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· 8 min read

Stateful vs stateless LLMs: why keeping context on the GPU changes the game.

How storing context in GPU memory improves performance and efficiency in LLM-driven architectures compared to stateless setups. The model stays stateless — your runtime doesn't have to.

Introduction

Limits of stateless

What stateful actually means

Keeping the KV cache resident on the GPU between turns. The model itself is unchanged and remains stateless; the runtime around it simply stops throwing away work it has already done.

Conclusion

Statefulness is a property of the runtime, not the model. It is also the property that decides whether agent workloads are economically viable at scale.

Run frontier models under your own rules.

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