Poolside pricing

About

Poolside is a frontier AI lab that builds its own foundation models for software development and sells them — wrapped in agents, IDE tooling, and a deployment stack — to large enterprises and governments. Founded in 2023 by Jason Warner (former CTO of GitHub) and Eiso Kant, it is headquartered in Paris and explicitly positions itself as a model company, not a Copilot-style wrapper over someone else’s API.

The product line centers on two in-house models: Malibu, a high-capacity model for multi-file generation, refactoring, and test creation, and Point, a smaller quantized model tuned for sub-200ms inline completion in the IDE. On top of the models sit VS Code / JetBrains / Visual Studio / Coder plugins, a CLI, and multi-agent orchestration that plans, executes code in sandboxes, and opens pull requests automatically.

What makes the business — and therefore the pricing — distinctive is the go-to-market: Poolside targets organizations with 5,000+ developers (banks, defense contractors, public-sector agencies) and deploys a dedicated model on-prem, in a private VPC, or via AWS Bedrock, with forward-deployed research engineers embedded in the customer’s team. That is a fundamentally sales-led, contract-based motion with no self-serve path.

On funding: Poolside raised a $500M Series B in October 2024 (led by Bain Capital Ventures, with NVIDIA, eBay Ventures, DST Global, Citi Ventures and others) at a roughly $3B valuation, taking total raised to about $626M. By late 2025, multiple outlets reported it raising up to $2B at a ~$12B valuation, with NVIDIA preparing to commit $500M–$1B, alongside Project Horizon — a 2-gigawatt AI campus in West Texas with CoreWeave and 40,000+ NVIDIA GB300 GPUs.

For the latest, visit Poolside.

Pricing summary : How Poolside’s pricing model works

Poolside publishes no rate card. As of 2026-06-16, poolside.ai exposes Models, Products, Enterprise, and Government sections but no pricing page — the /pricing URL returns a “page not found” error. Every deal is sales-quoted through a “Talk to us” contact, so price_transparency here is sales-only.

What you can verify is the shape of the contract. Poolside sells custom enterprise agreements that combine three things: (1) a per-developer-seat subscription core, (2) a dedicated model deployment in the customer’s environment (on-prem, private VPC, or managed AWS Bedrock), and (3) the compute that runs that dedicated model, plus embedded professional services (forward-deployed research engineers). That is a hybrid seat-plus-usage structure with a heavy commitment component — not metered per-token API access.

What makes this different: Most coding assistants sell a flat per-seat SaaS plan over a shared API (Copilot, Cursor). Poolside instead deploys a dedicated model trained on your proprietary codebase inside your infrastructure, so the bill is sized to seats and the compute footprint of that private deployment — closer to an enterprise platform contract than a developer-tools subscription. Because Poolside trains the models itself, the cost base is GPU capex (10,000 GPUs after the Series B; 40,000+ GB300s planned), which is reflected in enterprise-scale, multi-year commitments rather than monthly self-serve prices.

Pricing by product

Sales motions across products: sales-led only. There is no self-serve, free, or PLG path. Poolside does not list per-seat or per-token rates publicly; figures elsewhere in this page are funding/deal facts cited in words, not a rate card.

Hidden costs : What Poolside users actually pay

Because pricing is sales-only, the real “hidden costs” are structural rather than line-item overages. The cost drivers you should price into any Poolside evaluation:

No public dollar figures exist for any of these, so the only way to size a bill is a sales conversation scoped to your developer count and deployment environment. For how compute-coupled costs behave in usage-based contracts, see our introduction to usage-based pricing.

Want to estimate your own Poolside bill? Use the Poolside pricing calculator to model seat and deployment scenarios — but treat all outputs as estimates, since Poolside publishes no rates.

Pricing evolution : Poolside pricing history and changes

Cadence

Tracked range: 2024–present. Poolside has never published a public price, so “pricing evolution” here tracks the funding and capacity milestones that shape its enterprise contract economics rather than rate-card moves.

Notable changes

• 2024-10-02 — $500M Series B at a ~$3B valuation (Bain Capital Ventures lead; NVIDIA, eBay Ventures, DST Global, Citi Ventures among investors). Pricing stayed sales-only.
• 2025-10-31 — Reported raise of up to $2B at a ~$12B valuation, NVIDIA committing $500M–$1B; Project Horizon 2GW campus announced. No rate card introduced.
• 2026-06-16 — Verified: still no public pricing. poolside.ai shows Models / Products / Enterprise / Government; /pricing returns 404.

What’s unique : Poolside’s distinctive pricing mechanics

1. You pay for a dedicated model, not shared API calls. Unlike Copilot or Cursor, Poolside deploys a model trained on your codebase inside your infrastructure. The price therefore bundles compute and a private training environment — a platform contract, not a per-seat SaaS line.

