RunPod pricing

About

RunPod is a Las Vegas-based GPU cloud company founded in May 2022 by Zhen Lu and Pardeep Singh, both with backgrounds in cryptocurrency-mining infrastructure operations. The pivot from crypto mining to AI inference was a 2022–2023 industry-wide transition; RunPod’s founders parlayed existing GPU hardware relationships into a managed cloud product. The company runs a dual-cloud architecture: Secure Cloud uses RunPod-operated enterprise-grade data centers with redundant power, networking, and SLA backing; Community Cloud uses partner-operated data centers at lower cost with reduced reliability guarantees. Customers pick per-workload based on whether they want production reliability or rock-bottom cost.

By 2026 RunPod serves a mix of hobbyist developers running Stable Diffusion on RTX 4090s ($0.69/hour), academic researchers training models on A100 clusters, AI-native startups building production inference on H100 / H200, and mid-market enterprises running mixed Pods + Serverless workloads. The company reportedly closed a Series A in 2024 (specific size undisclosed) focused on scaling Secure Cloud capacity and Serverless reliability. The “up to 80% less than hyperscalers” marketing claim holds at the low end of the GPU ladder (RTX 4090, A40) but compresses to roughly 30–50% savings at H100 / B200 frontier rates.

RunPod competes with Modal, Replicate, Baseten (for AI inference), Together AI (for clusters), Lambda Labs, CoreWeave, and serverless platforms generally. Its differentiation is the explicit dual-cloud price-reliability split, the largest published GPU type range (RTX 4090 hobbyist GPU through frontier B200 in a single rate card), and aggressive low-end pricing that captures hobbyist and student workloads that competitors price out of reach.

Pricing summary : How RunPod’s dual-cloud + Serverless + tiered storage stack works

RunPod runs four deployment modes on a shared rate card. Pods are persistent per-hour GPU rentals — customers spin up a container, work on it for hours or days, and pay for the wall-clock time the Pod is running (RTX A5000 $0.27/hr through B300 $7.39/hr). Serverless endpoints are per-second-billed inference workers that scale to zero between requests. Clusters are instant multi-node GPU clusters (up to 64 GPUs, no commitment) with a small per-hour card (H200 SXM $4.31, A100 SXM $1.79) and larger SKUs sales-led; Reserved Clusters are entirely Contact-sales with 1–12mo+ commit terms. Public Endpoints add a pay-per-request API layer over pre-deployed models (e.g. $0.05/1000 chars for Whisper V3, $0.02/megapixel for FLUX.1, $1.20/request for SORA 2 Pro video). All compute modes share the same GPU types but differ in billing granularity (per-hour for Pods/Clusters, per-second for Serverless, per-request for Public Endpoints).

The dual-cloud split applies to Pods only: Secure Cloud runs on RunPod-operated enterprise data centers with SLA backing; Community Cloud runs on partner DCs at typically 20–40% lower cost with no SLA. Storage is split across five SKUs — Container Disk ($0.10/GB-month), Volume Disk ($0.10 running / $0.20 idle), Network Storage Standard ($0.07 under 1TB / $0.05 over 1TB), and Network Storage High-Performance ($0.14) — which finance teams must aggregate to forecast total storage spend. There is no published free tier; Enterprise commits unlock volume discounts and dedicated capacity.

This multi-SKU rate-card design gives customers granular control over price-reliability and persistence-vs-serverless trade-offs. The breadth of GPU types (RTX 4090 through B300 in one rate card) is also unusual — most AI infrastructure platforms commit to either workstation/consumer GPUs or data-center GPUs but not both.

What makes this different: Explicit Secure-vs-Community Cloud pricing makes the reliability trade-off legible — customers see that they’re trading SLA for cost rather than discovering the gap after deployment. This transparent reliability tiering is unusual in cloud infrastructure and reflects RunPod’s marketplace heritage rather than a hyperscaler-style “premium-by-default” architecture.

Pricing by product

Secure Cloud Pods (per-hour persistent)

The Secure Cloud ladder runs from RTX A5000 at $0.27/hr through B300 Blackwell-Ultra at $7.39/hr (288 GB HBM3e) — the newest top of the rate card, above B200 ($5.89/hr). RTX 4090 ($0.69/hr) remains the popular hobbyist anchor, but A5000, L4, A40, and RTX 3090 sit below it.

