> ## Documentation Index
> Fetch the complete documentation index at: https://docs.runpod.io/llms.txt
> Use this file to discover all available pages before exploring further.

# CPU types

> Available CPU instance types for Flash endpoints.

Flash provides access to CPU-only compute instances for workloads that don't require GPU acceleration. This reference lists all available CPU instance types.

## Using CPU instances

Specify a CPU instance using the `cpu` parameter. You can use either a string shorthand or the `CpuInstanceType` enum:

```python theme={"theme":{"light":"github-light","dark":"github-dark"}}
from runpod_flash import Endpoint, CpuInstanceType

# String shorthand
@Endpoint(name="data-processor", cpu="cpu5c-4-8")
async def process(data: dict) -> dict:
    ...

# Using enum
@Endpoint(name="data-processor", cpu=CpuInstanceType.CPU5C_4_8)
async def process(data: dict) -> dict:
    ...
```

## Available CPU instance types

CPU instances are organized by generation and optimization profile.

### 5th generation compute-optimized

Latest generation, optimized for compute-intensive workloads:

| CpuInstanceType | ID         | vCPU | RAM  | Best For                         |
| --------------- | ---------- | ---- | ---- | -------------------------------- |
| `CPU5C_1_2`     | cpu5c-1-2  | 1    | 2GB  | Lightweight APIs, simple tasks   |
| `CPU5C_2_4`     | cpu5c-2-4  | 2    | 4GB  | Small APIs, data validation      |
| `CPU5C_4_8`     | cpu5c-4-8  | 4    | 8GB  | General APIs, data processing    |
| `CPU5C_8_16`    | cpu5c-8-16 | 8    | 16GB | Heavy processing, parallel tasks |

### 3rd generation compute-optimized

Balanced compute focus:

| CpuInstanceType | ID         | vCPU | RAM  | Best For                  |
| --------------- | ---------- | ---- | ---- | ------------------------- |
| `CPU3C_1_2`     | cpu3c-1-2  | 1    | 2GB  | Basic endpoints, webhooks |
| `CPU3C_2_4`     | cpu3c-2-4  | 2    | 4GB  | Simple data processing    |
| `CPU3C_4_8`     | cpu3c-4-8  | 4    | 8GB  | Moderate workloads        |
| `CPU3C_8_16`    | cpu3c-8-16 | 8    | 16GB | CPU-intensive tasks       |

### 3rd generation general purpose

Balanced CPU and memory:

| CpuInstanceType | ID         | vCPU | RAM  | Best For                    |
| --------------- | ---------- | ---- | ---- | --------------------------- |
| `CPU3G_1_4`     | cpu3g-1-4  | 1    | 4GB  | Memory-light tasks          |
| `CPU3G_2_8`     | cpu3g-2-8  | 2    | 8GB  | General workloads           |
| `CPU3G_4_16`    | cpu3g-4-16 | 4    | 16GB | Memory-intensive processing |
| `CPU3G_8_32`    | cpu3g-8-32 | 8    | 32GB | High-memory workloads       |

## Common configurations

### APIs and webhooks

```python theme={"theme":{"light":"github-light","dark":"github-dark"}}
# Lightweight API
@Endpoint(name="webhook", cpu="cpu5c-2-4")
async def handle_webhook(data: dict) -> dict:
    ...

# Production API
@Endpoint(name="api", cpu="cpu5c-4-8", workers=(1, 10))
async def handle_request(data: dict) -> dict:
    ...
```

### Data processing

```python theme={"theme":{"light":"github-light","dark":"github-dark"}}
# Light processing
@Endpoint(name="processor", cpu="cpu3g-2-8")  # More RAM per vCPU
async def process(data: dict) -> dict:
    ...

# Heavy processing
@Endpoint(name="heavy-processor", cpu="cpu5c-8-16")
async def heavy_process(data: dict) -> dict:
    ...
```

### Memory-intensive tasks

```python theme={"theme":{"light":"github-light","dark":"github-dark"}}
# High memory requirement
@Endpoint(name="memory-worker", cpu="cpu3g-8-32")  # 8 vCPU, 32GB RAM
async def process_large_data(data: dict) -> dict:
    ...
```

### Load-balanced CPU API

```python theme={"theme":{"light":"github-light","dark":"github-dark"}}
from runpod_flash import Endpoint

api = Endpoint(
    name="cpu-api",
    cpu="cpu5c-4-8",
    workers=(1, 10)
)

@api.post("/process")
async def process(data: dict) -> dict:
    return {"result": "processed"}

@api.get("/health")
async def health():
    return {"status": "ok"}
```

## Container disk sizing

CPU endpoints automatically adjust container disk size based on instance limits:

* `CPU3G` and `CPU3C` instances: vCPU count × 10GB (e.g., 2 vCPU = 20GB)
* `CPU5C` instances: vCPU count × 15GB (e.g., 4 vCPU = 60GB)

If you specify a custom size via `PodTemplate` that exceeds the instance limit, deployment will fail with a validation error.