT-350M Jina Embeddings v5 Omni Small Jina Embeddings v5 Omni Nano Jina Embeddings v5 Omni Nano Text-Matching Jina Embeddings v5 Text Small Jina Embeddings v5 Text Nano Jina Embeddings v5 Text Small Text-Matching
Cohere Embed English v3Cohere
SPECIFICATIONS
Max dimension 3K 3K 1K 1K
Max tokens 2K 2K 33K 512
Parameters — — 677M —
License Proprietary Proprietary CC BY-NC 4.0 Proprietary
EMBEDDING TYPES
Types
Dense
Dense
Dense
Dense
MATRYOSHKA DIMENSIONS
Available sizes
1282565127681024153620483072
1282565127681024153620483072
32641282565127681024
—
INPUT MODALITIES
Text ✓ ✓ ✓ ✓
Image — — — ✓
PDF — — — —
OUTPUT TYPES
Single vector ✓ ✓ — ✓
Multi vector — — — —
LANGUAGE SUPPORT
Languages 🌍 Multi 🌍 Multi — —
PRICING
Per 1M tokens $0.150 $0.150 — —
BENCHMARKS
MMTEB — — 67.70 —
MTEB 1536D 68.17 68.17 — —
MTEB 2048D 68.16 68.16 — —
MTEB 768D 67.99 67.99 — —
MTEB AVG — — — 64.47
MTEB ENGLISH V2 — — 71.70 —
MTEB MULTILINGUAL AVG 68.32 68.32 — —
MTEB RETRIEVAL — — — 55.00