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Compare GPU and LLM inference API pricing between Runpod and Standard Compute. Find the best rates for AI training, inference, and ML workloads.
Provider 1
Provider 2
| GPU Model ↑ | Runpod Price | Standard Compute Price | Price Diff ↕ | Sources |
|---|---|---|---|---|
A100 PCIE 40GB VRAM • Runpod | Not Available | — | ||
A100 PCIE 40GB VRAM • | ||||
A100 SXM 80GB VRAM • Runpod | Not Available | — | ||
A100 SXM 80GB VRAM • | ||||
A40 48GB VRAM • Runpod | Not Available | — | ||
A40 48GB VRAM • | ||||
B200 180GB VRAM • Runpod | Not Available | — | ||
B200 180GB VRAM • | ||||
H100 NVL 94GB VRAM • Runpod | Not Available | — | ||
H100 NVL 94GB VRAM • | ||||
H100 PCIe 80GB VRAM • Runpod | Not Available | — | ||
H100 PCIe 80GB VRAM • | ||||
H100 SXM 80GB VRAM • Runpod | Not Available | — | ||
H100 SXM 80GB VRAM • | ||||
H200 141GB VRAM • Runpod | Not Available | — | ||
H200 141GB VRAM • | ||||
HGX B300 288GB VRAM • Runpod | Not Available | — | ||
HGX B300 288GB VRAM • | ||||
L4 24GB VRAM • Runpod | Not Available | — | ||
L4 24GB VRAM • | ||||
L40 40GB VRAM • Runpod | Not Available | — | ||
L40 40GB VRAM • | ||||
L40S 48GB VRAM • Runpod | Not Available | — | ||
L40S 48GB VRAM • | ||||
MI300X 192GB VRAM • Runpod | Not Available | — | ||
MI300X 192GB VRAM • | ||||
RTX 3070 8GB VRAM • Runpod | Not Available | — | ||
RTX 3070 8GB VRAM • | ||||
RTX 3080 10GB VRAM • Runpod | Not Available | — | ||
RTX 3080 10GB VRAM • | ||||
A100 PCIE 40GB VRAM • Runpod | Not Available | — | ||
A100 PCIE 40GB VRAM • | ||||
A100 SXM 80GB VRAM • Runpod | Not Available | — | ||
A100 SXM 80GB VRAM • | ||||
A40 48GB VRAM • Runpod | Not Available | — | ||
A40 48GB VRAM • | ||||
B200 180GB VRAM • Runpod | Not Available | — | ||
B200 180GB VRAM • | ||||
H100 NVL 94GB VRAM • Runpod | Not Available | — | ||
H100 NVL 94GB VRAM • | ||||
H100 PCIe 80GB VRAM • Runpod | Not Available | — | ||
H100 PCIe 80GB VRAM • | ||||
H100 SXM 80GB VRAM • Runpod | Not Available | — | ||
H100 SXM 80GB VRAM • | ||||
H200 141GB VRAM • Runpod | Not Available | — | ||
H200 141GB VRAM • | ||||
HGX B300 288GB VRAM • Runpod | Not Available | — | ||
HGX B300 288GB VRAM • | ||||
L4 24GB VRAM • Runpod | Not Available | — | ||
L4 24GB VRAM • | ||||
L40 40GB VRAM • Runpod | Not Available | — | ||
L40 40GB VRAM • | ||||
L40S 48GB VRAM • Runpod | Not Available | — | ||
L40S 48GB VRAM • | ||||
MI300X 192GB VRAM • Runpod | Not Available | — | ||
MI300X 192GB VRAM • | ||||
RTX 3070 8GB VRAM • Runpod | Not Available | — | ||
RTX 3070 8GB VRAM • | ||||
RTX 3080 10GB VRAM • Runpod | Not Available | — | ||
RTX 3080 10GB VRAM • | ||||
| Model ↑ | Runpod | Standard Compute | Input Diff ↕ |
|---|---|---|---|
Kimi | $0.950 in $4.00 out | Not available | — |
Kimi | $0.950 in $4.00 out | Not available | — |
Moonshot | $3.00 in $15.00 out | Not available | — |
Alibaba | $10.00 in $10.00 out | Not available | — |
Explore how these providers compare to other popular GPU cloud services
Compare Runpod with another leading provider
Compare Runpod with another leading provider
Compare Runpod with another leading provider
Compare Runpod with another leading provider
Compare Runpod with another leading provider
Compare Runpod with another leading provider
Access to a wide range of GPU types with enterprise-grade security
Only pay for the compute time you actually use
Programmatically manage your GPU instances via REST API
Pods typically ready in 20-30 s
SSH & VS Code tunnels built-in
Automatic migration on pre-empt
Routes requests to the most efficient models based on current prices and usage.
Automatically selects the fastest and cheapest provider for requests.
Users can monitor and manage their monthly compute budget live.
Supports various AI models including frontier models from major labs.
Ensures user data is not stored or used for training models.
No session, hourly or weekly caps — a single monthly compute budget that can be spent at any pace until it runs out.
On‑demand single‑node GPU instances in Secure Cloud (data‑center hosted) or lower‑cost Community Cloud, with flexible templates and storage.
Pay‑per‑second endpoints with automatic scaling for production AI/ML applications.
Fully managed multi‑node GPU clusters with high‑speed networking between nodes.
Pods hosted in vetted data centers; higher reliability tier
Pods on vetted community hosts at lower rates than Secure Cloud
Interruptible capacity at reduced prices
Pay-per-second billing for endpoint execution time, with automatic scaling and no charge when idle
Per-hour or per-second billing for multi-node GPU clusters with no commitment, scaling up to 64 GPUs
Discounted rates for 1, 3, 6, or 12+ month commitments on dedicated clusters with guaranteed availability and SLA-backed uptime; quoted by sales
Usage-based billing for pre-deployed model APIs, charged per request, per token, or per 1000 characters depending on the model
Subscription tiers, each including a fixed monthly compute budget, with no per-token fees. See the pricing page for current tiers.
Per-member plans under one company account; members can be assigned different tiers.
Custom volume pricing with an uptime SLA, custom terms and consolidated invoicing. Quoted by the provider.
Eligible new accounts can request a small, finite trial compute allowance with a real API key and no card required, activated from the dashboard. It does not renew.
Sign up for Runpod using your email or GitHub account
Add a credit card or cryptocurrency payment method
Select a template and GPU type to launch your first instance
Go to the Standard Compute homepage.
Create an account to obtain your API key.
Choose a subscription that fits your needs.
Follow integration guides to connect your AI models.
Track your compute budget and usage through the dashboard.
31 global regions worldwide
Documentation site, support request form, public status page, and a community Discord
Inference regions in the EU and US on every plan; region activation is checked in the dashboard.
Standard support on all individual plans; the Scale tier adds priority support with a direct engineer line and the Business tier includes an uptime SLA. Integration and setup guides are published on the website.