LLM
DeepSeek V3
DeepSeek V3 is a strong dedicated enterprise target when teams want a cost-aware open LLM stack for private production inference.
Chat completionsPrivate prompt flow
LLM
Deploy DeepSeek R1 on dedicated infrastructure
DeepSeek R1 is one of the clearest enterprise deployment wins in the open LLM landscape because teams want its reasoning ability without exposing prompts or internal context to third-party shared providers.
Dedicated GPU
Private workloads
Production ready
Why teams deploy DeepSeek R1
Teams choose dedicated infrastructure for DeepSeek R1 when they need complete control over performance, security, runtime configuration, and production-scale reliability.
private reasoning workloads
internal copilots
secure enterprise chat systems
Modality
LLM
Deployment
Dedicated LLM runtime on enterprise GPU infrastructure
Inputs
Chat prompts, reasoning tasks, internal documents, private system instructions
Outputs
Reasoning-heavy chat and completion responses
Production showcase
Showcase
Production-quality outputs generated with DeepSeek R1 running on dedicated GPU infrastructure.
LLM
DeepSeek R1 sample output
Supported capabilities
Chat completions
Private prompt handling
Runtime control
Enterprise storage integration
Common use cases
internal knowledge assistants
reasoning APIs
private enterprise 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 DeepSeek R1 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
$249/month
Scale to higher GPU tiers when you need more VRAM, throughput, or concurrency.
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