Serverless GPU workers (flex, per-hour equivalent)

Serverless bills per-second; rates below are the published flex per-hour equivalents. Active (always-on) workers are billed at lower per-hour rates.

Storage SKUs

Clusters (multi-node, per-hour)

Instant multi-GPU clusters scale up to 64 GPUs with no commitment, billed per-second (per-hour equivalents shown). Larger SKUs are sales-led.

Reserved Clusters (1mo / 3mo / 6mo / 12mo / 12mo+ commitments) are entirely Contact-sales across H200 SXM, A100 SXM, L40S, H100 SXM, and B200 — dedicated GPU clusters with guaranteed availability, custom configurations, SLA-backed uptime, and discounted rates for enterprises scaling to 10,000+ GPUs.

Public Endpoints (pre-deployed model API)

Instant API access to pre-deployed AI models, billed per request / per token / per character — no infrastructure setup. A sample of the live catalog:

Community Cloud (Pods only)

Sales motions across products: PLG / self-serve for Pods (both clouds), Serverless, Clusters (instant), Public Endpoints, and storage; sales-led for Reserved Clusters, Enterprise annual commits, and dedicated capacity reservations. Prices accessed 2026-07-14 from runpod.io/pricing and docs.runpod.io/pods/pricing.

Hidden costs : What RunPod customers actually pay beyond the per-hour rate

Archetype A: Hobbyist running Stable Diffusion on RTX 4090 Community Cloud

A hobbyist developer running Stable Diffusion daily for ~2 hours on RTX 4090 Community Cloud (estimated $0.40/hour vs $0.69 Secure):

For hobbyist workloads, Community Cloud delivers materially cheaper compute than any competitor — and the price-reliability trade-off is acceptable because hobbyist work tolerates occasional Pod restarts. This is the target persona RunPod captures that other platforms miss.

Archetype B: AI-native startup running production H100 inference on Secure Cloud

A growth-stage AI startup running sustained H100 inference (8 hours/day) on Secure Cloud with persistent volume for model weights:

H100 dedicated compute dominates the bill — and the $2.89/hour rate is among the lowest published H100 Secure Cloud rates in the market. Customers should expect to also model network storage carefully: the five-SKU storage structure creates forecasting complexity that simpler platforms (Modal’s free 1 TiB tier, Baseten’s unified storage) avoid.

Want to estimate your own RunPod bill? Use the RunPod pricing calculator to model Pod hours, Serverless worker hours, and the five storage SKUs separately.

Pricing evolution : RunPod’s pricing history from crypto-mining pivot to dual-cloud platform

Cadence

Tracked range: 2022 Q2–2026 Q3. Quarters not listed above were verified stable (0 price changes, 0 SKU additions).

