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Comparison of Perplexity: Embed V1 4B, Intfloat: Multilingual-E5-Large, Qwen3-Embedding-8B
3 modelsperplexityPerplexity: Embed V1 4BRemove ×intfloatIntfloat: Multilingual-E5-LargeRemove ×QwenQwen3-Embedding-8BRemove ×
What’s differentpplx-embed-v1 -4B is one of Perplexity's state-of-the-art text embedding models built for real-world, web-scale retrieval. pplx-embed-v1 is optimized for standard dense text retrieval with the 4B parameter…The multilingual-e5-large embedding model encodes sentences, paragraphs, and documents across over 90 languages into a 1024-dimensional dense vector space, delivering robust semantic embeddings optimized…The Qwen3 Embedding model series is the latest proprietary model of the Qwen family, specifically designed for text embedding and ranking tasks. Building upon the dense foundational models of the Qwen3…
DateMar 16, 2026ListedJun 4, 2024ListedJun 10, 2025Listed
Listed rate$0.03 in / $0.00 out/ 1M tokensOpenRouter · all routes ↗$0.01 in / $0.00 out/ 1M tokensOpenRouter · all routes ↗$0.01 in / $0.00 out/ 1M tokensOpenRouter · all routes ↗
Provider endpoints1 endpoint →1 endpoint →1 endpoint →
FreshStack · MTEB 1.38.43 ↗MTEB 1.38.43; test/default; dataset 7a20df1aNot reportedNot reported0.43017 ↗Revision 4e423935; test/defaultContributor reported
Context window32K51241K
Max output28.8K46032K
Parameters4B—8B
Open weightsNot reportedSupportedSupported

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