Who This Guide Is For

• Audience: Hyperscaler infrastructure planners, data center operators, energy procurement managers, nuclear industry analysts, and AI infrastructure investors navigating the power availability constraint.
• Prerequisites: Understanding of data center power infrastructure basics (PUE, IT load, cooling), familiarity with grid interconnection processes and utility rate structures, basic knowledge of nuclear reactor types and safety concepts, awareness of battery storage applications beyond backup power, and hyperscaler sustainability commitments.
• Estimated Time: Approximately 20 minutes to complete this strategic guide.

Overview

AI infrastructure expansion has collided with a hard physical constraint: power availability. This guide provides a decision framework for data center operators comparing four power sourcing strategies: grid extension (3-5 year waits), on-site generation ($2-3M per MW), Small Modular Reactor (SMR) deployment (2029-2035 timeline), and Battery Energy Storage Systems (BESS) that unlock 40% higher compute density on existing connections.

By the end of this guide, readers will understand:

• How AI workload power profiles differ from traditional computing
• Why grid interconnection queues exceed 2,600 GW with 5-year average waits
• Three competing SMR technologies and their data center fit
• How BESS transforms from backup infrastructure to compute capacity multiplier
• Hyperscaler energy procurement strategies (Meta, Amazon, Google, Microsoft)
• An actionable decision flowchart based on urgency, scale, carbon constraints, and regulatory risk tolerance

Key Facts

• Who: Hyperscalers (Meta, Amazon, Google, Microsoft) committing 12+ GW nuclear capacity by 2040
• What: Grid interconnection queues exceed 2,600 GW; Microsoft reports 47% of new capacity requests face grid constraints
• When: SMR timelines range from 2029 (Aalo Pod) to 2030s (X-energy, Blykalla); nuclear restarts operational 2028-2029
• Impact: AI data center power density reaches 50-100 MW per acre versus traditional facilities at 5-15 MW per acre

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Step 1: Understanding the AI Power Crunch

Power availability has become the defining constraint in AI infrastructure expansion. The traditional approach of securing grid interconnection and building compute capacity no longer works in markets where queues stretch to 5 years.

The Scale of the Problem

US grid interconnection queues exceeded 2,600 GW as of late 2025, according to PV Magazine analysis. This backlog represents years of accumulated demand overwhelming transmission capacity, transformer manufacturing, and permitting processes. Data center developers face 3-5 year minimum waits in constrained markets like PJM (covering Virginia, Ohio, Pennsylvania), with national averages approaching 5 years.

Microsoft’s 2025 procurement documents reveal the operational impact: 47% of new data center capacity requests encounter grid constraints. This percentage continues rising as AI workloads demand more power at faster expansion rates than utilities can deliver.

Why AI Changed the Equation

Traditional cloud computing grew incrementally, allowing utilities to plan capacity additions over multi-year cycles. AI infrastructure expansion follows a different pattern:

• Training clusters require sustained high-power computation for weeks or months, creating continuous baseload demand that utilities cannot flexibly manage.
• Inference workloads demand instant response with minimal latency, requiring rapid load-following capability that many grids cannot provide.
• Campus scale now reaches 1+ GW continuous demand, exceeding output of most utility-scale power plants.

Atlas Energy’s $840M acquisition of Caterpillar power assets in March 2026 demonstrates capital intensity of private grid development: $2-3M per MW of installed capacity. This investment enables bypassing 3-7 year utility interconnection delays but introduces carbon and reliability trade-offs.

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Step 2: AI Workload Power Profiles

AI workloads demand fundamentally different power profiles than traditional cloud computing. Understanding these differences is essential for selecting appropriate power sourcing strategies.

Training vs Inference Power Consumption

Workload Type	Power Pattern	Duration	Grid Impact
AI Training	Sustained high-power	Weeks to months	Continuous baseload demand
AI Inference	Instant response required	Milliseconds to seconds	Rapid load-following needed
Traditional Cloud	Variable but predictable	Hours to days	Manageable with existing infrastructure

AI training runs consume power continuously for extended periods. A large language model training run can require 100+ MW sustained for weeks, creating baseload demand comparable to a small city. This pattern differs from traditional computing where workloads vary throughout the day with predictable peaks.

