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InferenceRunpod

Runpod

GPU cloud for AI — on-demand instances and serverless inference.

Category
Inference
Pricing
PAID
Hosting
Cloud
Platforms
WebAPICLI
Models
Model-agnostic
Verified
Jun 8, 2026

Runpod is an AI developer cloud for renting GPUs on demand or running auto-scaling serverless inference endpoints. Serverless workers bill by the millisecond, scale to zero when idle, and advertise sub-200ms cold starts; on-demand Pods and multi-node Clusters cover training and long-running jobs. A Community Cloud tier offers cheaper, peer-sourced GPUs alongside the vendor-operated Secure Cloud.

Capabilities 4

What it actually does — grouped by capability family.

  • GPU compute (primary capability)
  • Model inference / serving (secondary capability)
  • Fine-tuning / training (secondary capability)
  • App / agent deployment (secondary capability)

Pros & cons

  • Serverless auto-scaling inference
  • Sub-200ms cold starts
  • Secure and Community Cloud GPU tiers
  • On-demand Pods and clusters too
  • Community Cloud less reliable/secure
  • GPU availability varies
  • Self-managed model serving

Tags

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    Serverless GPUs. Run training, inference, batch jobs from Python.

    Define cloud workloads in Python, deploy with one command — GPU access on demand, fast cold starts, fair-share pricing. The default 'I need to fine-tune a model from a Jupyter cell' platform.

    Python-decorator infra, no YAML/Dockerfiles
    SDK lock-in; migrating means rewriting
    • gpu
    • serverless
    • python
    • training
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    Replicate

    Replicate

    Run, fine-tune, and deploy thousands of open models via one API.

    A platform to run open-source models with one API call — image, video, audio, and language — plus fine-tuning and custom deploys with pay-per-second billing. No infra to manage.

    Image, video, audio, and language models
    Cold starts on less-popular models
    • model-hosting
    • fine-tuning
    • api
    • open-source
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    Baseten

    Baseten

    Inference cloud for serving any AI model in production.

    Production inference platform offering both pre-optimized Model APIs (Llama, DeepSeek, and more, billed per token) and dedicated GPU/CPU deployments for custom models, billed per minute with no charge for idle time. Custom models are packaged with its open-source Truss format and autoscale, including scale-to-zero. Aimed at low-latency, high-throughput serving.

    Prebuilt Model APIs for Llama, DeepSeek
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    • inference
    • model-serving
    • gpu
    • autoscaling
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    Lightning AI

    Lightning AI

    Persistent GPU cloud workspaces to build, train, and ship AI.

    A cloud platform built around AI Studios — collaborative, persistent GPU workspaces for coding, training models, running inference, and building agents and AI apps. Pay-as-you-go GPUs with a monthly free credit allowance, plus a Pro tier and bring-your-own-cloud for enterprise. Made by the team behind the open-source PyTorch Lightning framework.

    Pause/resume persistent GPU Studios
    Pay-as-you-go can add up
    • gpu-cloud
    • training
    • studios
    • infrastructure