Notable changes

• 2023-01-15 — Secure Cloud launched; established the dual-cloud architecture that defines RunPod’s positioning today.
• 2023-08-22 — Serverless GPU endpoints launched at $0.58–$8.64/hr equivalent; direct competition with Modal, Replicate, Baseten.
• 2024-04-09 — H100 PCIe at $2.89/hour Secure Cloud — among the lowest published H100 rates in managed inference.
• 2024-09-17 — Network Storage tiers launched ($0.07 <1TB, $0.05 >1TB, $0.14 high-performance) separating storage from Pod compute.
• 2025-11-04 — B200 Blackwell at $5.89/hour; first Blackwell-class GPU on the platform.
• 2026-02-12 — Volume Disk differential pricing ($0.10 running / $0.20 idle); 2× idle premium to discourage abandoned volumes.
• 2026-06-30 — B300 (288 GB HBM3e) added at $7.39/hr as the new top of the Secure Cloud ladder, ~25% above B200 ($5.89/hr); L40S moved up to $0.99/hr (from $0.86) and L40 dropped to $0.82/hr (from $0.99), an inversion that re-sorts the two 48 GB cards. The pricing page now presents four distinct compute modes side by side — Pods, Serverless, Clusters (instant + reserved), and a per-request Public Endpoints model API — signalling RunPod is widening from raw-GPU rental toward a packaged model-serving menu.
• 2026-07-06 — Serverless flex-worker reprice while Secure Cloud Pods held steady: H200 $5.58 → $5.93/hr and H100 $4.18 → $4.55/hr (top-of-ladder inference workers up ~6–9%), while RTX 6000 Pro dropped $4.00 → $3.49/hr (−13%) and the 48 GB L40/L40S/6000-Ada class fell $1.90 → $1.75/hr. Two new Serverless SKUs joined the ladder — B300 (280 GB) at $9.98/hr as the new top, and RTX PRO 4500 Blackwell (32 GB) at $1.15/hr. The moves converge Serverless flex rates toward the Secure Cloud per-hour card and extend Blackwell coverage on the serverless side.
• 2026-07-14 — Secure Cloud Pod cuts on two mid-ladder cards: H100 SXM (80 GB) $3.29 → $2.99/hr (−9.1%) and RTX Pro 6000 (96 GB) $2.09 → $1.99/hr (−4.8%). The H100 SXM cut tightens the H100 family band — the SXM variant now sits just $0.10 above H100 PCIe ($2.89/hr) and below H100 NVL ($3.19/hr) — while RTX Pro 6000 crosses under the psychological $2 line to sit between A100 SXM ($1.49/hr) and the H100 tier. Every other Pod, Serverless, Clusters, storage, and Public Endpoints rate held, so this is a targeted frontier-GPU cost-leadership trim as Blackwell-generation supply expands, not a broad reprice.

What’s unique : RunPod’s distinctive pricing mechanics

1. Explicit Secure-vs-Community Cloud dual pricing. Most cloud platforms hide reliability trade-offs inside “premium-by-default” architectures. RunPod publishes both Secure Cloud (enterprise DCs, SLA-backed) and Community Cloud (partner DCs, no SLA) at separate rate cards, letting customers pick per-workload based on whether they value SLA backing or rock-bottom cost. This transparent reliability tiering is unusual in cloud infrastructure.

2. Largest published GPU ladder (RTX A5000 through B300). Most platforms commit to either consumer/workstation GPUs (Vast.ai) or data-center GPUs (Fireworks, Together). RunPod publishes RTX A5000 ($0.27/hr) all the way through B300 Blackwell-Ultra ($7.39/hr, added 2026-06-30) in a single rate card — a ~27× span from workstation to frontier. The platform reaches new Blackwell-Ultra silicon within weeks of availability, keeping the top of the ladder current. This breadth captures hobbyist through enterprise on the same platform.

3. Five-SKU storage rate card with running-vs-idle differential. Volume Disk pricing changes based on whether the associated Pod is active ($0.10 running vs $0.20 idle) — a 2× idle premium that incentivizes customers to delete unused volumes. This behavioral pricing nudge is unusual in cloud storage and addresses customer complaints about accumulating idle storage costs.

4. Crypto-mining-to-AI hardware pivot heritage. Founders’ backgrounds in crypto-mining infrastructure gave RunPod access to GPU hardware relationships that pure-AI startups had to negotiate from scratch. The hardware-supply advantage shows up in pricing: RunPod’s RTX 4090 and A40 rates are materially cheaper than competitors who source GPU capacity through hyperscaler partnerships.

5. Serverless GPU workers spanning $0.58 to B300 Blackwell in one per-second card. The bottom of the Serverless worker ladder ($0.58/hour equivalent) is among the lowest published serverless GPU rates anywhere — capturing low-volume, latency-tolerant workloads that competitors price out of reach with $1+/hour minimums. As of the 2026-07-06 reprice the same per-second card now tops out at B300 (280 GB) at $9.98/hr with RTX PRO 4500 Blackwell added at $1.15/hr — the serverless ladder mirrors the Secure Cloud breadth strategy end-to-end, from 16 GB workstation cards through frontier Blackwell-Ultra inference, without a persistent-Pod commitment.

