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Compare Embedding Models

Side-by-side comparison of embedding model specifications

Linq-Embed-Mistral▾
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
Linq-Embed-MistralLinq AI
Jina Embeddings v5 Omni 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 Omni SmallJina AI
Jina Embeddings 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
Jina Embeddings v3Jina AI
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
SPECIFICATIONS
Max dimension 4K 1K 1K 3K
Max tokens 4K 33K 8K 2K
Parameters 7B 1.74B 559M —
License Apache 2.0 CC BY-NC 4.0 CC BY-NC 4.0 Proprietary
EMBEDDING TYPES
Types
Dense
Dense
Dense
Dense
MATRYOSHKA DIMENSIONS
Available sizes —
32641282565127681024
32641282565121024
1282565127681024153620483072
INPUT MODALITIES
Text ✓ ✓ ✓ ✓
Image — ✓ — —
PDF — ✓ — —
OUTPUT TYPES
Single vector ✓ — ✓ ✓
Multi vector — — — —
LANGUAGE SUPPORT
Languages 🌍 Multi — 🌍 89+ 🌍 Multi
PRICING
Per 1M tokens — — $0.020 $0.150
BENCHMARKS
LONGEMBED — — 55.66 —
MMTEB — — 58.58 —
MTEB 1536D — — — 68.17
MTEB 2048D — — — 68.16
MTEB 768D — — — 67.99
MTEB AVG 68.20 — — —
MTEB EN — — 54.33 —
MTEB MULTILINGUAL AVG — — — 68.32
MTEB RETRIEVAL 60.20 — — —