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	GTE-Qwen2-7B-instruct▾ 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 GTE-Qwen2-7B-instructAlibaba	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	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	1K	4K	1K	3K
Max tokens	512	32K	33K	2K
Parameters	335M	7B	677M	—
License	Apache 2.0	Apache 2.0	CC BY-NC 4.0	Proprietary
EMBEDDING TYPES
Types	Dense	Dense	Dense	Dense
MATRYOSHKA DIMENSIONS
Available sizes	641282565121024	—	32641282565127681024	1282565127681024153620483072
INPUT MODALITIES
Text	✓	✓	✓	✓
Image	—	—	—	—
PDF	—	—	—	—
OUTPUT TYPES
Single vector	✓	✓	—	✓
Multi vector	—	—	—	—
LANGUAGE SUPPORT
Languages	—	🌍 Multi	—	🌍 Multi
PRICING
Per 1M tokens	—	—	—	$0.150
BENCHMARKS
CMTEB 35	—	72.05	—	—
MMTEB	—	—	67.70	—
MTEB 1536D	—	—	—	68.17
MTEB 2048D	—	—	—	68.16
MTEB 56	—	70.24	—	—
MTEB 768D	—	—	—	67.99
MTEB AVG	64.68	—	—	—
MTEB ENGLISH V2	—	—	71.70	—
MTEB FR	—	68.25	—	—
MTEB MULTILINGUAL AVG	—	—	—	68.32
MTEB PL	—	67.86	—	—
MTEB RETRIEVAL	54.39	—	—	—
MTEB STS	85.00	—	—	—