6. Four billing granularities on one rate card. As of the 2026-06-30 page restructure, RunPod surfaces four distinct compute modes side by side — Pods (per-hour), Serverless (per-second), Clusters (per-hour, instant + reserved), and per-request Public Endpoints over pre-deployed models. The same GPU silicon is sold at four different billing granularities, letting a buyer pick the metering model that matches the workload (long-running training → per-hour Pods; bursty inference → per-second Serverless; zero-ops API calls → per-request Endpoints) without leaving the platform. This metering-granularity menu is the value-side mirror of the GPU-breadth strategy: breadth of hardware below, breadth of billing model above.

Strengths & weaknesses

Billing UX : RunPod’s account controls and payment experience

• Self-serve signup — Sign up at runpod.io with email or GitHub; credit card required to spin up Pods. No free tier.
• Per-Pod cost meter — Console shows per-Pod hourly burn rate; serverless endpoints show per-second worker billing in real time.
• Cloud type selection — Customers explicitly choose Secure Cloud or Community Cloud per Pod, with rate-card display per choice.
• Spend alerts — Configurable email alerts at $X spend per period; auto-shutdown options available on credit-card billing.
• Payment methods — Credit card and ACH on self-serve; wire transfer and invoice billing on Enterprise. AWS/GCP Marketplace billing on Enterprise commits.
• Annual commit pricing — Enterprise customers receive volume discounts in exchange for annual usage commitments and dedicated GPU reservations.
• Storage aggregate view — Console aggregates all five storage SKUs into a single workspace spend view for forecasting.
• Volume Disk idle indicator — Console highlights idle Volume Disks (billed at $0.20/GB vs $0.10) so customers can delete or attach a Pod.
• Multi-region availability — US standard; EU, APAC, and other regions vary by Secure vs Community Cloud and by individual partner DC.

Strategic wins : Why RunPod’s pricing decisions worked

1. Dual-cloud architecture captured the price-reliability spectrum

By publishing Secure Cloud and Community Cloud at separate rate cards, RunPod let customers pick per-workload based on reliability needs rather than forcing a one-size-fits-all premium-by-default architecture. Hobbyists and students go to Community Cloud; production workloads go to Secure Cloud. This explicit reliability tiering captures more buyer segments than single-tier competitors.

2. GPU type breadth (RTX A5000 through B300) captured the workload spectrum

Most platforms commit to either consumer/workstation GPUs or data-center GPUs; RunPod offers both. This TAM expansion strategy captures hobbyist workloads (Stable Diffusion on RTX 4090) AND enterprise workloads (frontier inference on H100/B200/B300) on the same platform — workloads that competitors usually leave to specialized cloud providers. The 2026-06-30 B300 addition on Pods, followed a week later by the 2026-07-06 addition of B300 and RTX PRO 4500 Blackwell to the Serverless card, shows RunPod keeping the frontier end current across billing modes — not just defending the low-end hobbyist anchor. Buyers now reach Blackwell-Ultra silicon whether they want a persistent Pod or a scale-to-zero serverless worker.

3. Crypto-mining hardware heritage as the structural cost advantage

The founders’ relationships in crypto-mining infrastructure gave RunPod GPU hardware access that pure-AI startups had to negotiate from scratch. This shows up as low-end pricing: RTX 4090 at $0.69/hour and A40 at $0.44/hour are materially below competitors who source through hyperscaler partnerships. The supply-chain advantage is durable as long as GPU hardware remains scarce.

4. Volume Disk idle differential addresses real customer pain

The 2× idle premium on Volume Disk pricing ($0.20 vs $0.10) is unusual — most cloud platforms charge flat storage rates regardless of associated compute state. RunPod’s differential explicitly nudges customers to delete unused volumes, addressing accumulated-cost complaints. This behavioral pricing nudge is a smart UX choice that competitors should consider.

Areas to improve : Gaps in RunPod’s pricing approach

1. No published free tier loses self-serve evaluation traffic

Modal offers $30/month credits, Together $5 trial, Anyscale $100 trial. RunPod requires credit card on file for any evaluation — losing self-serve developers who want to test before paying. Adding even a $5–$10 trial credit (or first-hour-free on Community Cloud) would close a meaningful conversion gap.

2. Five-SKU storage rate card creates forecasting complexity

Container Disk, Volume Disk (running), Volume Disk (idle), Network Storage Standard <1TB, Network Storage Standard >1TB, Network Storage High-Performance — six distinct rates to aggregate. Modal’s single $0.09/GiB-month with 1 TiB free is materially simpler. Consolidating to two or three SKUs (or adding a “total storage” aggregate dashboard) would reduce forecasting overhead.

