Parasail Blog
Product updates, engineering deep dives, and thought leadership from the Parasail team.
Prefill vs Decode in LLM Inference
Understand how prefill and decode shape time to first token, streaming performance, KV-cache pressure, and LLM serving decisions.
GuidesParasail to Combine NVIDIA AI Infrastructure with d-Matrix Accelerators to Achieve 10x Faster Token Generation
Parasail to deliver faster, more cost-efficient tokens by pairing NVIDIA Hopper and Blackwell GPUs with d-Matrix Corsair accelerators
ProductBeyond the frontier: How to build a defensible AI inference infrastructure
Closed model dependency is becoming structural liability. Here's the framework for building a reliable AI inference architecture.
ProductFaster autoscaling for vLLM: Restoring from snapshots instead of starting cold
Cold-start latency is one of the biggest bottlenecks when scaling inference. Parasail's model snapshotting saves and restores CPU and GPU process state to bring vLLM replicas online 3-5x faster than rebuilding from scratch.
EngineeringMost inference commits are broken. Here's how we fixed ours.
Most inference commits lock you to hardware you'll outgrow and a model you'll want to swap. We structured Parasail's commit around dollars of inference, not a SKU, so it flexes as your usage and the frontier change.
ProductThe idle GPU tax: What it is, why it’s getting worse, and how you can fix it
Learn what the idle GPU tax is, what it costs, and how usage-based billing on dedicated endpoints helps you avoid it altogether.
Engineering