Side by side

See the difference.

Scores, capabilities and costs for the models you’re considering.

Scroll to compare models →

Comparison of embeddinggemma-300m, Intfloat: E5-Base-v2, embeddinggemma-2
3 modelsgoogleembeddinggemma-300mRemove ×intfloatIntfloat: E5-Base-v2Remove ×googleembeddinggemma-2Remove ×
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 e5-base-v2 embedding model encodes English sentences and paragraphs into a 768-dimensional dense vector space, producing efficient and high-quality semantic embeddings optimized for tasks such as…EmbeddingGemma 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,…
DateSep 16, 2025ListedNov 22, 2023ListedOct 8, 2026Listed
Listed rateSee provider quotes$0.005 in / $0.00 out/ 1M tokensOpenRouter · all routes ↗See provider quotes
Provider endpoints0 endpoints →1 endpoint →0 endpoints →
Context window2K5128.2K
Max output—460—
Parameters300M——
Open weightsNot reportedSupportedNot reported

Add another model

Search all models →