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Comparison of codestral-embed, Intfloat: E5-Base-v2, embeddinggemma-2
3 modelsUnknowncodestral-embedRemove ×intfloatIntfloat: E5-Base-v2Remove ×googleembeddinggemma-2Remove ×
What’s different8.2K contextThe 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,…
DateOct 16, 2026DiscoveredNov 22, 2023ListedOct 8, 2026Listed
Listed rate$0.15 in / $0.00 out/ 1M tokensExperiential · all routes ↗Standard list rate$0.005 in / $0.00 out/ 1M tokensOpenRouter · all routes ↗See provider quotes
Provider endpoints1 endpoint →1 endpoint →0 endpoints →
Context window8.2K5128.2K
Max output—460—
Parameters———
Open weightsNot reportedSupportedNot reported

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