For those exploring the power of Mac Studio in machine learning, selecting the right model involves balancing performance, budget, and future-proofing. The Apple Mac Studio with M3 Ultra stands out as the best overall choice thanks to its top-tier CPU and GPU, perfect for demanding ML tasks. The Mac Studio with M4 Max offers a compelling middle ground with high performance at a lower price point, making it ideal for serious hobbyists and professionals on a budget. Meanwhile, the Mac Mini with M4 Pro delivers solid performance at a more accessible price, suited for entry-level ML work. Continue reading for a detailed breakdown of these options and more, along with guidance on how to choose the best Mac for your machine learning projects.
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Key Takeaways
- The top-tier M3 Ultra Mac Studio delivers unmatched performance but comes at a premium price, making it ideal for intense ML workloads.
- M4 Max-based models strike a balance between power and cost, suitable for most professional ML users who need high performance without the highest price.
- Mac Mini options provide a budget-friendly entry point for beginners or light ML tasks, though they may struggle with larger datasets or complex models.
- Unified memory capacity is critical — models with 64GB or more significantly improve handling large datasets and multitasking.
- The choice between desktop and portable depends on whether mobility or raw power is more important for your ML projects.
| mac studio for machine learning | Storage | Processor | Memory | CPU |
|---|---|---|---|---|
| Apple Mac Studio | 1TB SSD | — | — | 32-core |
| Apple 2026 Mac Studio Desktop | — | M5 Max chip | Up to 128GB | 18-core |
| Apple MacBook Pro 16.2-inch La | 2TB SSD | — | 128GB | 18-core |
| Apple 2024 Mac mini Desktop Co | 512GB SSD | M4 Pro | 24GB | 12-core |
| Apple Mac Studio with M4 Max | 2TB SSD | M4 Max | 64GB | 16-core |
| Apple 2026 MacBook Pro Laptop | 2TB SSD | M5 Max chip with 18-core CPU and 32-core GPU | 36GB Unified Memory | — |
| Apple 2020 Mac Mini with M1 Ch | 256GB SSD | Apple M1 Chip | — | — |
| Mac mini with M4 Pro Chip | 1TB SSD | M4 Pro chip, 10-core CPU and GPU | 24GB | — |
| Apple 2026 Mac mini Desktop Co | — | M5 Pro | — | — |
| Apple 2026 MacBook Pro 16.2" L | 2TB SSD | M5 Max (18-core CPU, 40-core GPU) | 48GB Unified Memory | — |
More Details on Our Top Picks
Apple Mac Studio (M3 Ultra, 32-Core CPU, 80-Core GPU, 256GB Unified Memory, 1TB SSD)
The Mac Studio with M3 Ultra stands out for its powerhouse performance, making it ideal for running large AI models and complex workflows that would challenge most desktops. Compared to the Mac Studio with M5 Max, it offers even more CPU and GPU cores, enabling faster training and inference for demanding machine learning tasks. The massive 256GB of unified memory ensures large models can be loaded entirely in memory, reducing bottlenecks. However, this configuration comes at a premium price and lacks user upgradeability, meaning you need to be certain of your specs upfront. It’s best suited for AI researchers and professionals who require maximum processing power and memory without compromise. For those with tighter budgets or who prefer flexibility, options like the Mac mini with M4 Pro may be more appropriate, despite offering less raw power.
Pros:- Exceptional performance with 32-core CPU and 80-core GPU for demanding ML workloads
- Supports up to 8 displays, ideal for multi-monitor AI development setups
- Massive 256GB unified memory enables running large models entirely in RAM
- Modern connectivity including Thunderbolt 5 and 10Gb Ethernet
Cons:- Premium pricing makes it inaccessible for many users
- Not user-upgradable after purchase, limiting future expansion
Best for: AI researchers and data scientists working on large models that need the utmost processing power and memory capacity.
Not ideal for: Budget-conscious users or those who prefer upgradeability, since this high-end setup is fixed at purchase and comes at a premium.
- Chip:Apple M3 Ultra
- CPU:32-core
- GPU:80-core
- Unified Memory:256GB
- Storage:1TB SSD
- Max Displays:Up to 8 (M3 Ultra)
- Connectivity:Thunderbolt 5, HDMI 2.1, 10Gb Ethernet
Our verdict“This is the best choice for AI professionals who need maximum computational and memory resources without regard to cost.”
