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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
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
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
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 4K 1K 768 2K
Max tokens 33K 512 8K 128K
Parameters 8B 335M 239M —
License Apache 2.0 Apache 2.0 CC BY-NC 4.0 Proprietary
EMBEDDING TYPES
Types
Dense
Dense
Dense
Dense
MATRYOSHKA DIMENSIONS
Available sizes
3264128256512102420484096
641282565121024
3264128256512768
25651210241536
INPUT MODALITIES
Text ✓ ✓ ✓ ✓
Image — — — ✓
PDF — — — ✓
OUTPUT TYPES
Single vector ✓ ✓ — ✓
Multi vector — — — —
LANGUAGE SUPPORT
Languages 🌍 100+ — — 🌍 100+
PRICING
Per 1M tokens — — — —
BENCHMARKS
CMTEB CHINESE 73.84 — — —
MMTEB — — 65.50 —
MTEB AVG — 64.68 — —
MTEB EN V2 75.22 — — —
MTEB ENGLISH V2 — — 71.00 —
MTEB MULTILINGUAL 70.58 — — —
MTEB RETRIEVAL — 54.39 — —
MTEB STS — 85.00 — —