# What does Shared KV Cache do in Gemma 4?

Source: https://zilliz.com/ai-faq/what-does-shared-kv-cache-do-in-gemma-4
Author: zilliz

Shared KV Cache reduces memory consumption by reusing key-value states across layers instead of maintaining separate caches per layer.

In transformer architectures, attention mechanisms require storing key-value (KV) pairs for each token at each layer. Traditional approaches maintain separate KV caches for every layer, consuming substantial memory proportional to model depth. With 30+ decoder layers, memory overhead becomes significant.

Shared KV Cache reuses these key-value states across layers. Instead of storing independent KV pairs for each layer, the architecture shares a common KV state that all layers reference. This dramatically reduces memory consumption without degrading output quality.

Memory efficiency translates directly to practical benefits:
- **Higher throughput**: Process more documents simultaneously
- **Longer sequences**: Handle longer documents or image sequences
- **Faster inference**: Less memory bandwidth consumed during generation
- **Cost optimization**: Process more embeddings per compute unit

For teams using Zilliz Cloud, reduced embedding generation costs mean faster time-to-index. You can generate and upload embeddings more quickly, keeping your Zilliz Cloud indexes updated with minimal latency. This is particularly valuable for real-time applications where document updates must be reflected in search results promptly.

Shared KV Cache demonstrates Google's focus on making Gemma 4 practical for production environments where resource constraints and cost are real operational concerns.

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