Power Density Comparison

Facility Type	Power Density	Typical Scale
Traditional Data Center	5-15 MW per acre	10-50 MW campus
AI Training Cluster	50-100 MW per acre	100-500 MW campus
Hyperscaler AI Campus	50-100 MW per acre	1+ GW campus

This density increase means AI facilities cannot simply add more servers to existing buildings. They require dedicated power infrastructure scaled to orders-of-magnitude higher demand. Meta’s Prometheus campus demands multiple GW-scale commitments, forcing hyperscalers to think in power plant terms rather than server rack terms.

Load Variability Implications

X-energy’s XE-100 reactor demonstrates load-following capability relevant to AI inference workloads: 40-100% power ramping in 12 minutes. This speed exceeds Gen III+ reactors that require hours for comparable load changes. For inference-heavy facilities, load-following capability determines whether nuclear can serve as primary power source or requires battery buffering.

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Step 3: Grid Interconnection Bottlenecks

Understanding grid interconnection constraints helps operators evaluate whether to wait for utility connections or pursue alternatives.

Permitting and Queue Backlogs

The Federal Energy Regulatory Commission (FERC) oversees grid interconnection permitting, but the process has become a bottleneck:

• Queue depth: 2,600+ GW nationally as of late 2025
• Average wait time: 5 years from application to energization
• PJM market: Over 2,000 GW in queue, with data center developers facing 3-5 year waits

These delays reflect cumulative underinvestment in transmission capacity combined with explosive demand growth. Utility queue management prioritizes existing customers and large industrial loads, but the backlog continues growing faster than new capacity comes online.

Transformer and Equipment Shortages

Even when interconnection agreements are signed, physical infrastructure delays persist:

• Transformer manufacturing: 3-4 year lead times for large power transformers
• Switchgear availability: Supply chain constraints extending project timelines
• Transmission construction: Environmental reviews and land acquisition add 2-3 years

Peak power prices in major data center markets (Virginia, Texas, California) exceed $100/MWh during summer afternoons, reflecting grid stress and capacity scarcity.

Regional Variation

Market	Queue Depth	Typical Wait	Constraint Severity
PJM (Virginia/Ohio)	2,000+ GW	3-5 years	Critical for hyperscalers
Texas (ERCOT)	300+ GW	2-4 years	Moderate but growing
California (CAISO)	400+ GW	3-5 years	High due to renewable integration

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Step 4: Power Sourcing Strategies Comparison

Four primary strategies exist for securing AI data center power. Each carries distinct timeline, cost, and regulatory trade-offs.

Strategy Comparison Matrix

Dimension	Grid Extension	On-Site Generation	SMR Deployment	BESS Installation
Timeline	3-5+ years	Immediate	2029-2035	Immediate
Cost ($/MW)	Variable (utility rates)	$2-3M installed	Not disclosed	Variable
Carbon Impact	Depends on grid mix	High (fossil)	Zero (nuclear)	Enables renewable shift
Reliability	Utility-grade	Owner-controlled	24/7 baseload	Backup + peak-shave
Regulatory Complexity	High (FERC, environmental)	Medium (local permits)	Very High (NRC)	Low
Best For	Long-term planning	Emergency capacity	Carbon-free baseload	Capacity unlock

Grid Extension

Grid extension remains the default option for operators with multi-year planning horizons and access to markets with shorter queues. The strategy leverages existing utility infrastructure but accepts uncertainty in timeline and rate structures.

When to choose grid extension:

• Planning horizon exceeds 5 years
• Market has queue depth under 500 GW
• Carbon constraints are moderate (not net-zero 2030)
• Cost certainty from long-term utility contracts preferred

Limitations:

• Timeline uncertainty creates planning risk
• Rate structures may change during wait period
• Grid reliability depends on utility performance

On-Site Generation

Private generation bypasses grid interconnection entirely. Atlas Energy’s Caterpillar acquisition demonstrates this approach at scale: $840M investment enabling immediate deployment.

When to choose on-site generation:

• Immediate power need (0-2 years)
• No hard carbon constraint
• Budget supports $2-3M per MW capital intensity
• Regulatory tolerance for local permitting process

Limitations:

• High carbon impact conflicts with sustainability commitments
• Fuel cost volatility over project lifetime
• Maintenance and operational complexity

SMR Deployment

Small Modular Reactors offer carbon-free 24/7 baseload power with distinct timeline and regulatory characteristics.

