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LLM

Phi-4 on a dedicated GPU for your team

Phi-4 is a strong fit for smaller dedicated enterprise deployments where teams want a compact model footprint without leaving shared hosted services in the loop.

Inputs

Prompts, internal app context, private business workflows

Outputs

Compact open LLM responses on dedicated infrastructure

Phi-4 sample output

Why teams deploy Phi-4

Teams choose a dedicated GPU for Phi-4 when they need full control over sensitive prompts, proprietary assets, or custom runtime configurations that shared endpoints can't provide.

compact private LLM hosting
cost-aware enterprise assistants
smaller inference footprints

Deployment details

Modality
LLM
Deployment
Dedicated compact LLM runtime on enterprise GPU
Starting at
$1999/month

Supported capabilities

Chat
Private inference
Dedicated runtime control
Enterprise deployment

Common use cases

internal helpers
automation backends
private app copilots

What you get with Enterprise

Dedicated GPU deployment with no shared queue contention
100% private workloads, prompts, and generated outputs
Code access for custom runtimes, adapters, and optimization
Bring-your-own S3 storage for assets, checkpoints, and outputs
Enterprise Deployment

Get a dedicated GPU for this model

Get Phi-4 running on a GPU dedicated to your team — with private data flow, full code access, and S3-backed storage for production workloads.

Full privacy for prompts, inputs, and outputs
Code access for custom runtimes and adapters
Your own S3 for checkpoints and generated assets
Dedicated GPU — no shared queue or throttling

Starting at

$1999/month

Scale to higher GPU tiers when you need more VRAM, throughput, or concurrency.

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