Don’t choose by chip name alone. Check concurrent build jobs, project dependencies, unified memory peaks, and the data that must stay on the node before choosing a rental term and node. All three configurations are dedicated physical Macs: every order gets its own Mac mini physical node, with compute, memory, and local storage not shared with other customers.
Record real peak usage in all four decision areas instead of estimating from averages.
Check whether local development, testing, archiving, and CI queues overlap.
Account for indexing, linking, dependency resolution, and persistent workspace overhead.
Xcode, simulators, browsers, and model processes all share unified memory.
Reserve space for DerivedData, dependency caches, model weights, and archives.
All prices are charged in US dollars (USD). Daily rental suits short validation tasks, weekly rental suits focused iteration, and monthly or quarterly rental is better for persistent build nodes. Before choosing a term, confirm the memory and local SSD capacity your workload requires.
| Configuration | Chip | Unified memory | Base SSD | Daily | Weekly | Monthly | Quarterly |
|---|---|---|---|---|---|---|---|
| m4-16-256 OnceMac M4 16 | M4 | 16GB | 256GB | $19.1 | $51.6 | $95.5 | $259.8 |
| m4-24-512 OnceMac M4 24 | M4 | 24GB | 512GB | $40.1 | $108.3 | $200.5 | $545.4 |
| m4pro-64-2tb OnceMac M4 Pro 64 | M4 Pro | 64GB | 2TB | $59.7 | $161.1 | $298.4 | $811.6 |
All three configurations are available in Singapore, Japan (Tokyo), South Korea (Seoul), Hong Kong, the US East Coast, and the US West Coast. Availability is reported in real time by the console. Choose the node closest to your code repository, team, and target test users.
These recommendations are not a substitute for measuring your application; they provide an actionable starting point. Choose a plan that covers your current peak. Upgrade when memory pressure, cache usage, or concurrent queues consistently approach the limit.
Best for solo remote development, small iOS projects, command-line testing, short-term release validation, and workloads with one primary build job at a time.
Best for medium-sized multi-module projects, continuously running self-hosted runners, and development environments using Xcode, simulators, browsers, and auxiliary tools at the same time.
Best for large workspaces, highly concurrent builds, larger MLX model inference, data preprocessing, and workloads that keep models and development tools running together over time.
Fixed compile times cannot be compared across projects: dependency versions, warm or cold caches, signing steps, test scope, network downloads, and concurrency settings all affect results. A more reliable approach is to record peak CPU, memory, cache, and queue usage across a complete pipeline run.
Checkpoints and recommended starting points for three project types
First verify that clean builds, incremental builds, unit tests, and archives complete reliably in the same environment.
M4, 16GB unified memory, and a 256GB SSD provide a practical baseline for repeatable testing.
Indexing, dependency resolution, testing, and archiving are more likely to overlap. Monitor memory pressure and cache growth instead of checking only whether one build finishes.
M4, 24GB unified memory, and a 512GB SSD leave more practical headroom for multitasking development.
Measure builds, tests, archives, log processing, and other persistent tasks as one workload, while reserving capacity for burst queues.
M4 Pro, 64GB unified memory, and a 2TB SSD are better suited to high concurrency and large local datasets.
MLX can use Apple Silicon unified memory directly, but available capacity must also cover macOS, Python environments, the model runtime, context caches, data preprocessing, and other development tools. Choose a configuration based on the stable peak after the model loads, not just the model file size.
Quantization, context length, batch size, model architecture, and concurrent requests all affect memory usage and inference performance. The same model may need very different headroom under different parameters, so we do not promise a fixed speed or a fixed list of runnable models.
Suitable for installing MLX, validating scripts, checking dependencies, and running experiments with lower memory requirements. If the model runs alongside Xcode or other tools, measure actual pressure first.
Provides more room for preprocessing, development environments, and inference with moderate memory needs. Re-test based on model quantization and context settings.
Best for larger resident models, highly concurrent builds, or inference running alongside development tools. It does not mean every model will run with every parameter set.
Base SSD capacity is fixed by configuration: OnceMac M4 16 includes 256GB; OnceMac M4 24 includes 512GB; and OnceMac M4 Pro 64 includes 2TB. Expansion fees are added to the selected configuration and rental term, making them suitable for workloads that retain more build caches, archives, test assets, or model weights.
| Storage option | Best for | Daily | Weekly | Monthly | Quarterly |
|---|---|---|---|---|---|
| Base SSD | Included in the selected configuration price: 256GB, 512GB, or 2TB | Included | Included | Included | Included |
| +1TB SSD | For additional dependency caches, archives, assets, and medium-sized models | $2.1 | $5.8 | $10.7 | $29.1 |
| +2TB SSD | For larger datasets, long-term build caches, and retaining artifacts from multiple versions | $4.2 | $11.6 | $21.4 | $58.2 |
Beyond the Git workspace, include package-manager caches, binary dependencies, multiple branch copies, and temporary export directories.
Multiple Xcode versions, Schemes, test artifacts, and archives continue to grow. Establish cleanup rules instead of relying on manual space management.
Model file size does not represent runtime memory, but it directly uses SSD space. Download caches and converted copies must also be counted separately.
A complete choice combines the chip, unified memory, SSD, node, and rental term. If several team members will use the machine, have the engineers running the builds or experiments confirm peak usage first instead of choosing by procurement label alone.
Start with M4 for light and everyday development; prioritize M4 Pro for large workspaces, highly concurrent workloads, or high-memory experiments.
Record the peak while Xcode, simulators, browsers, runners, or models run together, then choose 16GB, 24GB, or 64GB.
Add up source, dependencies, DerivedData, archives, logs, models, and datasets, then decide whether the base SSD needs an additional 1TB or 2TB.
Choose among Singapore, Japan (Tokyo), South Korea (Seoul), Hong Kong, the US East Coast, and the US West Coast based on proximity to your team, repository, or test users.
Choose daily or weekly for short-term validation; consider monthly or quarterly for ongoing development, CI/CD, and long-running experiments. All amounts are charged in US dollars.
Only USDT-TRC20 and Visa / Mastercard / Amex (via Stripe) are supported. All charges are in US dollars (USD). Available payment gateways and configuration availability are reported in real time by the console.
Choose the chip, memory, and storage from three dedicated physical Mac configurations, then select one of six nodes and a daily, weekly, monthly, or quarterly term. For specialized workloads, send the team your concurrency, peak memory, and data volume first.