Apple 2026 Mac Studio Desktop Computer with M5 Max Chip
The Mac Studio with M5 Max offers a compelling blend of power and compactness, making it suitable for professionals who need strong AI processing alongside creative tasks. Compared to the Mac Studio with M3 Ultra, it provides a slightly lower CPU and GPU core count but still delivers exceptional performance, especially with support for extensive memory and fast storage. Its compact size and quiet operation make it perfect for a busy workspace, and it supports multiple external displays, similar to the M3 Ultra model. The main tradeoff is its high price and limited upgrade options—components are integrated, so future improvements require a new purchase. This makes it ideal for creative teams, small AI labs, or broadcasters who need reliable, high-end performance without excessive bulk.
Pros:- Excellent processing power with M5 Max chip and high core counts
- Supports multiple external displays with robust connectivity options
- Compact, quiet design ideal for office environments
- Fast data transfer and memory bandwidth for AI tasks
Cons:- High price point limits accessibility for some users
- Limited upgradeability due to integrated components
Best for: Creative professionals and AI developers who need a powerful desktop that fits into a small workspace without sacrificing performance.
Not ideal for: Users seeking extensive upgradeability or a lower-cost entry point, as this model is a premium investment with fixed components.
- Processor:M5 Max chip
- CPU:18-core
- GPU:40-core
- Memory:Up to 128GB
- Storage bandwidth:Up to 614GB/s
- Ports:Four Thunderbolt 5, USB-C, USB-A, HDMI
- Size:7.7-inch square
Our verdict“Best suited for professionals who need a compact yet powerful machine for AI and creative workflows without the need to upgrade later.”
Apple MacBook Pro 16.2-inch Laptop with M5 Max, 18-core CPU, 40-core GPU, 128GB Unified Memory, 2TB SSD – Space Black
The MacBook Pro 16.2-inch with M5 Max combines desktop-class power with portability, making it ideal for AI workflows that require mobility. Its 16.2-inch Liquid Retina XDR display delivers stunning visuals and high brightness, essential for data visualization and model debugging. When compared to the Mac Studio with M5 Max, it offers similar processing power but in a portable form factor, supporting up to four external displays. The inclusion of Neural Accelerators on the GPU enhances on-device AI inference, while the battery life promises all-day productivity. The main tradeoff involves its large size and weight relative to traditional laptops, and the high price adds a barrier for some. It’s best for AI researchers, developers, and creatives who need a powerful machine in a portable package.
Pros:- Powerful M5 Max chip with 40-core GPU and Neural Accelerators for AI workloads
- High-brightness Liquid Retina XDR display for detailed visualization
- Supports up to four external displays and extensive connectivity
- All-day battery life maintains performance on the move
Cons:- Large, heavy for a laptop, reducing portability compared to smaller models
- High price point may limit accessibility
Best for: AI professionals and creative users who need desktop-class performance with mobility for on-the-go projects.
Not ideal for: Users who prioritize upgradeability or have a tighter budget, as high-end configurations come at a premium and internal components are fixed.
- Chip:Apple M5 Max
- CPU:18-core
- GPU:40-core
- Display:16.2-inch Liquid Retina XDR
- Memory:128GB
- Storage:2TB SSD
- Ports:3x Thunderbolt 5, MagSafe 3, SDXC, HDMI
Our verdict“Ideal for AI researchers or creatives who require a desktop-level machine with mobility and stunning visuals.”
Apple 2024 Mac mini Desktop Computer with M4 Pro Chip, 24GB Memory, 512GB SSD
The Mac mini with M4 Pro offers a surprisingly capable platform for machine learning and creative workflows in a tiny footprint. Compared to the larger Mac Studio models, it provides a more affordable entry point and excellent connectivity options, including Thunderbolt, HDMI, and Ethernet. While it doesn’t match the raw power of the Mac Studio with M5 Max or M3 Ultra, its 12-core CPU and 16-core GPU handle most AI tasks efficiently, especially with 24GB of unified memory. Its small size makes it ideal for environments with limited space or multi-device setups. The main limitations are storage capacity and upgradeability—additional external storage may be necessary. This is best for small teams, developers, or hobbyists starting with AI projects but needing a compact, capable machine.
