Compare Embedding Models

Side-by-side comparison of embedding model specifications

	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	Jina Embeddings v5 Text 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 Text NanoJina 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	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
SPECIFICATIONS
Max dimension	4K	768	4K	—
Max tokens	33K	8K	33K	—
Parameters	8B	239M	8B	350M
License	Apache 2.0	CC BY-NC 4.0	Apache 2.0	Apache 2.0
EMBEDDING TYPES
Types	Dense	Dense	Dense	LateColBERT
MATRYOSHKA DIMENSIONS
Available sizes	3264128256512102420484096	3264128256512768	3264128256512102420484096	—
INPUT MODALITIES
Text	✓	✓	✓	✓
Image	—	—	—	—
PDF	—	—	—	—
OUTPUT TYPES
Single vector	✓	—	✓	—
Multi vector	—	—	—	✓
LANGUAGE SUPPORT
Languages	🌍 100+	—	🌍 100+	🌍 Multi
PRICING
Per 1M tokens	—	—	—	—
BENCHMARKS
CMTEB CHINESE	73.84	—	73.84	—
MMTEB	—	65.50	—	—
MTEB EN V2	75.22	—	75.22	—
MTEB ENGLISH V2	—	71.00	—	—
MTEB MULTILINGUAL	70.58	—	70.58	—