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Comparison of multilingual-e5-large-instruct, drex-v1.5, embeddinggemma-2
3 modelsintfloatmultilingual-e5-large-instructRemove ×nace-aidrex-v1.5Remove ×googleembeddinggemma-2Remove ×
What’s differentThe Multilingual-E5 models, initialized from XLM-RoBERTa, support up to 512 tokens per input — any longer text will be silently truncated. To ensure optimal performance, always prefix inputs with “query:”…Drex v1.5 is a 9B decision model from Nace.AI. Given a state (text or JSON) and typed questions (yes/no, multiple choice, or ordinal score), it returns a calibrated probability for every option in a single…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,…
DateApr 17, 2025ListedOct 8, 2026ListedOct 8, 2026Listed
Listed rateSee provider quotes$0.04 in / $0.00 out/ 1M tokensDeepInfra · all routes ↗See provider quotes
Provider endpoints0 endpoints →2 endpoints →0 endpoints →
Context window512131.1K8.2K
Max output—118K—
Parameters———
Open weightsNot reportedSupportedNot reported

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