Compare Embedding Models

Side-by-side comparison of embedding model specifications

	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	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	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	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	3K	1K	—	2K
Max tokens	2K	8K	—	128K
Parameters	—	559M	350M	—
License	Proprietary	CC BY-NC 4.0	Apache 2.0	Proprietary
EMBEDDING TYPES
Types	Dense	Dense	LateColBERT	Dense
MATRYOSHKA DIMENSIONS
Available sizes	1282565127681024153620483072	32641282565121024	—	25651210241536
INPUT MODALITIES
Text	✓	✓	✓	✓
Image	—	—	—	✓
PDF	—	—	—	✓
OUTPUT TYPES
Single vector	✓	✓	—	✓
Multi vector	—	—	✓	—
LANGUAGE SUPPORT
Languages	🌍 Multi	🌍 89+	🌍 Multi	🌍 100+
PRICING
Per 1M tokens	$0.150	$0.020	—	—
BENCHMARKS
LONGEMBED	—	55.66	—	—
MMTEB	—	58.58	—	—
MTEB 1536D	68.17	—	—	—
MTEB 2048D	68.16	—	—	—
MTEB 768D	67.99	—	—	—
MTEB EN	—	54.33	—	—
MTEB MULTILINGUAL AVG	68.32	—	—	—