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Comparison of gte-base, Intfloat: E5-Large-v2, LiquidAI: LFM2.5-Embedding-350M (free)
3 modelsthenlpergte-baseRemove ×intfloatIntfloat: E5-Large-v2Remove ×liquidLiquidAI: LFM2.5-Embedding-350M (free)Remove ×
What’s differentThe GTE models are trained by Alibaba DAMO Academy. They are mainly based on the BERT framework and currently offer three different sizes of models, including GTE-large, GTE-base, and GTE-small. The GTE…The e5-large-v2 embedding model maps English sentences, paragraphs, and documents into a 1024-dimensional dense vector space, delivering high-accuracy semantic embeddings optimized for retrieval, semantic…LFM2.5-Embedding-350M is a text embedding model from Liquid AI. It produces 1,024-dimensional embeddings for retrieval and semantic search. Successful OpenRouter requests and embeddings may be retained and…
DateNov 22, 2023ListedNov 22, 2023ListedAug 18, 2026Listed
Listed rate$0.005 in / $0.00 out/ 1M tokensOpenRouter · all routes ↗$0.01 in / $0.00 out/ 1M tokensOpenRouter · all routes ↗$0.00 in / $0.00 out/ 1M tokensOpenRouter · all routes ↗
Provider endpoints1 endpoint →1 endpoint →1 endpoint →
Context window512512512
Max output460460460
Parameters———
Open weightsSupportedSupportedSupported

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