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RunPod GPU prices

Track RunPod GPU prices for H100 SXM, H200, MI300X, and A100 SXM4, compare current median rates, and see how this provider moves versus the broader cloud market.

Plan with RunPod Browse GPU prices Open RunPod
Lowest Median
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GPUs Available
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models tracked
Median Range
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across recent GPUs
Last Updated
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Search guide

RunPod cloud GPU pricing overview

RunPod currently appears in our dataset with pricing for 17 tracked GPU models, including H100 SXM, H200, MI300X, and A100 SXM4.

Use this page when you want a provider-first view: start with the current table to compare median rates today, then use the history chart to understand how the provider's market has moved over time.

Cheapest provider right now

Lowest tracked RunPod GPU median right now

The lowest tracked RunPod GPU median right now is V100 at $0.21/hr (community).

Methodology and freshness

How provider pricing is normalized

We normalize each tracked listing into per-GPU hourly pricing, keep the latest snapshot per pricing type, and let you compare the same provider across many GPU models without manually reconciling marketplace formats.

FAQ

RunPod GPU pricing FAQ

Does RunPod offer H100, A100, or H200 GPUs?

RunPod currently has tracked pricing for H100 SXM, H200, MI300X, and A100 SXM4.

What is the lowest tracked GPU median on RunPod right now?

The lowest tracked RunPod GPU median right now is V100 at $0.21/hr (community).

How fresh are the RunPod GPU prices on this page?

This page shows the latest stored snapshot for each RunPod GPU and pricing type. The freshest row currently visible is from Jul 31, 2026, and collectors run on a daily cadence.

How should I compare RunPod with other GPU providers?

Start with the current GPU table to compare median prices on this provider, then use the provider comparison links below to compare shared GPUs against hyperscalers and specialist GPU clouds.

Popular follow-up searches

Popular RunPod GPU price searches

These follow-up pages prioritize the GPU and provider combinations most likely to matter for buyers researching rental cost, availability, and alternatives.

RunPod H100 SXM price Compare RunPod's current H100 SXM rate against the rest of the tracked market. RunPod H200 price Compare RunPod's current H200 rate against the rest of the tracked market. RunPod MI300X price Compare RunPod's current MI300X rate against the rest of the tracked market. RunPod A100 SXM4 price Compare RunPod's current A100 SXM4 rate against the rest of the tracked market. Cheapest GPU for GLM-4.7-Flash Map the 3B-active GLM-4.7-Flash onto the current 32GB and 48GB GPU market. Best GPU for Kimi Linear 48B hosting See which 48GB-class GPU is the cheapest practical home for Kimi's long-context 3B-active model.
Coverage notes

How RunPod pricing is tracked

RunPod is high-value for vLLM and serverless-style buyers who care about practical deployment paths.

Source
RunPod GraphQL API Requires `RUNPOD_API_KEY`
Pricing models
on-demand, community, spot tracked where available
Best for
Open-weight inference, bursty GPU APIs, and buyers comparing specialist GPU cloud economics. buyer fit
Region support: Region metadata depends on the returned template/pod fields and is not uniformly present.
Limitations: Template availability and community or spot pricing can move quickly, so freshness matters.
Workload views

RunPod prices by workload

Jump from the full provider catalog into workload-specific slices for model serving, batch queues, fine-tuning, and training.

RunPod vLLM hosting prices OpenAI-compatible vLLM serving usually starts at 24GB GPUs and moves into 80GB+ rows for larger models, batching, and long prompts. RunPod batch inference prices Batch inference can use cheaper and less stable pricing modes when queues are flexible and retries are acceptable. RunPod fine-tuning prices Fine-tuning usually starts in 80GB-class inventory once optimizer state, activations, checkpointing, and sequence length are considered. RunPod training prices Training budgets are dominated by 80GB+ accelerators, provider stability, and whether newer H100/H200/B200/MI300X rows justify their premium over A100.

Current RunPod GPU prices

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GPU VRAM Type Min Median Max Offers Last Updated
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Compare RunPod against other providers

RunPod vs Vast.ai RunPod vs AWS RunPod vs Azure RunPod vs GCP RunPod vs Lambda RunPod vs Oracle
Agent-assisted setup

Hand this runbook to Claude Code or Codex

Open a terminal in the repository where you want the deployment files, start claude or codex, then paste this prompt. It asks the agent to verify sources and stop before it creates billable infrastructure.

Claude Code quickstart ↗ Codex docs ↗
Deployment prompt 
Use the infrastructure or model context on this page to create a reproducible open-model deployment. Use this guide as the starting context: https://www.getflops.ai/provider/runpod. Read the linked model card and provider documentation before choosing hardware or runtime settings. Open every linked primary source and flag any mismatch instead of guessing. Create a deployment folder containing README.md, .env.example with no secrets, a pinned start script or infrastructure manifest, and smoke-test.sh. Make the endpoint OpenAI-compatible where the runtime supports it. Run local/static validation, estimate the billable resources, and stop before provisioning paid infrastructure until I approve.
Guardrails included No secrets in files · verify primary docs · approval before spend