# Pasqal Financial Model European quantum computing hardware company building neutral-atom Quantum Processing Units (QPUs) for HPC and enterprise use cases. - Canonical: https://finamodel.com/startups/pasqal - Excel download: https://finamodel.com/startup-models/pasqal.xlsx - Category: Hardware/Deep-tech - Model type: SaaS ARR / Valuation - Funding round: Series A - Funding: $29.3M - Founded: 2021 - Geography: Europe-headquartered (Paris-Saclay, France); partnerships in France, Germany, Italy, Canada [DECK] - Customer: B2B ## About the company Pasqal builds neutral-atom quantum processing units for HPC and enterprise applications. Its European quantum-hardware business depends on technical milestones, partnerships, and high-value systems, with potential revenue from installed QPUs, cloud access, research projects, and service arrangements. The company faces a long path from technical performance to commercial scale. Customers need evidence that systems solve useful workloads, while manufacturing, specialised components, installation, and R&D consume capital before recurring deployment volume is established. Model qualified opportunities, QPU sales, ASP, cloud access, service revenue, grants, and deployment timing. Include R&D, manufacturing, facilities, specialist components, installation, field engineering, and support. Performance milestones, partnership conversion, delivery capacity, system margin, grants, cloud utilisation, and repeat orders should drive scenarios. ## What's included - 5-year monthly revenue build with stage-appropriate growth assumptions - Full P&L, headcount plan, and operating-expense schedule - Cash-flow statement, runway, and burn-rate tracking - Valuation via exit multiple with a DCF cross-check - Returns analysis with MOIC and IRR - Unit economics including CAC, LTV, payback, and cohort retention ## Product & value proposition - Neutral-atom QPUs using trapped Rubidium atoms in arrays of optical tweezers - 100–1,000 qubit systems; 100 qubits available end-2021, 1,000 qubits on cloud end-2023 - Two control modes: Analogue (better near-term performance, not universal) and Digital (universal, comparable to other platforms) - Full-stack offer: hardware, quantum software (Pulser library, open-source), cloud services, and application layer - Supports 1D, 2D, 3D geometries; high connectivity advantage vs. other qubit platforms - QPU physical specs: 330 cm wide, 200 cm tall, <750 kg, <10 kW power, standard Ethernet interface, no cooling required - designed for HPC centre deployment ## Revenue model Two access modes described: 1. **On-premise QPU sales/deployment** - QPUs installed at HPC centres or client premises (TGCC France, Jülich Germany named as early adopters) 2. **Cloud access / QCaaS** - Online platform accessible to end-users and ISV partners; cloud launch end-Q1 2022 Partnership model (Co-Design): - Multi-phase engagement (~6 months/phase): framing → algorithm development & emulation → hardware implementation - Partners pay for Proofs of Concept and joint studies involving PASQAL engineers - Named paying/engaged partners: EDF, GENCI, Jülich, CINECA, Qu&Co, Multiverse Computing, Qubit Pharmaceuticals, Rahko No pricing figures (€/qubit-hour, PoC fees, hardware price) disclosed in deck. ## Traction & metrics - 100 qubits available end-2021 on in-house prototype - 1,000 qubit target on cloud by end-2023 - Cloud access planned end-Q1 2022 - On-premise QPUs at two European HPC facilities (TGCC, Jülich) by early 2023 - QAOA emulation run on 84 real instances (EDF data), 15 qubits - Approximation ratio chart (slide 14): convergence from ~0.72–0.80 at depth 1 to ~0.95–0.99 at depth 7 across two graph types - Quantum advantage demonstrated for MIS problem at 1,000 qubits (published: Serret et al., Phys. Rev. A 102, 2020) - No revenue, ARR, customer count, or bookings figures disclosed. ## Competition / moat Not explicitly named competitors. Moat framed as: - Qubit count leadership: "unrivalled performance (qubit number, connectivity, quantum volume)" - Analogue