2. Compute footprint is a first-class pricing dimension. Because Poolside runs frontier models on customer-controlled hardware (on-prem, VPC, or Bedrock), the GPU footprint of your deployment is part of the bill. That makes pricing scale with deployment size, not just headcount.

3. Professional services are bundled, not bolted on. Forward-deployed research engineers embed with the customer and “take joint responsibility for outcomes.” The implementation cost that other vendors charge separately (or skip) is folded into the Poolside contract value.

Strengths & weaknesses

Billing UX : Poolside billing controls and transparency

• Billing controls — Not publicly documented; handled through enterprise contracts and account teams rather than a self-serve billing dashboard.
• Usage visibility — Deployments include RBAC and audit trails, which give admins visibility into usage and access, but there is no public consumption/spend meter described.
• Payment options — Custom enterprise procurement (invoicing, POs, multi-year terms) — no credit-card or self-serve checkout. Engagement starts with “Talk to us.”

Strategic wins : Why Poolside’s pricing decisions worked

1. Selling the model, not the seat, justifies enterprise-scale contracts

By deploying a dedicated, custom-trained model rather than a shared API, Poolside reframes the purchase from “developer tool” to “AI platform,” which supports far larger contract values per customer. See how AI companies are shifting away from per-user licenses.

2. Sales-only pricing matches the buyer

For Global 2000 and government buyers, procurement, security review, and on-prem deployment dominate — a public rate card adds little and can anchor negotiations low. Quoting per engagement lets Poolside price to the value of a dedicated model in a regulated environment. Related: outcome-based and value pricing trends.

3. License-safe, air-gapped deployment unlocks the highest-paying segment

Excluding GPL/AGPL code from training and supporting air-gapped deployment directly addresses the compliance blockers that keep banks and defense agencies off shared-API assistants — the segment most able to fund frontier compute. See choosing the right usage metric for how value-aligned dimensions support premium pricing.

Areas to improve : Gaps in Poolside’s pricing approach

1. Total opacity raises buyer friction

With no public anchor at all, even qualified buyers cannot estimate budget before committing to a sales cycle. A published “starting at” floor or sample TCO model would lower the barrier without giving up custom quoting. See bill shock and cost unpredictability.

2. Compute-coupled pricing is hard to forecast

Because the bill scales with the dedicated compute footprint, customers face the same unpredictability as raw GPU spend. Clear capacity tiers or usage caps would make TCO more forecastable for finance teams.

3. No on-ramp for smaller teams or pilots

There is no trial, low-commitment pilot SKU, or self-serve tier, so Poolside cannot capture mid-market demand or land-and-expand from small teams — a gap competitors with free/pro tiers exploit.

Key takeaways

1. No public pricing — every deal is sales-quoted. Poolside is a genuine “frontier lab, no rate card” company; budget only via a sales conversation.
2. The unit is a dedicated model deployment, not a seat. Pricing bundles per-developer seats, dedicated compute, and embedded engineers into one enterprise contract.
3. Compute is a pricing dimension. Running a private frontier model on-prem/VPC means the GPU footprint drives cost as much as headcount.
4. Built for regulated buyers. License-safe training and air-gapped deployment target banks, defense, and government — the segment that can fund frontier compute.
5. Capital and NVIDIA backing underwrite the model. A ~$3B (2024) then reported ~$12B (2025) valuation and NVIDIA investment fund the GPU base that the enterprise contracts ultimately pay for.

UBP implications

1. When the cost base is compute, couple price to deployment, not just seats. Poolside shows how a model lab aligns price with the GPU footprint it provisions per customer rather than a flat per-user fee.
2. Sales-only pricing is a legitimate strategy for high-value, regulated buyers — transparency matters less when the deal is a security-reviewed, multi-year platform commitment.
3. Bundling professional services into contract value is a UBP-adjacent lever: it raises ACV and de-risks adoption, but obscures the unit economics buyers want to compare.

Sources

• Poolside official website — homepage and nav, no pricing page (accessed 2026-06-16)
• Poolside /pricing returns 404 — confirms sales-only (accessed 2026-06-16)
• TechCrunch: Poolside raises $500M from eBay, NVIDIA and others (accessed 2026-06-16)
• Sacra: Poolside valuation, funding & product profile (accessed 2026-06-16)

Bottom line

Poolside is a frontier AI lab building its own code foundation models and selling them — as dedicated, custom-trained deployments — to large enterprises and governments. There is no public pricing: every deal is sales-quoted around per-developer seats, dedicated compute, and embedded engineering, with multi-year commitments. If you run a 5,000+ developer org in a regulated environment and want a model trained on your codebase inside your infrastructure, Poolside is built for you — but expect a procurement-led process, not a checkout. Compare it against fully-priced coding assistants in the pricing blueprint.

Want to compare Poolside against other AI coding companies? Browse the pricing blueprint.