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Compare Embedding Models

Side-by-side comparison of embedding model specifications

Jina Embeddings v4▾
✓ 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 v4Jina AI
Cohere Embed v4▾
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 v4Cohere
Qwen3-Embedding-8B▾
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
Qwen3-Embedding-8BQwen
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 2K 2K 4K 3K
Max tokens 33K 128K 33K 2K
Parameters 3.8B — 8B —
License Apache 2.0 Proprietary Apache 2.0 Proprietary
EMBEDDING TYPES
Types
DenseLate
Dense
Dense
Dense
MATRYOSHKA DIMENSIONS
Available sizes
12825651210242048
25651210241536
3264128256512102420484096
1282565127681024153620483072
INPUT MODALITIES
Text ✓ ✓ ✓ ✓
Image ✓ ✓ — —
PDF ✓ ✓ — —
OUTPUT TYPES
Single vector ✓ ✓ ✓ ✓
Multi vector ✓ — — —
LANGUAGE SUPPORT
Languages 🌍 29+ 🌍 100+ 🌍 100+ 🌍 Multi
PRICING
Per 1M tokens $0.050 — — $0.150
BENCHMARKS
CMTEB CHINESE — — 73.84 —
COIR 71.59 — — —
JINA VDR 84.11 — — —
LONGEMBED 67.11 — — —
MMTEB 66.49 — — —
MTEB 1536D — — — 68.17
MTEB 2048D — — — 68.16
MTEB 768D — — — 67.99
MTEB EN 55.97 — — —
MTEB EN V2 — — 75.22 —
MTEB MULTILINGUAL — — 70.58 —
MTEB MULTILINGUAL AVG — — — 68.32
VIDORE 90.17 — — —