Cut your LLM token
costs by 80-99%.
The complete toolkit for prompt caching, KV cache optimization, and intelligent token management — without sacrificing quality.
Daily API spend, before vs after
Anonymized production traffic. 30 days. Same workload.
Everything you need to run LLMs efficiently
Battle-tested optimization techniques from the frontier of production LLM serving.
Prompt Caching
Automatic cache-header injection across Anthropic, OpenAI, and self-hosted models. Zero code changes.
90% ↓ input tokensKV Cache Optimization
PagedAttention, RadixAttention, disaggregated prefill/decode. 3× throughput on the same hardware.
3× throughputSmart Model Routing
Route by complexity: Haiku for simple, Opus for hard. Learned from your traffic patterns.
60-95% ↓ costsCost Observability
Real-time token accounting, per-endpoint budgets, and anomaly detection out of the box.
Full visibilityPrompt Compression
LLMLingua-style compression that preserves semantics — safely shrink context before it hits the model.
2-6× smallerBatch API Integration
Automatically queue non-urgent work to batch endpoints. 50% off on eligible calls.
50% ↓ costEvery LLM workload that matters
Teams shipping with smart-token
Real numbers from teams running LLMs in production.
We were burning $40k/month on Opus for our support agent. smart-token dropped that to under $3k without touching a line of application code. The prompt caching alone paid for itself in a week.
Our RAG chatbot's TTFT went from 2.4s to 240ms after enabling KV cache reuse. Users noticed immediately. Support tickets about "slow responses" went to zero.
Model routing is what sold us. 80% of our traffic doesn't need Opus — smart-token figured that out from our patterns and routed automatically. Same quality, fraction of the price.
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