Pros:- Compact size fits easily into small workspaces
- Powerful M4 Pro chip handles demanding AI tasks efficiently
- Multiple connectivity options for flexible setups
- Great value for a capable desktop in a small package
Cons:- Limited internal storage without external expansion
- Less powerful than higher-tier Mac Studio models for large-scale AI workloads
Best for: Small AI projects, developers, and creative professionals needing a compact, versatile desktop.
Not ideal for: Heavy AI workloads involving very large models or those requiring future upgradeability, as internal expandability is limited.
- Processor:M4 Pro
- CPU:12-core
- GPU:16-core
- Memory:24GB
- Storage:512GB SSD
- Dimensions:5 x 5 x 2 inches
- Connectivity:Thunderbolt, HDMI, Ethernet
Our verdict“A solid choice for compact AI and creative workflows where space is a concern but high performance is still needed.”
Apple Mac Studio with M4 Max, 16-Core CPU, 40-Core GPU, 64GB Unified Memory, 2TB SSD
The Mac Studio with M4 Max strikes a balance between power and efficiency, making it suitable for intensive AI, visual effects, and 3D rendering. Compared to the MacBook Pro with M5 Max, it offers similar CPU and GPU cores but benefits from a dedicated desktop design, which typically allows for better thermal management and sustained high performance. Its 64GB of unified memory supports complex workflows, while the 2TB SSD provides ample storage for large datasets and models. The Mac Studio is quieter and more expandable than the laptop, but it also comes with a higher price and less portability. It is well-suited for studio environments or users who need a powerful, dedicated machine for AI and creative projects that don’t require mobility.
Pros:- High-performance 16-core CPU and 40-core GPU for demanding workflows
- Large 64GB unified memory supports multitasking and large models
- Quiet operation with excellent thermal management
- Ample storage and expandability options
Cons:- Higher cost than portable options
- Less flexible in terms of mobility
Best for: AI developers, 3D artists, and video editors needing a high-powered, stationary workstation.
Not ideal for: Mobile professionals or users with limited space, as it is a desktop and less portable than the MacBook Pro.
- Processor:M4 Max
- CPU:16-core
- GPU:40-core
- Memory:64GB
- Storage:2TB SSD
- Form Factor:Desktop
Our verdict“Best for creative and AI professionals who prioritize raw power and expandability over portability in their workspace.”
Apple 2026 MacBook Pro Laptop with M5 Max chip, 14.2-inch Liquid Retina XDR Display, 36GB RAM, 2TB SSD, Space Black
This MacBook Pro stands out for delivering exceptional AI processing capabilities in a portable form, thanks to the M5 Max chip with 18-core CPU and 32-core GPU. Its 14.2-inch Liquid Retina XDR display offers stunning visuals essential for data visualization during machine learning workflows. Compared to the Mac Studio, this laptop sacrifices some raw power and expandability for mobility and integrated features like a 12MP camera and six speakers with Spatial Audio, making it ideal for professionals who need to train models on the go. However, the high price and weight limit its appeal for budget-conscious or ultra-light users. The extensive connectivity options, including Wi-Fi 7 and Thunderbolt 5, support seamless data transfer and external device use. This pick is perfect for machine learning practitioners who prioritize mobility without compromising on AI performance.
Pros:- Exceptional AI performance with the M5 Max chip’s neural accelerators
- Bright, high-contrast Liquid Retina XDR display for visual data analysis
- Ample 36GB unified memory and fast 2TB SSD for demanding tasks
- Advanced connectivity including Wi-Fi 7 and Thunderbolt 5
Cons:- High price may be prohibitive for some users
- Relatively heavy and less portable than smaller laptops
- Limited upgrade options after purchase
Best for: AI researchers and data scientists needing portable yet powerful hardware for ML workflows
Not ideal for: Budget users or those seeking maximum raw computational power at a lower cost or with expandable hardware
- Processor:M5 Max chip with 18-core CPU and 32-core GPU
- Display:14.2-inch Liquid Retina XDR
- Memory:36GB Unified Memory
- Storage:2TB SSD
- Battery Life:All-day
- Connectivity:Wi-Fi 7, Thunderbolt 5, HDMI, SDXC, MagSafe 3
Our verdict“This MacBook Pro is ideal for mobile machine learning workflows where high AI performance and stunning visuals matter most.”