control mode enables near-term practical use cases ahead of universal quantum computers - Academic lineage: Paris-Saclay / CNRS world-leading quantum science hub - Ecosystem lock-in: HPC centre integrations (GENCI, Jülich, CINECA), ISV partnerships, open-source Pulser SDK for developer adoption - Published peer-reviewed results demonstrating quantum advantage (Scholl et al. 2020, Serret et al. 2020) ## Team & funding ask / use of funds - CEO: Georges-Olivier Reymond - No other team members named in slides. - No funding ask, round size, valuation, or use-of-funds slide in the deck. Presented to Quantonation (quantum-focused VC), suggesting active fundraise but no terms disclosed. --- ## Recommended financial model - **Archetype + why:** Hardware + SaaS/QCaaS hybrid - specifically a **contract/services revenue + recurring cloud subscription** model. Revenue has two distinct streams: (1) lump-sum or milestone-based hardware/PoC contracts, (2) recurring cloud access fees as QPU capacity scales. This is analogous to an HPC/infrastructure vendor model (think: usage-based cloud + hardware deployment) rather than a pure SaaS. A 3-statement operating model with revenue segmented by stream is most appropriate. - **Forecast horizon & granularity:** 5 years (2021–2026), quarterly for years 1–2, annual for years 3–5. Reflects long PoC cycles (~6 months/phase) and hardware deployment lead times. - **Key drivers & assumptions:** | Driver | Value / Source | | -- | -- | | Qubit count - 2021 | 100 | | Qubit count - 2023 | 1,000 | | Qubit count CAGR 2023–2026 | ~3x per 2 years (neutral-atom roadmap); reach ~10,000 by 2026 | | Cloud launch date | End Q1 2022 | | On-premise deployments - 2023 | 2 (TGCC + Jülich) | | On-premise deployments growth | +2–4 HPC sites/year from 2024; each site = multi-year contract | | PoC engagement duration | 6 months/phase | | PoC contract value | €150K–€500K/engagement (pre-commercial quantum pricing for Fortune 500/HPC); no deck data | | Active PoC partners (2021) | ~5–7 named (EDF, Multiverse, Qu&Co, Rahko, Qubit Pharma, GENCI, Jülich) | | Cloud pricing (QCaaS) | Usage-based, €/qubit-hour or subscription tier; €50K–€500K ACV for enterprise | | Gross margin - hardware | 30–50% (deep-tech hardware; scale improves margin) | | Gross margin - cloud/services | 60–75% at scale; lower early due to optics/laser infrastructure COGS | | R&D as % of revenue | 60–80% years 1–3 (pre-revenue scaling); declines to 30–40% by 2025–2026 | | Headcount | ~20–40 FTEs in 2021 (typical European quantum startup at this stage); scale to 150+ by 2026 | | Funding assumption | Series A €15–30M in 2021/22 to fund hardware scale-up and cloud build-out (context: Quantonation investor day, pre-revenue) | - **Scenarios (Base / Bull / Bear - which variables flex):** - **Base:** 2 on-premise QPU deals/year from 2023; cloud revenue ramps from 2022; 1,000 qubit milestone hit on schedule 2023 - **Bull:** Faster qubit scaling (3,000+ by 2023); 3–5 HPC deals/year; pharmaceutical/energy verticals adopt early; cloud ASP higher - **Bear:** Qubit scaling delayed 12–18 months; PoC pipeline stays thin; cloud launch slips; competition from IBM/IonQ/Google crowds market - **Required sheets / outputs:** 1. Assumptions - all drivers, toggleable scenario switch 2. Revenue build - two streams: (a) PoC/hardware contracts (volume × ACV), (b) cloud/QCaaS (seats or usage, ramp curve) 3. P&L - revenue, COGS by stream, gross profit, R&D, S&M, G&A, EBITDA, net income 4. Headcount plan - engineering, hardware, software, commercial 5. Cash & runway - burn rate, funding tranches, months of runway 6. KPI dashboard - qubit count progression, active PoC partners, on-premise deployments, cloud ARR 7. Sensitivity table - qubit scaling speed × on-premise deal velocity ## Frequently asked questions ### Is the Pasqal financial model free? Yes. The Pasqal model is a free Excel download with live formulas. ### Can I change the assumptions? Yes. The workbook is editable and its live formulas recalculate when assumptions change.