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 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	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	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
SPECIFICATIONS
Max dimension	1K	1K	1K	1K
Max tokens	512	33K	8K	512
Parameters	—	677M	559M	335M
License	Proprietary	CC BY-NC 4.0	CC BY-NC 4.0	Apache 2.0
EMBEDDING TYPES
Types	Dense	Dense	Dense	Dense
MATRYOSHKA DIMENSIONS
Available sizes	—	32641282565127681024	32641282565121024	641282565121024
INPUT MODALITIES
Text	✓	✓	✓	✓
Image	✓	—	—	—
PDF	—	—	—	—
OUTPUT TYPES
Single vector	✓	—	✓	✓
Multi vector	—	—	—	—
LANGUAGE SUPPORT
Languages	🌍 100+	—	🌍 89+	—
PRICING
Per 1M tokens	—	—	$0.020	—
BENCHMARKS
LONGEMBED	—	—	55.66	—
MMTEB	—	67.70	58.58	—
MTEB AVG	—	—	—	64.68
MTEB EN	—	—	54.33	—
MTEB ENGLISH V2	—	71.70	—	—
MTEB RETRIEVAL	—	—	—	54.39
MTEB STS	—	—	—	85.00