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Comparison of embeddinggemma-300m, gte-large, VoyageAI by MongoDB: voyage-4-lite
3 modelsgoogleembeddinggemma-300mRemove ×thenlpergte-largeRemove ×voyageaiVoyageAI by MongoDB: voyage-4-liteRemove ×
What’s differentEmbeddingGemma is a 300M parameter multilingual open embedding model from Google DeepMind, designed for efficient deployment even on low-resource devices, producing high-quality text vector representations…The 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…voyage-4-lite is a lightweight, general-purpose embedding model optimized for low latency and cost. Enabled by Matryoshka learning and quantization-aware training, voyage-4-lite supports embeddings in 2048,…
DateSep 16, 2025ListedNov 22, 2023ListedJul 27, 2026Listed
Listed rateSee provider quotes$0.01 in / $0.00 out/ 1M tokensOpenRouter · all routes ↗$0.02 in / $0.00 out/ 1M tokensOpenRouter · all routes ↗
Provider endpoints0 endpoints →1 endpoint →1 endpoint →
Context window2K51232K
Max output—46028.8K
Parameters300M——
Open weightsNot reportedSupportedNot reported

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