Compare Embedding Models

Side-by-side comparison of embedding model specifications

	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	Jina Embeddings v5 Text Small Text-Matching▾ 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 Small Text-MatchingJina 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	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	2K	1K	—	4K
Max tokens	33K	33K	—	33K
Parameters	3.8B	677M	350M	8B
License	Apache 2.0	CC BY-NC 4.0	Apache 2.0	Apache 2.0
EMBEDDING TYPES
Types	DenseLate	Dense	LateColBERT	Dense
MATRYOSHKA DIMENSIONS
Available sizes	12825651210242048	32641282565127681024	—	3264128256512102420484096
INPUT MODALITIES
Text	✓	✓	✓	✓
Image	✓	—	—	—
PDF	✓	—	—	—
OUTPUT TYPES
Single vector	✓	—	—	✓
Multi vector	✓	—	✓	—
LANGUAGE SUPPORT
Languages	🌍 29+	—	🌍 Multi	🌍 100+
PRICING
Per 1M tokens	$0.050	—	—	—
BENCHMARKS
CMTEB CHINESE	—	—	—	73.84
COIR	71.59	—	—	—
JINA VDR	84.11	—	—	—
LONGEMBED	67.11	—	—	—
MMTEB	66.49	—	—	—
MTEB EN	55.97	—	—	—
MTEB EN V2	—	—	—	75.22
MTEB MULTILINGUAL	—	—	—	70.58
VIDORE	90.17	—	—	—