Why it matters

Serving costs scale with users. Optimization directly hits bottom line.

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The architecture

Batching: process multiple requests together. GEMM efficient for batches.

Quantization: INT8, INT4 reduce memory + speed up.

Serving cost leversBatchingthroughputQuantizationsmaller + fasterModel choiceSLM for simpleModel routing: cheap SLM handles most; expensive LLM for hard queries only
Cost optimization.
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How it works end to end

Model routing: classifier decides which model. Cheap for simple, expensive for hard.

Prefix caching: shared prompts reuse KV cache.

Spot instances: 60-90% cheaper for tolerant workloads.

Scale to zero: idle serving off-hours.