When to choose SMR deployment:

• Planning horizon 5+ years (2029-2035 timeline)
• Net-zero carbon commitment before 2040
• Scale requirement 50-500+ MW
• Regulatory tolerance for NRC licensing pathway

Limitations:

• Timeline extends to 2030s for most technologies
• NRC design certification process adds complexity
• Capital cost not fully disclosed publicly
• Single-technology commitment creates hedging risk

BESS Installation

Battery Energy Storage Systems transform from backup infrastructure to compute capacity multiplier under the Compute Per Megawatt (CPM) framework.

When to choose BESS:

• Existing grid connection facing capacity constraints
• Immediate need to unlock more compute
• Peak-shaving economics favorable
• Low regulatory tolerance preferred

Limitations:

• Storage duration limited (4-8 hours typical)
• Round-trip efficiency 75-85% creates energy loss
• Does not address total power shortage
• Requires existing grid connection as foundation

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Step 5: SMR Options for Data Centers

Three SMR technologies compete for data center applications with distinct technical and timeline characteristics.

SMR Technology Comparison Matrix

Dimension	Blykalla SEALER	X-energy XE-100	Aalo Pod
Coolant	Lead (inert)	Helium (inert gas)	Sodium (reactive metal)
Module Size	~50 MWt thermal	80 MWe / 200 MWt	10 MWe per reactor
Deployable Unit	300 MW (6 units)	320 MWe (4-pack)	50 MWe (5 reactors)
Key Safety Feature	No hydrogen risk, atmospheric pressure	TRISO fuel cannot melt	Fast-neutron stability
Load-Following	Not disclosed	40-100% in 12 min	Not disclosed
Design Life	Not disclosed	60 years	Not disclosed
Commercialization	Early 2030s	2030s	2029 (fastest)
Data Center Fit	Medium scale	Hyperscale	Purpose-built

Blykalla SEALER (Lead-Cooled)

Blykalla’s SEALER reactor uses lead coolant operating at atmospheric pressure. This design eliminates hydrogen explosion risk associated with water-cooled reactors under accident conditions. The Swedish company plans 300 MW output from six reactors at Norrsundet, targeting early 2030s commercial operation.

Advantages for data centers:

• Atmospheric pressure operation reduces containment complexity
• Lead coolant inertness eliminates certain accident scenarios
• Higher thermal efficiency than water-cooled designs
• Swedish regulatory pathway offers European deployment model

Timeline considerations:

• Permitting initiation in late 2026
• Commercial operation early 2030s
• Four-agency approval process in Sweden extends timeline

X-energy XE-100 (TRISO Fuel)

X-energy’s XE-100 uses TRISO-X fuel in a helium-cooled pebble-bed design. TRISO fuel particles cannot melt at any achievable temperature, providing inherent safety that simplifies regulatory approval. Each 80 MWe module combines into 320 MW four-unit plants.

Advantages for data centers:

• TRISO fuel eliminates meltdown scenarios
• 40-100% load-following in 12 minutes matches inference workload patterns
• 60-year design life provides long-term reliability
• 11+ GW development pipeline across US and UK demonstrates commercial traction
• NRC pre-application engagement advances regulatory pathway

Timeline considerations:

• 2030s commercial deployment target
• Partnership with Talen for PJM market deployment (960+ MW)
• Amazon commitment of 5+ GW by 2039

Aalo Pod (Sodium-Cooled)

Aalo’s 50 MW Pod uses sodium coolant in a fast-neutron reactor design. The company completed Critical Test Reactor assembly at Idaho National Laboratory in March 2026, targeting July 4, 2026 criticality under DOE Nuclear Reactor Pilot Program.

Advantages for data centers:

• 2029 commercial target is fastest SMR timeline
• 50 MW size matches typical data center incremental capacity additions
• Purpose-built design for data center applications
• DOE Pilot Program provides streamlined regulatory pathway

Limitations:

• Sodium’s chemical reactivity introduces operational risks TRISO designs avoid
• Smaller scale requires multiple units for hyperscale campuses
• Less disclosed technical information than competitors

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Step 6: BESS Role in AI Load Management

Battery Energy Storage Systems (BESS) have transformed from backup power infrastructure to compute capacity multipliers under the Compute Per Megawatt (CPM) framework.

