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Compare Embedding Models

Side-by-side comparison of embedding model specifications

mxbai-embed-large-v1▾
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
mxbai-embed-large-v1Mixedbread
LFM2-ColBERT-350M▾
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
LFM2-ColBERT-350MLiquid 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
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
SPECIFICATIONS
Max dimension 1K — 3K 2K
Max tokens 512 — 2K 128K
Parameters 335M 350M — —
License Apache 2.0 Apache 2.0 Proprietary Proprietary
EMBEDDING TYPES
Types
Dense
LateColBERT
Dense
Dense
MATRYOSHKA DIMENSIONS
Available sizes
641282565121024
—
1282565127681024153620483072
25651210241536
INPUT MODALITIES
Text ✓ ✓ ✓ ✓
Image — — — ✓
PDF — — — ✓
OUTPUT TYPES
Single vector ✓ — ✓ ✓
Multi vector — ✓ — —
LANGUAGE SUPPORT
Languages — 🌍 Multi 🌍 Multi 🌍 100+
PRICING
Per 1M tokens — — $0.150 —
BENCHMARKS
MTEB 1536D — — 68.17 —
MTEB 2048D — — 68.16 —
MTEB 768D — — 67.99 —
MTEB AVG 64.68 — — —
MTEB MULTILINGUAL AVG — — 68.32 —
MTEB RETRIEVAL 54.39 — — —
MTEB STS 85.00 — — —