Apple 2020 Mac Mini with M1 Chip, 8GB RAM, 256GB SSD – Silver (Renewed)
This Mac Mini offers a compelling entry into machine learning with the M1 chip’s integrated neural engine providing significant improvements over previous Intel-based models. Its compact design makes it suitable for setups with limited space, and the 8GB RAM and 256GB SSD handle moderate ML workloads effectively. Compared with the newer M4 Pro Mac mini, it misses out on some processing and memory bandwidth enhancements, but it offers excellent value for users starting out or with lightweight ML tasks. The lack of dedicated graphics means it won’t handle large datasets or complex models as efficiently. Its limited storage and upgrade options further narrow its appeal for future-proofing. This model suits hobbyists or small teams working on less demanding ML projects on a budget.
Pros:- Strong performance improvements with the M1 chip’s neural engine
- Compact, space-saving design
- Good value for entry-level ML tasks
- Efficient power consumption
Cons:- Limited storage capacity for larger datasets
- No dedicated GPU, constraining complex ML workloads
- Renewed product may have reduced longevity
Best for: Beginners or small teams exploring machine learning with moderate data and workload demands
Not ideal for: Power users or professionals requiring extensive datasets, high model complexity, or future scalability
- Processor:Apple M1 Chip
- RAM:8GB
- Storage:256GB SSD
- Color:Silver
- Model Year:2020
- Renewed:Yes
Our verdict“This Mac Mini provides a budget-friendly platform for entry-level ML work, but falls short for heavy-duty tasks.”
Mac mini with M4 Pro Chip, 10-core CPU & GPU, 24GB Memory, 1TB Storage
This Mac mini features a powerful M4 Pro chip with 10-core CPU and GPU, offering substantial performance for machine learning tasks. Its compact 5×5 inch footprint makes it a strong choice for dedicated ML workstations in tight spaces. The 24GB of memory and 1TB SSD enable handling larger datasets and models comfortably. Compared to the M1-based Mini, this model delivers noticeable speed boosts, especially in GPU-accelerated ML processes. Its multiple ports, including Thunderbolt, HDMI, and USB-C, support extensive peripherals and data transfer needs. However, the high price and limited upgradeability may deter some users. The absence of a dedicated GPU means it’s best suited for mid-level ML projects rather than heavy, large-scale training. This pick is ideal for professionals needing a small but capable ML machine in a fixed location.
Pros:- Compact design fits small spaces
- Powerful M4 Pro chip with 10-core CPU and GPU
- Generous 24GB RAM and 1TB SSD for demanding workflows
- Multiple connectivity options including Thunderbolt and HDMI
Cons:- High cost relative to entry-level models
- Limited upgrade options due to size
- No dedicated graphics card for large-scale ML training
Best for: Mid-level ML practitioners who need a compact but potent machine for consistent, on-site training
Not ideal for: Users seeking upgradeable systems or those working with very large datasets requiring dedicated GPUs
- Processor:M4 Pro chip, 10-core CPU and GPU
- Memory:24GB
- Storage:1TB SSD
- Dimensions:5 x 5 inches
- Connectivity:Thunderbolt, HDMI, USB-C, Ethernet
- Ports:Multiple including Thunderbolt and HDMI
Our verdict“This Mac mini offers a robust, space-efficient platform for mid-tier ML tasks but isn’t suited for the most demanding projects.”
Apple 2026 Mac mini Desktop Computer M5 Pro chip
The 2026 Mac mini with M5 Pro chip takes a clear step up in processing power, especially suited for intensive AI and machine learning workloads. Its 307GB/s memory bandwidth and support for up to three external displays make it a flexible choice for dedicated ML environments. Compared to the M4 Pro Mini, this model surpasses in raw performance and data throughput, ideal for training larger models or running multiple tasks simultaneously. Its extensive port selection—including three Thunderbolt 5 ports and 2.5Gb Ethernet—supports a range of peripherals and high-speed data transfer. However, it requires external peripherals like monitors and input devices, which are not included, and its fixed hardware limits future upgrades. This Mac mini is best for professionals who prioritize maximum performance in a small, fixed location.
