GPU CLOUD COMPARISON

RunPod vs Vast.ai vs Runcrate.

Pricing, features, and developer experience compared side by side. See how Runcrate stacks up on GPU pricing, inference API, and ease of use.

200+
Models
20+
GPU types
$1.54/hr
H100 price

COMPARISON

Runcrate vs RunPod / Vast.ai.

H100 80GB price
Runcrate: $1.54/hr
RunPod / Vast.ai: $1.99/hr / ~$1.65/hr
A100 80GB price
Runcrate: $1.06/hr
RunPod / Vast.ai: $1.49/hr / ~$1.10/hr
RTX 4090 price
Runcrate: $0.52/hr
RunPod / Vast.ai: $0.44/hr / ~$0.34/hr
Inference API
Runcrate: 200+ models, zero setup
RunPod / Vast.ai: DIY with pods/containers
Egress fees
Runcrate: $0
RunPod / Vast.ai: Storage fees / ~$2.50/100GB
Spot interruption warning
Runcrate: N/A (on-demand)
RunPod / Vast.ai: 5 seconds / varies by host
Multi-modal API
Runcrate: Chat, image, video, TTS, STT
RunPod / Vast.ai: Raw GPU only

GPU PRICING

GPU pricing comparison.

NVIDIA H200 141GB
RuncrateFrom $2.41/hr
141GB HBM3e, latest gen
NVIDIA H100 80GB
RuncrateFrom $1.54/hr
80GB HBM3, NVLink
NVIDIA B200 192GB
RuncrateFrom $3.20/hr
192GB HBM3e, Blackwell
NVIDIA A100 80GB
RuncrateFrom $1.06/hr
80GB HBM2e, proven workhorse
NVIDIA L40S 48GB
RuncrateFrom $0.80/hr
48GB GDDR6X, inference optimized
NVIDIA RTX 4090 24GB
RuncrateFrom $0.52/hr
24GB GDDR6X, best $/perf

WHY SWITCH

Why teams switch to Runcrate.

API + GPU Instances

RunPod and Vast.ai give you raw GPU pods. Runcrate gives you that AND a 200+ model inference API. Use the API for production inference, GPU instances for training and custom workloads.

H100 at $1.54/hr

Competitive with RunPod's on-demand pricing ($1.99/hr) and Vast.ai marketplace rates. No bidding, no spot interruptions, no surprise egress fees.

60-Second Deploy

Select your GPU, pick a template (PyTorch, Jupyter, VS Code), deploy. SSH, browser IDE, and port forwarding included. Per-minute billing from first boot.

Zero Egress Fees

Download your models, datasets, and results without bandwidth charges. RunPod charges for network storage. Vast.ai charges ~$2.50/100GB. Runcrate: $0.

GET STARTED

Try it now.

import Runcrate from "@runcrate/sdk";

const rc = new Runcrate({ apiKey: "rc_live_YOUR_API_KEY" });

// Deploy an H100 GPU instance in 60 seconds
const instance = await rc.instances.create({
  name: "my-gpu-instance",
  gpuType: "H100",
  gpuCount: 1,
  sshKeyId: "sk_...",
  template: "pytorch-cuda",
  storage: 100,
});

// Check availability and pricing
const gpuTypes = await rc.instances.listTypes({ gpuType: "A100" });
console.log(gpuTypes); // [{ hourlyRate: 1.06, region: "us-east", ... }]

// Get instance IP for SSH
const status = await rc.instances.getStatus(instance.id);
console.log("ssh root@" + status.ip);

// Or skip GPUs entirely — use the inference API
const response = await rc.chat.completions.create({
  model: "deepseek-ai/DeepSeek-V3",
  messages: [{ role: "user", content: "Hello!" }],
});

// Manage storage
const volumes = await rc.storage.list();
console.log(volumes);

// Terminate when done — per-minute billing stops immediately
await rc.instances.terminate(instance.id);

FAQ

Common questions.

Try Runcrate for GPU inference.