Why Nirvana is the best place to run your AI agents

Faster storage, smaller bills, and more billable work out of the same agents.

TL;DR

• Nirvana is the best place to run AI agents because we purpose built the storage. High-performance ABS is the MOAT: it is what makes reads and writes faster, and what makes the sandbox genuinely persistent.
• Nirvana cloud finished LangChain agent workloads ahead of every AWS setup tested, across all 18 runs. On the write path the lead grows with load: 24 to 28% at 100K checkpoints. That frees roughly 80 days of agent work a year on write-heavy work.
• The workspace lives on a networked ABS volume, so it was never part of the machine. Benchmark against GKE and E2B shows all 5,501 committed checkpoints recovered on a brand-new pod after an ungraceful kill. Anyone can add a snapshot feature. Building high performance storage takes years.
• ~$0.0040 per million durable checkpoints against ~$0.024 on GKE, at GKE's own compute rate. Idle compute is released in 1.46 s, so gaps over ~10 seconds become worth reclaiming instead of paying through.
• Fast storage, reclaimed idle, one bill. Run your agents on Nirvana.

Running agents starts with the compute layer decision: (assuming you already have a cloud) and which sandbox on top of it.

So most teams pick a sandbox vendor, the vendor rents from a hyperscaler, and the cloud underneath gets chosen for them, along with the limitations of a general-purpose cloud.

Nirvana owns the whole path: the hardware, the storage, the networking, the Kubernetes, and a sandbox purpose-built for demanding workloads.

Here are three reasons why Nirvana is the best place to run your AI agents:

1. Faster reads and writes, which means more work out of the same fleet

We ran the open-source LangChain agent benchmark against four AWS storage configurations across 18 runs, 9 write and 9 mixed read/write, with identical durability settings on every platform and every Postgres commit waiting on WAL fsync.

Nirvana finished ahead on end-to-end duration in all 18. The lead grows with load: ~10% at moderate load, 24 to 28% at 100K checkpoints. At 100K checkpoints that is 75 minutes of wall clock against 105 on the best AWS configuration. Run write-heavy work all year and the same fleet frees roughly 80 days of capacity.

That is 80 extra days of output from machines you can bill your clients for. More tasks completed, more API calls served, more trades cleared, more customers per cluster.

2. The sandbox is persistent, and the storage under is our MOAT

Someone said ephemeral sandboxes are dead. We agree. An agent that cannot survive losing its machine is not an agent you can trust with hours of work.

Nirvana Agent Sandboxes mount their workspace on a networked ABS volume, so it was never part of the machine to begin with. When the machine dies, the agent recovers with a new one and goes back to work in about 10s (vs GKE 35s). In Quirq's benchmark, all 5,501 committed checkpoints came back on a brand-new pod after an ungraceful kill. E2B lost them all.

Plenty of platforms will snapshot something for you with their RAM-backed sandboxes. Almost nobody built the storage. Accelerated Block Storage is ours and it's purpose built, which is why every volume gets 20,000 baseline IOPS with no performance tier to buy, and fsync returns in 1.65 ms after a real flush. A vendor renting from a hyperscaler inherits that hyperscaler's disk, and its ceiling with it.

Anyone can add a snapshot feature. Building high-performance storage takes years.

3. Both sides of the bill shrink, on both layers

Nirvana gives you the cloud and the sandbox your AI agents run on. Here is the ballpark.

On the cloud: ~$229 a month against ~$3,724 for the io2 configuration ABS beat, on the same 4 vCPU, 16 GB, 256 GB shape. That is roughly 16× on high-IOPS storage.

On the sandbox: ~$0.0040 per million durable checkpoints against ~$0.024 on GKE, priced at GKE's own compute rate for both, so the gap is throughput and not pricing. Compute time only, with storage and platform fees excluded.

And idle compute is released in 1.46 s, so gaps longer than about 10 seconds become worth reclaiming instead of paying through. In Quirq's test, none of the committed checkpoints had to be recreated.

So you save in four places: cheaper storage, less compute per unit of durable work, idle compute you can actually reclaim, and work you never have to run twice.

Where your agents should run

Fast storage. A workspace that outlives the machine. A smaller bill on both layers. All three come from the same thing: we built the storage, and we own every layer between it and your agent.

SOC 2 Type II, a dedicated cluster per customer, backed by Jump Trading and Crucible, with more than 50 customers live in production including Aori, Goldsky, Optimism and Monad, etc.

If you buy the persistent-agent thesis, and you are building agents that run for hours, checkpoint constantly and have to survive the machines underneath them, Nirvana is the best place to build and run AI agents.

Nirvana Agent Sandboxes are generally available. Two endpoints and an API key, with SDKs in Python, TypeScript, Go, Java, Kotlin and C#.

Read the docs → · Talk to us →

About Nirvana Labs

Nirvana Labs is a high-performance storage cloud purpose built for blockchain, AI and databases i.e. the most demanding, real-time, stateful workloads. Accelerated Block Storage (ABS) offers 20K baseline IOPS included, no over provisioning. Nirvana Kubernetes Service (NKS) with Karpenter auto-scaling, high clock-speed compute and private networking. Backed by Jump Trading, Crucible, etc with 50+ customers live in production today.

Learn more at Nirvana Labs

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