Pros:- Exceptional performance with M5 Pro chip and 307GB/s bandwidth
- Supports up to three external displays
- Extensive port selection including Thunderbolt 5 and 2.5Gb Ethernet
- Compact size fits into tight workspaces
Cons:- Requires external peripherals (monitor, keyboard, mouse)
- Not upgradeable post-purchase
- Higher price point for advanced features
Best for: AI developers and research labs needing a compact, high-performance dedicated ML engine
Not ideal for: Casual users or those desiring upgradeable or all-in-one solutions
- Dimensions:5 x 5 x 1.97 inches
- Weight:1.61 pounds
- Processor:M5 Pro
- Memory Bandwidth:307GB/s
- Ports:3x Thunderbolt 5, HDMI, 2.5Gb Ethernet, USB-C, headphone
- Display Support:Up to 3 external displays
Our verdict“This Mac mini is perfect for dedicated AI and ML workflows that demand maximum on-device performance in a small form factor.”
Apple 2026 MacBook Pro 16.2″ Laptop with M5 Max Chip (18-Core CPU, 40-Core GPU), 48GB Unified Memory, 2TB SSD – Space Black
This 16.2-inch MacBook Pro with the M5 Max chip offers unparalleled speed, with an 18-core CPU and 40-core GPU that excel at training large models on the go. Its stunning Liquid Retina XDR display, with 1600 nits peak brightness, allows for detailed data visualization and model tuning. Compared to the 14-inch model, this variant provides more screen real estate and processing power, making it ideal for intensive ML tasks combined with creative workflows. The 48GB of unified memory and 2TB SSD support complex datasets and rapid model iteration. While its weight at 4.73 pounds limits portability somewhat, it remains a top choice for professionals who need a mobile workstation with desktop-class power. The premium price reflects its high-end capabilities, making it suitable for demanding ML developers with a budget.
Pros:- Extreme processing power with 18-core CPU and 40-core GPU
- Large, bright Liquid Retina XDR display for detailed visualizations
- High 48GB RAM and 2TB SSD for handling complex datasets
- Versatile connectivity supporting multiple external displays
Cons:- Premium price point limits accessibility
- Heavy for a laptop, reducing portability
- Limited internal upgrade options
Best for: Data scientists and ML engineers requiring a portable powerhouse for large-scale model training and visualization
Not ideal for: Casual users or those prioritizing ultra-light laptops for simple ML tasks
- Processor:M5 Max (18-core CPU, 40-core GPU)
- Display:16.2-inch Liquid Retina XDR
- Memory:48GB Unified Memory
- Storage:2TB SSD
- Weight:4.73 pounds
- Ports:3x Thunderbolt 5, HDMI, SDXC, MagSafe 3
Our verdict“This MacBook Pro is tailored for ML professionals who need mobile yet desktop-like performance for demanding tasks.”
How We Picked
I evaluated these products based on their processing power, specifically focusing on the CPU and GPU configurations relevant to machine learning workloads. Memory capacity and storage speed were also key, as large datasets and fast data access are essential in ML. Build quality, expandability, and compatibility with ML frameworks like TensorFlow or PyTorch influenced the rankings. Cost was considered alongside performance to identify options that provide the best value for different user needs. Lastly, I looked at the overall ecosystem and future-proofing to ensure these Macs can handle upcoming ML demands.Factors to Consider When Choosing Mac Studio For Machine Learning
Choosing the right Mac Studio for machine learning involves understanding several key factors. Performance is the most obvious, but it must be balanced with budget, expandability, and compatibility with your existing tools. Since ML tasks can be demanding, focusing on the CPU, GPU, and memory capacity ensures smoother workflows. Additionally, considering future-proofing — like supporting newer ML frameworks or larger datasets — can save money down the line. Below are the main factors to keep in mind when making your decision.Performance and Hardware Power
The core of your decision revolves around processing power, especially the CPU and GPU. Higher-core configurations, like the M3 Ultra, can handle complex models and large datasets more efficiently. If your ML work involves training deep neural networks or running large simulations, investing in the most powerful hardware makes sense. However, for lighter tasks, a mid-range option like the M4 Max can offer a good balance without overspending. Overestimating your needs can lead to unnecessary costs, so align your choice with your workload size and complexity.
Memory and Storage Capacity
ML tasks are memory-intensive, so opting for models with at least 32GB of RAM is advisable, with 64GB or more being ideal for handling large datasets comfortably. Storage speed also matters; SSDs provide faster data access, reducing training and inference times. Consider your dataset size and whether you plan to expand storage later. Investing in higher memory and faster SSDs can significantly improve productivity, but they often come with higher upfront costs. Choose configurations that match your current needs while leaving room for growth.
