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Compare Embedding Models

Side-by-side comparison of embedding model specifications

Linq-Embed-Mistral▾
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
Linq-Embed-MistralLinq 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
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
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 4K 1K 1K 4K
Max tokens 4K 8K 33K 33K
Parameters 7B 559M 677M 8B
License Apache 2.0 CC BY-NC 4.0 CC BY-NC 4.0 Apache 2.0
EMBEDDING TYPES
Types
Dense
Dense
Dense
Dense
MATRYOSHKA DIMENSIONS
Available sizes —
32641282565121024
32641282565127681024
3264128256512102420484096
INPUT MODALITIES
Text ✓ ✓ ✓ ✓
Image — — — —
PDF — — — —
OUTPUT TYPES
Single vector ✓ ✓ — ✓
Multi vector — — — —
LANGUAGE SUPPORT
Languages 🌍 Multi 🌍 89+ — 🌍 100+
PRICING
Per 1M tokens — $0.020 — —
BENCHMARKS
CMTEB CHINESE — — — 73.84
LONGEMBED — 55.66 — —
MMTEB — 58.58 67.70 —
MTEB AVG 68.20 — — —
MTEB EN — 54.33 — —
MTEB EN V2 — — — 75.22
MTEB ENGLISH V2 — — 71.70 —
MTEB MULTILINGUAL — — — 70.58
MTEB RETRIEVAL 60.20 — — —