Compare Embedding Models

Side-by-side comparison of embedding model specifications

	Jina Embeddings v5 Omni Nano▾ 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 NanoJina AI	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	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	768	4K	3K	2K
Max tokens	8K	4K	2K	128K
Parameters	1.04B	7B	—	—
License	CC BY-NC 4.0	Apache 2.0	Proprietary	Proprietary
EMBEDDING TYPES
Types	Dense	Dense	Dense	Dense
MATRYOSHKA DIMENSIONS
Available sizes	3264128256512768	—	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	—	68.20	—	—
MTEB MULTILINGUAL AVG	—	—	68.32	—
MTEB RETRIEVAL	—	60.20	—	—