The CPM Framework

The Compute Per Megawatt framework reframes batteries as enablers of higher compute density rather than mere backup systems. Technical implementation involves:

1. Time-shift: Batteries charge during low-demand, low-price periods (often when renewable generation peaks)
2. Peak-shaving: Discharge during high-demand AI training bursts to avoid demand charges
3. Capacity unlocking: Push compute beyond contracted grid capacity without violating interconnection agreements

This approach improves grid connection utilization from 60-70% average to 95%+ average, enabling 40% higher compute density on existing connections.

BESS Technical Parameters

Parameter	Value	Implication
Round-trip efficiency	75-85%	Energy loss during storage cycle
Response time	Seconds to minutes	Faster than grid load-following
Typical duration	4-8 hours	Covers daily demand cycles
Integration complexity	Low	Minimal regulatory hurdles

Revenue and Efficiency Opportunities

BESS deployment creates multiple value streams beyond compute capacity:

• Demand charge reduction: Peak-shaving reduces utility demand charges
• Time-of-use arbitrage: Charge at low prices, discharge at high prices
• Grid services: Frequency regulation and capacity market participation
• Renewable integration: Storage enables higher renewable penetration

PV Magazine projects hyperscalers will add 5-10 GW behind-the-meter storage annually starting 2027, reflecting the CPM framework’s commercial viability.

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Step 7: Hyperscaler Energy Procurement Strategies

Major hyperscalers have committed over 12 GW nuclear capacity by 2040, each pursuing distinct strategic approaches.

Hyperscaler Nuclear Commitments Comparison

Hyperscaler	Total Capacity	Timeline	Technology Approach	Key Partnerships
Meta	6.6 GW	By 2035	Diversified (Natrium, Oklo, Vistra)	TerraPower, Oklo, Vistra
Amazon	5+ GW	By 2039	Concentrated (TRISO)	X-energy, Talen
Google	600+ MW	2029+	Restart + SMR	NextEra, Kairos Power
Microsoft	835 MW+ SMR	2028+	Restart + Fusion + Micro	Constellation, Helion, Aalo

Meta: Portfolio Diversification

Meta’s 6.6 GW nuclear commitment represents the largest corporate nuclear purchase in US history. The company pursues diversification across three technologies:

• TerraPower Natrium: 2.8 GW from 8 units, molten salt energy storage
• Oklo Aurora: 1.2 GW Ohio campus, fast reactor design
• Vistra existing plant PPAs: 2,176 MW from operational nuclear plants

This portfolio approach hedges technology risk. If one design fails to commercialize, Meta retains capacity from alternative pathways.

Amazon: Concentrated TRISO Bet

Amazon committed 5+ GW to X-energy TRISO technology by 2039, representing stronger technology conviction than Meta’s diversification. The Cascade Advanced Energy Center will deploy 12 XE-100 modules.

This concentrated approach offers:

• Higher execution efficiency: Single technology focus simplifies deployment
• TRISO safety advantage: Fuel cannot melt at any temperature
• X-energy pipeline: 11+ GW development pipeline demonstrates commercial momentum

Risk factor: Single-technology exposure creates hedging vulnerability if TRISO pathway encounters obstacles.

Google: Restart Plus SMR Hybrid

Google pursues a hybrid strategy combining near-term restarts with longer-term SMR development:

• Duane Arnold restart: 600+ MW by 2029 via 25-year NextEra PPA
• Kairos Power SMR: Longer-term advanced reactor development

This approach addresses immediate power needs while investing in future nuclear capacity.

Microsoft: Restart + Fusion + Microreactor

Microsoft combines three distinct nuclear pathways:

• Three Mile Island restart: 835 MW via Constellation Energy, operational 2028+
• Helion fusion PPA: Advanced fusion development agreement
• Aalo Atomics collaboration: AI-powered permitting acceleration targeting 50% timeline reduction

Microsoft’s strategy spans proven restarts, advanced fusion bets, and microreactor collaboration for incremental capacity.

