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Latest articles

Parasail 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

Beyond 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.

Most 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.

Parasail and Neuralwatt: More Inference from Every Watt

Neuralwatt's energy intelligence is now running in Parasail's fleet, routing compute to the most efficient GPUs and pulling more inference out of every watt.

How to choose the right managed inference architecture: Serverless, dedicated, dedicated serverless, or batch

Use this decision framework to choose the right managed inference mode based on latency requirements, GPU breakeven utilization, and whether your workload needs a dedicated endpoint.

Serverless vs. Dedicated Inference: Why We Built Dedicated Serverless

With dedicated serverless you get dedicated hardware on per-token pricing, no idle-hour charges or long-term GPU commitment.

Parasail and Wafer AI: Faster models, lower costs

Parasail and Wafer AI are partnering to make frontier AI cheaper and more accessible.

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From the team Parasail blog

Latest articles

How Parasail built one AI agent for inference operations

Building sub-second LLM inference for global AI traffic

Prefill vs. decode in LLM inference

Designing multi-region LLM deployments with gateway architecture

Parasail vs. DeepInfra: Cost, latency, model selection, and engineering support

Guide to optimize batching and throughput for offline LLM inference in 2026

Parasail to Combine NVIDIA AI Infrastructure with d-Matrix Accelerators to Achieve 10x Faster Token Generation

Beyond the frontier: How to build a defensible AI inference infrastructure

Faster autoscaling for vLLM: Restoring from snapshots instead of starting cold

Most inference commits are broken. Here's how we fixed ours.

The idle GPU tax: What it is, why it’s getting worse, and how you can fix it

Parasail and Neuralwatt: More Inference from Every Watt

How to choose the right managed inference architecture: Serverless, dedicated, dedicated serverless, or batch

Serverless vs. Dedicated Inference: Why We Built Dedicated Serverless

Parasail and Wafer AI: Faster models, lower costs

Making an EAGLE fly: How We Got 2.6x Faster LLM Inference (Without Cheating)

Making Cold Start Latencies go Brrrr: A Multi-pronged Approach (Part 1)

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