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DATASHEET // RUNPOD

RunPod

On-demand GPU pods for ComfyUI, vLLM, training.

PAID8–80 GB VRAMSelf-hosted server
Watermark-FreeHobbyist-OKAPI
Visit RunPodUPDATED 2026-05-16 · AFFILIATE LINK
runpod.io
RunPod — preview image

HARDWARE REQUIREMENTS //

Self-hosted server · Datacenter GPU (80 GB+)

8–80 GB VRAM
Min VRAM
8 GB
Rec. VRAM
80 GB
Min RAM
16 GB
Rec. RAM
128 GB
Disk
100 GB
GPU class
Datacenter GPU
Whatever the pod image bundlesNo Apple SiliconGPU RequiredQuant: FP16, BF16, FP8 +1

Card mix ranges from RTX 3090 to H200 / B200.

[ EDITORIAL PICK ]

Why we recommend RunPod

DERIVED FROM METADATA — NOT SPONSORED
  • Runs on 8 GB

    Comfortable on a mid-range consumer card — no need to remortgage for an A100.

  • Top-tier pick

    Power-user score 87/100 — consistently rated highly by people who use this every day, not just benchmark chasers.

  • Watermark-free

    Output is clean — you can ship it without scrubbing logos out.

  • 4 quant formats

    Supports FP16, BF16, FP8 and 1 more — you can dial VRAM use up or down to match your card.

[ EVIDENCE NOTE ]

Documentation-led datasheet

This page summarizes upstream documentation, release information, and editorially reviewed catalogue fields. It is not presented as a hands-on benchmark. Verify changing requirements at the official project; report stale data through our corrections channel.

AT-A-GLANCE SIGNALS //

DERIVED FROM THIS PAGE'S DATA
  • Install difficulty
    Standard

    A standard local install — download, install dependencies, point at your GPU.

  • Hardware comfort
    Mainstream

    Needs 8 GB minimum — RTX 3060 12GB or 4070 territory.

  • Ecosystem
    API-first

    Exposes a stable API — you can build on top of it programmatically.

  • Verification
    Recent

    Catalogue entry last updated 61 days ago — re-verification due soon.

[ MORE IN THIS NICHE ]

Other orchestration & apis tools we rate

Three picks across different tradeoffs — so you don't end up with three near-clones of RunPod.

What is RunPod?

Rent A100 / H100 / 4090 / L40S pods by the minute. Templates for ComfyUI, A1111, vLLM, Ollama. Useful when your workflow outgrows your local box.

Pros & cons

✓ PROS

  • Cheaper than the big clouds
  • Per-minute billing
  • Ready-made templates

– CONS

  • Spot pods can be reclaimed
  • You manage your own storage
  • Network egress costs

What's actually free?

Pay-as-you-go. No free tier. Community-cloud pricing starts around $0.20/hr for older cards.

Watermark-Free

Alternatives

Vast.ai

GPU marketplace — rent consumer cards at half the hyperscaler price.

PAIDCLOUD · NO GPU

Modal

Serverless Python for GPU workloads.

FREEMIUM16–80 GB VRAM
VRAM fit16–80 GB