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Introducing Respan Router
NVIDIA

NVIDIA: Inference & Compute

Founded 1993|Santa Clara, California|10001+ people|Enterprise

What is NVIDIA?

Key features

Core capabilities this platform advertises.

  • H100 and B200 GPU clusters
  • DGX Cloud platform
  • CUDA ecosystem
  • NeMo framework for LLM training
  • Omniverse for 3D and simulation

Strengths and tradeoffs

What this tool does well, and the limitations to keep in mind.

Pros

  • Unmatched GPU performance for AI training and inference
  • Deep CUDA software ecosystem with broad framework support
  • Comprehensive AI platform from hardware to software to cloud
  • Massive developer community and extensive documentation
  • Industry-leading enterprise support and regular updates

Cons

  • Extremely high cost for hardware and cloud services
  • Strong vendor lock-in through CUDA ecosystem
  • Limited flexibility for non-NVIDIA hardware configurations
  • Complex licensing and pricing structure

Plans & pricing

What's included in each plan, and how the tiers compare.

NVIDIA AI Enterprise

Contact sales

Contact sales for a quote

  • GPU-optimized AI frameworks
  • NVIDIA NIM microservices
  • Pre-trained models and tools
  • Enterprise support

DGX Cloud

From $36,999/month

Monthly

  • 8x H100 or A100 GPUs per instance
  • 640GB GPU memory
  • Multi-node training support

Project DIGITS

$3,000

 

  • Compact local AI system
  • Prototyping before cloud scale
View official pricing page

Common use cases

Enterprises and research labs that need the highest-performance GPU infrastructure

  • Large-scale model training
  • High-performance inference serving
  • AI research and development
  • Autonomous vehicle and robotics simulation
  • Enterprise AI infrastructure

Using NVIDIA with Respan

Respan provides observability and cost tracking for AI workloads running on NVIDIA hardware. Teams using NVIDIA GPUs for inference can route API calls through Respan to monitor latency, throughput, and cost across GPU-accelerated endpoints.

  • Track inference costs across NVIDIA GPU deployments
  • Monitor latency and throughput for TensorRT-optimized models
  • Compare performance across different GPU configurations
  • Optimize model routing between GPU and CPU endpoints

Run NVIDIA in production with Respan

10KFree traces/mo
1,000+Models
5 minSetup

Respan lets you trace LLM and agent calls across any model or framework, A/B test prompts on production traffic, and route requests across 1,000+ models through one gateway.

Try Respan free

Best NVIDIA alternatives & competitors

Top companies in Inference & Compute you can use instead of NVIDIA.

View all NVIDIA alternatives

NVIDIA models and API status

Live API status, the current flagship model and how NVIDIA's models compare, from the Respan model hub.

Compare NVIDIA

Side-by-side comparisons with other tools in this category.

Best integrations for NVIDIA

Companies from adjacent layers in the AI stack that work well with NVIDIA.

Last verified: February 28, 2026