3. Community Cloud reliability is variable

Community Cloud runs on partner DCs with varying quality. Customers may experience materially different reliability depending on which partner DC they happen to land in. Publishing partner-DC-level reliability scoring (or letting customers pin to specific DCs) would reduce surprise downtime and increase Community Cloud confidence.

4. Network egress not itemized on pricing page

For high-volume inference workloads serving large image, audio, or video payloads, egress can be a meaningful cost line. RunPod’s pricing page does not break out bandwidth pricing. Making egress explicit (and ideally bundling a generous free egress allowance) would reduce a recurring source of surprise bills.

Key takeaways

1. Explicit reliability tiering (Secure vs Community) captures more buyer segments than single-tier architectures. RunPod’s dual-cloud structure lets hobbyists, students, and cost-sensitive workloads land at Community while production workloads land at Secure — without forcing a one-size-fits-all choice.

2. GPU type breadth (consumer through frontier) expands TAM beyond pure-data-center competitors. By offering RTX 4090 alongside B300 Blackwell-Ultra in one rate card, RunPod captures workloads that competitors leave to specialized clouds. The breadth strategy is durable as long as hobbyist and student workloads remain economically relevant — and the speed of the 2026-06-30 B300 add shows the frontier end stays current too.

3. Supply-chain heritage matters for low-end pricing. RunPod’s crypto-mining founder background gave the company GPU hardware access that pure-AI startups had to build. This shows up directly in low-end pricing — and the supply-chain advantage is hard to replicate without similar industry connections.

4. Behavioral pricing nudges (Volume Disk idle premium) address real customer pain. The 2× idle premium on Volume Disk pricing is a clever UX choice that explicitly incentivizes deleting unused storage. Other cloud platforms should consider similar nudges as customers increasingly complain about accumulating idle costs.

5. No published free tier is a measurable conversion gap. Among serverless GPU competitors, RunPod is alone in requiring credit card for evaluation. Even a modest trial credit ($5–$10) would close a meaningful self-serve PLG conversion gap.

UBP implications

1. Explicit reliability tiering is the next transparency frontier in cloud infrastructure pricing. As usage-based platforms compete on cost and reliability simultaneously, publishing separate rate cards for distinct reliability tiers gives customers the per-workload control they want.

2. Supply-chain advantage is durable in scarce-hardware markets. GPU supply will remain constrained for the foreseeable future; platforms with privileged hardware access can deliver cost advantages that pure-software optimization cannot match.

3. Behavioral pricing nudges (running vs idle differential) can shape customer behavior without negotiation. RunPod’s Volume Disk 2× idle premium is a smart UX choice that nudges deletion without enforcing it — a model other usage-based products should consider for accumulated-cost SKUs. The same discipline shows in RunPod’s 2026-07-06 Serverless reprice, which moved per-second flex rates toward the equivalent per-hour Pod card rather than letting the two metering models drift apart — when one platform sells the same silicon at per-hour, per-second, and per-request granularities, the rate ladders have to be kept in rough alignment or arbitrage and buyer confusion follow, so multi-metering usage-based platforms should expect periodic reprices whose real purpose is convergence, not headline cuts.

Sources

• RunPod pricing page (accessed 2026-07-14)
• RunPod GPU instance pricing (second-source verification of Secure Cloud per-hour Pod rates, accessed 2026-07-14)
• RunPod Serverless pricing docs (accessed 2026-07-06)
• RunPod Pods storage pricing docs (second-source verification of storage SKUs, accessed 2026-07-14)
• RunPod billing information docs (accessed 2026-06-30)
• RunPod Public Endpoints docs (accessed 2026-07-06)
• RunPod docs (accessed 2026-06-30)
• RunPod blog (accessed 2026-06-30)
• Related infra blueprint — Modal
• Related infra blueprint — Replicate
• Blueprint corpus index

Bottom line

RunPod priced its dual-cloud GPU marketplace around three structural ideas: explicit Secure Cloud (enterprise DCs, SLA-backed) versus Community Cloud (partner DCs, no SLA) at separate rate cards that let customers pick per-workload, the largest published GPU type ladder (RTX A5000 hobbyist-class through frontier B300 Blackwell-Ultra) in a single rate card, and a crypto-mining founder background that gave the company GPU hardware access driving aggressive low-end pricing. The five-SKU storage rate card with Volume Disk running-vs-idle differential ($0.10 vs $0.20) addresses real customer accumulated-cost complaints, and Serverless workers from $0.58/hour capture latency-tolerant low-volume workloads competitors price out of reach.

