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Comparison of multilingual-e5-large-instruct, LiquidAI: LFM2.5-24B-A2B, embeddinggemma-2
3 modelsintfloatmultilingual-e5-large-instructRemove ×liquidLiquidAI: LFM2.5-24B-A2BRemove ×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:”…24B total, 2.45B active parameters; always reasons before answering, with GGUF and MLX releases for local deployment.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 13, 2026ListedOct 8, 2026Listed
Listed rateSee provider quotes$0.05 in / $0.70 out/ 1M tokensLiquid · via OpenRouter · all routes ↗liquid/fp8 · quantization=fp8See provider quotes
Provider endpoints0 endpoints →2 endpoints →0 endpoints →
Context window512128K8.2K
Max output—8.2K—
Parameters—24B—
Tool callingNot reportedSupportedNot reported
Structured outputNot reportedSupportedNot reported
ReasoningNot reportedSupportedNot reported
Prompt cachingNot reportedSupportedNot reported
Open weightsNot reportedSupportedNot reported

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