Managed inference

One endpoint, global inference delivery.

Managed inference on dedicated NVIDIA B300s. Custom models on bare-metal GPUs available today.

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Why PolarGrid

Built for inference,not retrofitted from the cloud.

  • Time to capacity

    PolarGrid
    Minutes
    Reserved GPU cluster
    Months
    Serverless inference API
    Minutes, on shared GPUs

  • Hardware

    PolarGrid
    Dedicated NVIDIA B300s, single tenant
    Reserved GPU cluster
    Dedicated
    Serverless inference API
    Shared

  • Your model and serving image

    PolarGrid
    Any checkpoint, on a built-in engine or your own image
    Reserved GPU cluster
    Yes, you run it
    Serverless inference API
    Supported models and runtimes only

  • Endpoint

    PolarGrid
    One endpoint: OpenAI-compatible or your image's own API
    Reserved GPU cluster
    You build it
    Serverless inference API
    The provider's API

  • Traffic spikes

    PolarGrid
    Burst capacity on the same endpoint
    Reserved GPU cluster
    Buy more nodes
    Serverless inference API
    Scales on shared capacity

  • Served from

    PolarGrid
    The best of many sites
    Reserved GPU cluster
    One region
    Serverless inference API
    A few regions

  • Site failure

    PolarGrid
    Traffic moves to the next nearest site
    Reserved GPU cluster
    Your failover plan
    Serverless inference API
    Handled by the provider

  • Releases

    PolarGrid
    Evals, canary and automatic rollback
    Reserved GPU cluster
    You build it
    Serverless inference API
    Varies

  • Monitoring

    PolarGrid
    Metrics by site, public status page
    Reserved GPU cluster
    You build it
    Serverless inference API
    Provider dashboards
How it works

From checkpoint to production,without the detour.

Get a deployment plan
Checkpoint01 / 04
s3://acme-models/llama-ft/S3-compatible storage
shard 1/49.9 GB
shard 2/49.9 GB
shard 3/49.9 GB
shard 4/41.2 GB
config.json · tokenizer.json
Checkpoint found · 31.0 GBReady to deploy
Where it runs

Served from the sitenearest every user.

Fast everywhere

Each request is served from the site nearest the user, so time to first token stays low in every region, not only near one data center.

Elastic capacity

When traffic surges in one region, nearby sites take the overflow. A single site would queue it.

Resilient by design

If a site goes down, its traffic moves to the next nearest site and the endpoint stays up.

Sovereign data

Models can be pinned to specific regions for data residency.

Live sitePlanned siteRequestMap of PolarGrid sites worldwide. Live sites: Seattle, San Jose, Los Angeles, Dallas, Miami, Ashburn, New York and Montreal. Planned sites in North America: Calgary, Portland, Phoenix, Denver, San Antonio, Chicago, Atlanta, Tampa and Mexico City. Planned sites elsewhere: São Paulo, Santiago, Bogotá, London, Dublin, Paris, Amsterdam, Frankfurt, Stockholm, Madrid, Milan, Warsaw, Dubai, Johannesburg, Lagos, Nairobi, Mumbai, Bangalore, Singapore, Jakarta, Tokyo, Osaka, Seoul, Sydney, Melbourne and Auckland. Requests travel from North American cities to the nearest live site.
FAQ

Frequently askedquestions.

Get a deployment plan and quote

Share your model and expected traffic, and get a deployment plan and a quote back.