Compare Embedding Models

Side-by-side comparison of embedding model specifications

	Cohere Embed Multilingual 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 Cohere Embed Multilingual v3Cohere	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	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	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
SPECIFICATIONS
Max dimension	1K	1K	2K	4K
Max tokens	512	8K	33K	33K
Parameters	—	559M	3.8B	8B
License	Proprietary	CC BY-NC 4.0	Apache 2.0	Apache 2.0
EMBEDDING TYPES
Types	Dense	Dense	DenseLate	Dense
MATRYOSHKA DIMENSIONS
Available sizes	—	32641282565121024	12825651210242048	3264128256512102420484096
INPUT MODALITIES
Text	✓	✓	✓	✓
Image	✓	—	✓	—
PDF	—	—	✓	—
OUTPUT TYPES
Single vector	✓	✓	✓	✓
Multi vector	—	—	✓	—
LANGUAGE SUPPORT
Languages	🌍 100+	🌍 89+	🌍 29+	🌍 100+
PRICING
Per 1M tokens	—	$0.020	$0.050	—
BENCHMARKS
CMTEB CHINESE	—	—	—	73.84
COIR	—	—	71.59	—
JINA VDR	—	—	84.11	—
LONGEMBED	—	55.66	67.11	—
MMTEB	—	58.58	66.49	—
MTEB EN	—	54.33	55.97	—
MTEB EN V2	—	—	—	75.22
MTEB MULTILINGUAL	—	—	—	70.58
VIDORE	—	—	90.17	—