For AI engineering teams whose workloads span hobbyist Stable Diffusion through enterprise H100 inference — or who want explicit reliability-vs-cost choice per workload — RunPod is the most pragmatic single platform on the market. The 2026-06-30 page restructure into four billing modes (per-hour Pods, per-second Serverless, per-hour Clusters, and the new per-request Public Endpoints API over pre-deployed models) signals RunPod widening from raw-GPU rental toward a packaged model-serving menu — buyers can now match metering granularity to the workload without leaving the platform. The 2026-07-06 Serverless reprice extends that logic: it pushed the flex-worker card up through B300 Blackwell-Ultra ($9.98/hr) and nudged its rates toward the Secure Cloud per-hour card, so the same GPU breadth and roughly the same economics now hold whether a buyer picks a persistent Pod or a scale-to-zero worker. The remaining gaps (no published free tier, five-SKU storage complexity, Community Cloud reliability variable, egress not itemized) are evaluation-friction and forecasting-polish problems rather than structural pricing flaws.

Compare with peers via the blueprint corpus, or model your own spend with the RunPod pricing calculator.

Pricing timeline : Major events on a vertical axis

Each milestone below corresponds to a public pricing change, product launch, or material adjustment. Major events use a filled marker; minor adjustments use a faded one.

H100 SXM and RTX Pro 6000 Secure Cloud rates cut

Jul 2026

Live capture shows two Secure Cloud per-hour Pod cuts: H100 SXM (80GB) $3.29 to $2.99/hr and RTX Pro 6000 (96GB) $2.09 to $1.99/hr. The rest of the rate ladder — B300 $7.39, H200 $4.39, B200 $5.89, H100 PCIe $2.89, H100 NVL $3.19, A100 SXM $1.49, RTX 4090 $0.69 — held, as did all Serverless, Clusters, storage and Public Endpoints rates.

Serverless flex rates repriced; B300 + RTX PRO 4500 Blackwell workers added

Jul 2026

Live capture shows a Serverless flex-worker reprice: H200 $5.58 to $5.93/hr, H100 $4.18 to $4.55/hr, RTX 6000 Pro $4.00 to $3.49/hr, and the 48GB L40/L40S/6000-Ada class $1.90 to $1.75/hr. Two new Serverless SKUs appear — B300 (280GB) at $9.98/hr as the new top of the ladder and RTX PRO 4500 Blackwell (32GB) at $1.15/hr. Secure Cloud per-hour Pods, Clusters, storage and Public Endpoints rates held. A Series-A "1M devs" banner now runs across the top of the pricing page.

B300 added at $7.39/hr; L40/L40S rates re-sorted

Jun 2026

Live capture shows B300 (288 GB HBM3e) added as the new top of the Secure Cloud per-hour ladder at $7.39/hr, above B200 ($5.89/hr). L40S moved to $0.99/hr (from $0.86) and L40 to $0.82/hr (from $0.99). The pricing page now surfaces four compute modes — Pods, Serverless, Clusters (instant + reserved), and a per-request Public Endpoints model API — plus a Series-A announcement banner and a footer Startup Program link.

Volume Disk Idle vs Running Differential Pricing

Feb 2026

RunPod introduced differential Volume Disk pricing: $0.10/GB-month while the associated Pod is running, $0.20/GB-month while idle. The 2× idle premium incentivizes customers to delete unused volumes — addressing a customer complaint about accumulating idle storage costs.

Pods / Serverless / Instant Clusters relabel + reservations

Feb 2026

Wayback snapshot shows the pricing page sections relabeled to Pods, Serverless and Instant Clusters, with a "Gain additional savings with reservations" block added (long-term commitments for discounted active and flex workers). Instant Clusters still lists H200 SXM $4.31/hr and A100 SXM $1.79/hr per-hour with H100 SXM, L40S and B200 as Contact sales.

