$ python -m mlx_lm.server --port 8080
model loaded: quantized/model-4bit
listening on 0.0.0.0:8080
POST /v1/chat/completions 200
Keep Apple Silicon in the cloud
Keep AI inference, iOS and macOS builds, and automation running continuously. Every order includes one dedicated physical Mac mini—not a virtual machine—from $19.2/day.
Keep compute on the node, with access for the whole team
Dedicated Apple Silicon, memory, and toolchains stay online continuously, so model validation and build records continue even when a personal computer sleeps or a team member is offline.
A consistent environment—collaboration without passing around computers
Developers connect to the same always-on physical Mac via SSH or VNC to view build logs, model processes, and project files.
Dedicated, continuous, and controllable
Confirm the machine type, operating model, and access boundaries before deciding whether it fits your team’s existing workflow.
Dedicated physical Mac mini
Every order maps to an independent physical node. The chip, memory, and base storage are not shared with other tenants on the same runtime instance, making it easier to keep experiments and build environments consistent.
Non-virtualized configuration
All three configurations map directly to Mac mini hardware. Plan Xcode builds, runner concurrency, or MLX model size using actual memory, storage, and chip capabilities.
Remote operation, 24/7/365
All nodes operate normally 365 days a year. Connect through SSH or VNC, and long-running tasks continue after team members go offline.
From quantized models to an MLX API
Validate the model on a fixed configuration first, then package the inference process as a remote endpoint. Model paths, memory limits, listening addresses, and request logs remain available for inspection.
Sync model files, pin Python, MLX, and project dependency versions, and record startup parameters and the working directory.
Use the same prompts to observe peak memory, first-token latency, sustained throughput, and output consistency.
Verify the listening address, port access, process supervision, and error logs instead of checking only the local command-line result.
Expand from local requests to remote application calls, while retaining records for timeouts, retries, and model switching.
- Model format
- 4-bit MLX
- Memory usage
- 42.8 / 64GB
- Listening address
- 0.0.0.0:8080
- Request status
- HTTP 200
- API endpoint
- /v1/chat/completions
Illustrative data showing metrics worth recording; it does not represent fixed performance for a specific model or configuration. Actual results depend on the model, quantization method, context length, and concurrency settings.
Review the hardware, then choose a rental term
Starting at $19.2/day. All three plans are available by day, week, month, or quarter, and every order is billed in US dollars (USD).
VMKeep M4 Core
M4
16GB RAM
256GB SSD
$51.7 / week · $95.8 / month · $260.6 / quarter
Ideal for lightweight Xcode builds, automation scripts, small runners, and MLX environment validation. For larger dependency caches or continuous workloads, compare the mid-tier configuration first.
VMKeep M4 Plus
M4
24GB RAM
512GB SSD
$106.3 / week · $196.9 / month · $535.6 / quarter
Designed for continuous CI, larger dependency caches, React Native builds, and mid-size MLX model validation—balancing capacity with long-term running costs.
VMKeep M4 Pro
M4 Pro
64GB RAM
2TB SSD
$164.1 / week · $303.8 / month · $826.3 / quarter
Built for high-memory MLX inference, larger model evaluations, multi-task builds, and workflows that need local storage for many models or build artifacts.
Choose the location closest to your team or calling service across 5 nodes
All three configurations are available in Singapore, Japan (Tokyo), South Korea (Seoul), Hong Kong, and US East. Combinations listed in the catalog are generally orderable; live availability is returned by the console.
Latency ranges are provided to help with initial region selection. Actual routes vary with access location, network provider, and current routing. Test from your team’s network before production access.
The console centrally displays machines, rental terms, orders, and management actions. Connection methods and first-access checks are available on the usage support page.
View connection and migration guideAssess fit by inputs, execution, and outputs
Cloud Mac provides an always-on Apple Silicon environment with remote access. Actual workload performance still depends on code size, model parameters, dependency structure, and the selected configuration.
iOS / macOS builds
Organize code, dependencies, the Xcode toolchain, and signing materials in fixed directories, then run tests, archives, and pre-release checks.
- Input
- Code, dependencies, and signing configuration
- Execution
- xcodebuild and automation scripts
- Output
- Test reports, logs, and archive packages
Self-hosted runner
Assign repository jobs to a dedicated physical node and plan working directories, dependency caches, concurrency limits, and retry order for failed jobs.
- Input
- Repository events and pipeline jobs
- Execution
- Persistent runner and cache directories
- Output
- Execution logs, test results, and artifacts
MLX inference experiments
With fixed chip and memory conditions, compare model quantization versions, peak memory, first-token latency, and sustained throughput before packaging a remote API.
- Input
- Models, prompts, and inference parameters
- Execution
- MLX server and evaluation scripts
- Output
- API, metrics, and model findings
Remote graphical workstation
Use SSH for command-line tasks and VNC for the macOS graphical interface—ideal for short-term projects, cross-region collaboration, and temporary capacity expansion.
- Input
- Project files, toolchains, and assets
- Execution
- Remote access through SSH or VNC
- Output
- Project files, build results, and records
Clear terms, settled in US dollars
When ordering, confirm the machine type, node, rental term, and add-ons in sequence. Actual payment gateway availability is returned by the console.
Rent by day, week, month, or quarter
Start short-term validation by day or week; for continuous CI, long-running inference services, and a fixed remote work environment, compare monthly and quarterly plans. Before renewal, verify the current configuration, node, cycle, and data migration arrangements.
Only two payment methods supported
Every order is billed in US dollars (USD), with no conversion to other currencies.
Choose a configuration based on model memory, build cache, and concurrent workloads; choose a node based on your team and calling-service locations; and confirm plans for data export, token revocation, and key removal before the rental ends.
Confirm the machine type, region, and payment scope first
These answers cover the most common decisions. See the FAQ for more complete configuration, connection, and billing details.
Does VMKeep provide virtual machines?
No. Every order includes one dedicated physical Mac mini. The listed configuration corresponds to specific Apple Silicon, memory, and storage specifications, with no shared runtime instance between tenants.
Can I run an MLX inference server?
Yes. Validate the model from the command line, start a listening service, and connect applications through an API. Compatibility, memory requirements, first-token latency, and throughput depend on the model, quantization parameters, and selected configuration.
Which regions are available?
Available regions are Singapore, Japan (Tokyo), South Korea (Seoul), Hong Kong, and US East—5 nodes or data centers in total. All three configurations are available across all 5 nodes.
Which payment methods are supported?
Only USDT-TRC20 and Visa / Mastercard / Amex (via Stripe) are supported. All charges are settled in US dollars (USD). Actual gateway availability is returned by the console.
Choose an always-on Cloud Mac
Choose from three dedicated Apple Silicon configurations, then confirm a Singapore, Tokyo, Seoul, Hong Kong, or US East node and your rental term.