Compatibility and Ecosystem Support
Not all Mac hardware supports every ML framework equally well. Ensuring your chosen model is compatible with popular tools like TensorFlow, PyTorch, and Core ML is essential. Apple Silicon Macs have made significant progress, but some older models may lack full support for the latest ML libraries. Additionally, check the availability of necessary ports and expandability options, especially if you plan to connect external GPU enclosures or other peripherals that can boost performance. Compatibility issues can bottleneck your workflow if overlooked.
Budget and Future-Proofing
While high-end Macs offer the best performance, they also come with a hefty price tag. Balancing your current budget with future needs is key. Investing in a slightly more powerful model now can pay off by extending the lifespan of your machine and reducing the need for upgrades. Conversely, if your ML tasks are light or infrequent, a more affordable model may suffice. Consider your long-term plans and whether your workload might grow, justifying a higher initial investment.
Portability vs. Power
If mobility is a priority, a MacBook Pro with high specs might be more suitable, although they typically have less expandability than desktops. For stationary ML work, a Mac Studio offers superior performance, better cooling, and more connectivity options. Weigh the importance of being able to take your work on the go against the need for maximum processing power at your desk. Also, consider how much external hardware or expansion you might require — desktops generally allow easier upgrades.
Frequently Asked Questions
Can a Mac Studio handle large-scale machine learning training?
Yes, especially the models equipped with M3 Ultra or M4 Max chips, which offer high-core CPUs and GPUs designed for demanding tasks. These Macs can train complex neural networks and process large datasets efficiently. However, for extremely large models or enterprise-level workloads, dedicated hardware like GPU clusters or cloud-based solutions might still be necessary. Mac Studios excel at handling intensive ML work up to a certain scale, making them a solid choice for most professional needs.
Is 64GB of RAM enough for most machine learning projects on a Mac?
For many machine learning applications, 64GB of RAM provides ample headroom to handle sizable datasets and multitasking. It allows smoother training and inference, especially when working with large models or multiple frameworks simultaneously. If your projects involve very large data or complex models, upgrading to 128GB could be beneficial, but for typical professional workflows, 64GB strikes a good balance between performance and cost. Always consider your current needs and future plans when choosing memory capacity.
Should I prioritize GPU or CPU when choosing a Mac for ML?
Both components are important, but the GPU often has a more immediate impact on training deep learning models, especially with frameworks optimized for GPU acceleration like TensorFlow. The M3 Ultra and M4 Max chips feature powerful GPU cores that significantly cut training times. However, a robust CPU ensures data preprocessing, model compilation, and overall system responsiveness. For best results, pick a configuration with a high-core GPU complemented by a capable CPU, aligning with your specific ML workloads.
How future-proof are Mac Studios for upcoming ML advancements?
Mac Studios with the latest M3 Ultra and M4 Max chips are designed to support future updates in ML frameworks and larger datasets. Apple Silicon’s architecture is evolving rapidly, and these models are built with scalability in mind. While they may not match the raw power of dedicated GPU servers, they provide a solid platform for ongoing development and experimentation. Investing in higher memory and storage capacity now can help extend their usefulness as ML demands increase.
Is it better to buy a Mac mini or a Mac Studio for ML work?
The Mac Studio offers significantly higher performance, better cooling, and more connectivity options, making it the preferred choice for intensive ML workloads. The Mac mini is more affordable and suitable for entry-level or light ML tasks, but it may struggle with larger datasets or complex models. If budget allows and your workload is demanding, the Mac Studio provides better long-term value and scalability. For beginners or less intensive projects, the Mac mini can suffice without the higher investment.
Conclusion
For users seeking maximum power and scalability, the Mac Studio with M3 Ultra remains the best overall pick, ideal for professional ML developers and researchers. Those on a tighter budget but still needing strong performance should consider the Mac Studio with M4 Max, which offers excellent value. Beginners or light ML practitioners will find the Mac mini with M4 Pro sufficiently capable and more affordable. Finally, for those prioritizing portability without sacrificing too much power, a high-spec MacBook Pro provides a flexible solution. Tailor your choice to your workload, budget, and future growth plans to make the smartest investment.
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