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InferenceModal Labs

Modal

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

Category
Inference
Pricing
FREEMIUM
Hosting
Cloud
Platforms
APICLI
Models
Model-agnostic
Verified
Jun 1, 2026

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.

Capabilities 5

What it actually does — grouped by capability family.

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

Pros & cons

  • Python-decorator infra, no YAML/Dockerfiles
  • Scale-to-zero, pay only when running
  • Scales to hundreds of GPUs
  • Free monthly starter credits
  • SDK lock-in; migrating means rewriting
  • No managed vLLM/TensorRT setup
  • Costs climb under heavy usage
  • Billing hard to predict

Tags

View all Inference
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    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
    Dedicated GPU rates run pricier than Modal
    • inference
    • model-serving
    • gpu
    • autoscaling
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    Runpod

    Runpod

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

    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.

    Serverless auto-scaling inference
    Community Cloud less reliable/secure
    • gpu-cloud
    • serverless
    • inference
    • deployment
    • +1
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    Replicate

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    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
  • View Beam details
    InfraFREEMIUM

    Beam

    Beam

    On-demand serverless GPU compute for AI, from Python.

    A serverless cloud for deploying AI inference endpoints, agent sandboxes, task queues, and containerized GPU workloads with a few lines of Python. It handles fast cold starts, autoscaling, and Docker-in-Docker execution across multiple cloud backends, and supports bring-your-own-compute. The Developer tier is free with recurring monthly credit; paid tiers add team features and scale, billed pay-as-you-go by GPU usage.

    Define GPU workloads in pure Python
    Smaller ecosystem than hyperscalers
    • gpu
    • serverless
    • python
    • inference
    • +1