Build a Continuous Batching Server for High-Throughput LLM Inference Premium
Design a continuous batching server that dynamically admits and evicts sequences mid-generation, sustaining 8,000+ tokens per second across 128 concurrent requests on 4xA100 GPUs while keeping p99 time-to-first-token under 200ms.
Build a Disaggregated Prefill-Decode Inference Architecture Premium
Design a disaggregated prefill-decode inference architecture that separates compute-bound prefill from memory-bound decode across dedicated GPU pools, sustaining 12,000 decode tokens per second at sub-150ms TTFT while cutting GPU-hours 35% versus co-located serving.
Build a KV-Cache Sharing Layer for Multi-Turn LLM Conversations Premium
Design a distributed KV-cache sharing layer that eliminates redundant prefill computation for 50,000 concurrent multi-turn conversations, cutting time-to-first-token from 800ms to under 80ms with 70% GPU memory savings on prefix reuse.
Build a Multi-Modal Inference Server for Text, Image, and Audio Premium
A blueprint for a multi-modal inference server that fuses text, image, and audio inputs into one decoder across 250 requests per second, encoding up to 576 visual tokens and 500 audio tokens per call while holding p99 time-to-first-token under 900ms.
Build a Prompt Compression Pipeline to Reduce Token Costs Premium
A blueprint for compressing 8,000-token RAG contexts down to 2,000 tokens across 20,000 requests per minute, cutting billed input tokens by roughly 60% while keeping downstream answer accuracy within 2 points of the uncompressed baseline.
Build a Speculative Decoding Engine to Cut LLM Latency by 3x Premium
Design a speculative decoding engine that uses a small draft model to propose token sequences, enabling a 70B target model to verify multiple tokens per forward pass and achieve 3x throughput at p99 TTFT under 150ms.
Build a Token Budget Management System for LLM APIs Premium
Design a token budget management system that enforces per-tenant quotas at 10,000 requests per second, tracks real-time input and output token consumption, and rejects over-budget requests before inference to eliminate GPU waste and runaway API cost.
Build an LLM Cold Start Optimizer for Serverless Inference Premium
How to cut LLM serverless cold starts from 60-90 seconds to under 4 seconds using snapshotted model weights, warm pools, and predictive pre-provisioning, so a scale-to-zero GPU fleet absorbs bursty traffic without breaching a 2-second p99 time-to-first-token SLA.
Build an LLM Inference Gateway with Load Balancing Across Model Replicas Premium
Design an inference gateway that routes 5,000 requests per second across 64 GPU replicas, holds time-to-first-token under 400ms at p99, and picks replicas by KV cache pressure instead of round robin.