Gemma 4 offers four variants: E2B and E4B (efficient), 26B A4B (Mixture of Experts), and 31B Dense, each balancing size, speed, and quality.
The E-series variants (E2B and E4B) are designed for efficiency, targeting deployment scenarios where model size and inference latency matter. These are suitable for edge devices, real-time applications, and resource-constrained environments. The ‘E’ designation emphasizes their optimization for efficiency rather than raw capability.
The 26B A4B variant uses Mixture of Experts (MoE) architecture, activating only a subset of model parameters per token. This design provides larger effective capacity without proportional increases in computation cost. MoE models often deliver strong quality-to-speed ratios, making them valuable for balanced production systems.
The 31B Dense variant represents the full-scale model with all parameters active for every token. Dense models typically produce higher quality outputs than their MoE equivalents, justifying the increased computational cost for applications where quality is paramount.
For Milvus integrations, choose based on your inference budget and quality requirements. E-series variants allow lighter embedding generation pipelines that feed frequent updates into Milvus. The 26B A4B balances throughput and quality for sustained production embedding generation. The 31B Dense suits scenarios where embedding quality directly impacts downstream search relevance.
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