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Step 8: Decision Framework for Operators

This decision flowchart guides operators through power sourcing choices based on urgency, scale, carbon constraints, and regulatory risk tolerance.

Decision Flowchart (Text Description)

START: What is your immediate power requirement urgency?

BRANCH A: Immediate (0-2 years)
  -> Question 2: What is your carbon constraint?
     -> Net zero by 2030: BESS + renewable PPAs (cannot use fossil generation)
     -> Net zero by 2040: BESS + existing grid optimization
     -> No hard carbon target: Private generation ($2-3M/MW) acceptable

BRANCH B: Medium-term (2-5 years)
  -> Question 2: What is your power scale?
     -> 50-100 MW: Grid extension + BESS augmentation
     -> 300-500 MW: Evaluate SMR early commitment + grid backup
     -> 1+ GW: Existing plant PPAs (restarts) + SMR portfolio planning

BRANCH C: Long-term (5+ years)
  -> Question 3: What is your regulatory risk tolerance?
     -> Low (need certainty): Existing plant restarts (TMI, Duane Arnold) or X-energy TRISO with NRC progress
     -> Medium: X-energy TRISO with NRC pre-application progress
     -> High (can wait): Aalo DOE Pilot Program or Blykalla Swedish pathway

FINAL OUTPUT: Recommended power sourcing strategy

Step-by-Step Decision Process

Step 1: Determine Urgency

Urgency Level	Recommended Path
Immediate (0-2 years)	BESS + existing grid or private generation
Medium-term (2-5 years)	Grid extension + BESS optimization
Long-term (5+ years)	SMR strategic commitment

Step 2: Assess Power Scale

Scale Requirement	Recommended Solution
50-100 MW incremental	Aalo Pod microreactor or BESS augmentation
300-500 MW campus	X-energy 4-pack or Blykalla 6-unit
1+ GW hyperscale	Multi-SMR portfolio + existing plant PPAs

Step 3: Evaluate Carbon Constraint

Carbon Target	Power Strategy
Net zero by 2030	Nuclear (restart or SMR) + renewable PPAs
Net zero by 2040	SMR deployment timeline compatible
No hard carbon target	Private fossil generation acceptable

Step 4: Assess Regulatory Risk Tolerance

Risk Tolerance	Recommended Technology
Low (need certainty)	Existing plant restarts (Duane Arnold, TMI) or BESS
Medium	X-energy TRISO with NRC pre-application progress
High (can wait)	Aalo DOE Pilot Program or Blykalla Swedish pathway

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Common Mistakes & Troubleshooting

Symptom	Cause	Fix
Assuming SMRs solve current power constraints	SMR timelines range 2029-2035, not immediate	Position SMRs as strategic long-term hedge; use BESS or private generation for immediate needs
Treating BESS as backup-only infrastructure	CPM framework demonstrates batteries as compute multiplier	Design batteries for peak-shaving and time-shift, not just backup reliability
Single-technology nuclear commitment without diversification	Technology risk if single pathway fails	Consider portfolio approach like Meta’s 6.6 GW across Natrium, Oklo, Vistra; diversification hedges risk
Underestimating grid interconnection timeline uncertainty	3-5 year minimum wait with 2,600+ GW queue backlog	Plan for grid alternatives or accept 5+ year capacity delays; Microsoft’s 47% constraint rate demonstrates systemic bottleneck
Selecting SMR size mismatched to incremental capacity	Data centers typically add 50-100 MW increments	Aalo’s 50 MW matches this better than 300+ MW designs; size mismatch forces overbuild

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Key Timeline Milestones

Date	Event	Significance
July 4, 2026	Aalo Critical Test Reactor criticality deadline	Validates sodium-cooled microreactor pathway
Late 2026	Blykalla permitting initiation	Swedish regulatory process begins
2028+	Microsoft Three Mile Island restart	835 MW nuclear operational
2029	Aalo Pod commercial deployment	First SMR purpose-built for data centers potentially operational
2029	Google Duane Arnold restart	600+ MW nuclear via NextEra PPA
Early 2030s	Blykalla SEALER commercial	300 MW lead-cooled SMR for Swedish data centers
2030s	X-energy/Talen PJM deployment	960+ MW SMR capacity in Pennsylvania corridor
2035	Meta nuclear target	6.6 GW commitments operational
2039	Amazon nuclear target	5+ GW X-energy SMR deployment
2040	Projected hyperscaler SMR capacity	40+ GW potential if technology proves reliable

