gh-k-dense-ai-claude-scientific-skills-scientific-skills/skills/modal/references/resources.md

CPU, Memory, and Disk Resources

Default Resources

Each Modal container has default reservations:

• CPU: 0.125 cores
• Memory: 128 MiB

Containers can exceed minimum if worker has available resources.

CPU Cores

Request CPU cores as floating-point number:

@app.function(cpu=8.0)
def my_function():
    # Guaranteed access to at least 8 physical cores
    ...

Values correspond to physical cores, not vCPUs.

Modal sets multi-threading environment variables based on CPU reservation:

• OPENBLAS_NUM_THREADS
• OMP_NUM_THREADS
• MKL_NUM_THREADS

Memory

Request memory in megabytes (integer):

@app.function(memory=32768)
def my_function():
    # Guaranteed access to at least 32 GiB RAM
    ...

Resource Limits

CPU Limits

Default soft CPU limit: request + 16 cores

• Default request: 0.125 cores → default limit: 16.125 cores
• Above limit, host throttles CPU usage

Set explicit CPU limit:

cpu_request = 1.0
cpu_limit = 4.0

@app.function(cpu=(cpu_request, cpu_limit))
def f():
    ...

Memory Limits

Set hard memory limit to OOM kill containers at threshold:

mem_request = 1024  # MB
mem_limit = 2048    # MB

@app.function(memory=(mem_request, mem_limit))
def f():
    # Container killed if exceeds 2048 MB
    ...

Useful for catching memory leaks early.

Disk Limits

Running containers have access to many GBs of SSD disk, limited by:

1. Underlying worker's SSD capacity
2. Per-container disk quota (100s of GBs)

Hitting limits causes OSError on disk writes.

Request larger disk with ephemeral_disk:

@app.function(ephemeral_disk=10240)  # 10 GiB
def process_large_files():
    ...

Maximum disk size: 3.0 TiB (3,145,728 MiB) Intended use: dataset processing

Billing

Charged based on whichever is higher: reservation or actual usage.

Disk requests increase memory request at 20:1 ratio:

• Requesting 500 GiB disk → increases memory request to 25 GiB (if not already higher)

Maximum Requests

Modal enforces maximums at Function creation time. Requests exceeding maximum will be rejected with InvalidError.

Contact support if you need higher limits.

Example: Resource Configuration

@app.function(
    cpu=4.0,              # 4 physical cores
    memory=16384,         # 16 GiB RAM
    ephemeral_disk=51200, # 50 GiB disk
    timeout=3600,         # 1 hour timeout
)
def process_data():
    # Heavy processing with large files
    ...

Monitoring Resource Usage

View resource usage in Modal dashboard:

• CPU utilization
• Memory usage
• Disk usage
• GPU metrics (if applicable)

Access via https://modal.com/apps