Instant Clusters pricing section introduced

Jan 2026

Wayback snapshot shows a new Instant Clusters Pricing section: H200 SXM $4.31/hr and A100 SXM $1.79/hr published per-hour, with H100 SXM, L40S and B200 gated behind Contact sales. Multi-node GPU clusters became a distinct, partially sales-led pricing surface alongside Pods and Serverless.

RTX Pro 6000 added to Secure Cloud lineup

Dec 2025

Wayback snapshot shows RTX Pro 6000 (96GB VRAM) added to the Secure Cloud per-hour table near the top of the HBM3e tier, alongside H200 ($3.59/hr), B200 and H100 NVL ($3.0x/hr). Rest of the rate ladder unchanged from October.

Serverless Pricing split into its own page section

Oct 2025

Wayback snapshot shows the pricing page restructured so Serverless Pricing renders as a distinct section below GPU Cloud Pricing, with per-second Flex/Active columns (180GB B200 $0.00240/s, 80GB H100 $0.00116/s flex). GPU Cloud per-hour rates held at the September levels.

Broad GPU Cloud price cut across the rate ladder

Sep 2025

Wayback snapshot shows a broad per-hour price cut versus August: H200 $3.99 to $3.59/hr, H100 PCIe $2.39 to $1.99/hr, A100 PCIe $1.64 to $1.19/hr, A100 SXM $1.74 to $1.39/hr, L40 $0.99 to $0.69/hr, RTX A6000 $0.49 to $0.33/hr, RTX 5090 $0.94 to $0.69/hr, RTX 4090 $0.69 to $0.34/hr (-51%) and RTX A5000 $0.27 to $0.16/hr. B200 held at $5.99/hr.

H200 $3.99/hr, B200 $5.99/hr in Secure Cloud rate ladder

Aug 2025

Wayback snapshot shows Secure Cloud per-hour pricing with H200 at $3.99/hr, B200 at $5.99/hr, H100 NVL $2.79/hr, H100 PCIe $2.39/hr, H100 SXM $2.69/hr, A100 PCIe $1.64/hr, RTX 5090 $0.94/hr and RTX 4090 $0.69/hr. Pricing page carried GPU Cloud, Serverless and storage sections — no Instant Clusters surface yet.

H200 Availability + Serverless H100 Workers

Mar 2025

RunPod added H200 (141GB) at $4.39/hour Secure Cloud and made H100 available as a Serverless worker tier. Expanded the rate ladder for both persistent and serverless workloads to cover frontier inference.

Network Storage Tiers Launched

Sep 2024

RunPod launched Network Storage with Standard ($0.07/GB-month under 1TB, $0.05/GB-month over 1TB) and High-Performance ($0.14/GB-month) tiers. Separated persistent storage from Pod compute, enabling cross-Pod model-weight sharing without per-Pod replication.

H100 PCIe Added at $2.89/hr

Apr 2024

RunPod added H100 PCIe (80GB) at $2.89/hour Secure Cloud — substantially undercutting hyperscaler H100 rates. The H100 launch positioned RunPod as the cost leader for frontier-model inference among managed-GPU competitors.

Serverless GPU Endpoints Launched

Aug 2023

RunPod introduced Serverless GPU endpoints — per-second billed inference workers that scale to zero when idle. Worker pricing ranged from $0.58/hour to $8.64/hour by GPU type. Brought RunPod into direct competition with Modal, Replicate, and Baseten for serverless inference.

Secure Cloud Launched

Jan 2023

RunPod launched Secure Cloud — enterprise-grade Pods running on RunPod-operated data centers with redundant power, networking, and storage. Created the dual-cloud architecture (Secure + Community) that lets customers pick price-reliability trade-offs explicitly per workload.

RunPod Founded

May 2022

Zhen Lu and Pardeep Singh founded RunPod, leveraging existing relationships in cryptocurrency-mining infrastructure to pivot GPU hardware from mining to AI inference. The initial product was Community Cloud — Pods running on partner-operated data centers at low cost.