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🔺 Scout Intel: What Others Missed

Confidence: high | Novelty Score: 78/100

Most coverage frames the SMR race as technology competition, but the strategic signal is hyperscalers shifting from model provider to infrastructure owner. Meta’s 6.6 GW commitment across TerraPower, Oklo, and Vistra represents portfolio hedging that acknowledges no single SMR technology has proven commercial viability. Amazon’s concentrated X-energy bet signals stronger conviction but higher single-technology exposure. The critical timeline reality: even Aalo’s 2029 target leaves 3+ years of power gap for operators facing immediate constraints. This gap forces BESS adoption not as backup but as primary capacity unlocker via the CPM framework enabling 40% higher compute density on existing connections.

The regulatory pathway analysis reveals an underreported opportunity: DOE Nuclear Reactor Pilot Program provides Aalo a streamlined pathway potentially 50% faster than standard NRC licensing. Microsoft’s AI-powered permitting collaboration with Aalo targets acceleration that could establish precedent for future SMR approvals. Operators evaluating SMR options should prioritize regulatory pathway maturity alongside technology characteristics. X-energy’s heavy NRC pre-application investment demonstrates this foresight; Blykalla’s Swedish 4-agency approval process illustrates alternative pathway complexity.

Key Implication: Operators should sequence power strategy: immediate BESS deployment to unlock existing capacity (0-2 years), grid extension or private generation for medium-term needs (2-5 years), and SMR portfolio commitment as strategic hedge against long-term grid uncertainty (5+ years). The SMR race is a 2030s story; the BESS opportunity is actionable now.

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Summary & Next Steps

What You Have Learned

• Grid interconnection queues exceed 2,600 GW with 5-year average waits, making power availability the primary AI infrastructure constraint
• AI workload power density reaches 50-100 MW per acre, requiring dedicated power infrastructure scaled orders of magnitude beyond traditional facilities
• Three SMR technologies compete for data center applications: Blykalla (lead-cooled, early 2030s), X-energy (TRISO, 2030s, largest pipeline), Aalo (sodium, 2029, purpose-built)
• BESS transforms from backup to compute capacity multiplier via CPM framework, enabling 40% higher density on existing connections
• Hyperscalers have committed 12+ GW nuclear capacity by 2040, with Meta’s 6.6 GW representing the largest corporate nuclear purchase in US history

Recommended Next Steps

1. Immediate: Evaluate existing grid connections for BESS deployment potential; calculate CPM framework ROI based on current utilization rates
2. Medium-term: Assess grid extension timeline in target markets; consider existing plant restart PPAs if available
3. Long-term: Develop SMR portfolio strategy matching incremental capacity needs; consider technology diversification like Meta’s approach
4. Monitoring: Track Aalo July 2026 criticality milestone as early indicator of microreactor pathway viability

Related Coverage

• Swedish SMR: Blykalla SEALER Plant at Norrsundet — Lead-cooled 300 MW design targeting Swedish data centers
• X-energy and Talen Multi-SMR Deployment in Pennsylvania — TRISO technology for PJM market hyperscalers
• Aalo Atomic Microreactor for Idaho Data Centers — 50 MW sodium-cooled design purpose-built for data centers
• SMR Race to Power Data Centers: Blykalla, X-energy, Aalo — Comparative analysis of three SMR technologies competing for hyperscaler partnerships

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Sources

• World Nuclear News: Blykalla SEALER SMR — A-tier, March 2026
• World Nuclear News: X-energy Talen Partnership — A-tier, March 2026
• World Nuclear News: Aalo Microreactor — A-tier, March 2026
• World Nuclear News: Meta Nuclear Commitment — A-tier, March 2026
• X-energy Official: XE-100 Specifications — S-tier, official technical specifications
• PV Magazine: Battery Storage for AI Growth — A-tier, March 2026
• Utility Dive: Atlas Energy Caterpillar Acquisition — A-tier, March 2026
• World Nuclear News: Amazon SMR Progress — A-tier, March 2026
• World Nuclear News: Google Duane Arnold — A-tier, March 2026