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Comparison of embeddinggemma-2, all-mpnet-base-v2, Qwen3-Embedding-8B
3 modelsgoogleembeddinggemma-2Remove ×sentence-transformersall-mpnet-base-v2Remove ×QwenQwen3-Embedding-8BRemove ×
What’s differentEmbeddingGemma 2 is a 740M parameter multimodal embedding model from Google DeepMind that maps text (incl. code), images, video and audio, alone or interleaved, into a single 768-dimensional vector space,…A sentence transformation model that has been trained on a wide range of datasets, including but not limited to S2ORC, WikiAnwers, PAQ, Stack Exchange, and Yahoo! Answers. Our model can be used for various…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…
DateOct 8, 2026ListedFeb 28, 2023ListedJun 10, 2025Listed
Listed rateSee provider quotes$0.005 in / $0.00 out/ 1M tokensOpenRouter · all routes ↗$0.01 in / $0.00 out/ 1M tokensOpenRouter · all routes ↗
Provider endpoints0 endpoints →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 window8.2K51241K
Max output—46032K
Parameters——8B
Open weightsNot reportedSupportedSupported

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