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

# Capacity

> Check budget allocations and remaining GPU hours

## Get Capacity

Retrieve capacity budget and allocation information for your organization.

```bash theme={null}
GET /v1/capacity
```

### Query Parameters

| Parameter | Type | Description |
| - | - | - |
| `initiative_id` | string | Filter to specific team |
| `pool_id` | string | Filter to specific capacity pool |

### Example Request

```bash theme={null}
curl -X GET "https://api.usechamber.io/v1/capacity" \
  -H "Authorization: Bearer <token>" \
  -H "X-Organization-Id: <org-id>"
```

### Example Response

```json theme={null}
{
  "data": {
    "organization_id": "org_abc123",
    "summary": {
      "total_allocated_gpu_hours": 10000,
      "total_used_gpu_hours": 6500,
      "total_remaining_gpu_hours": 3500,
      "current_active_gpus": 24
    },
    "pools": [
      {
        "pool_id": "pool_prod",
        "name": "Production Pool",
        "allocated_gpu_hours": 6000,
        "used_gpu_hours": 4200,
        "remaining_gpu_hours": 1800,
        "instance_types": ["p4d.24xlarge", "p5.48xlarge"]
      },
      {
        "pool_id": "pool_dev",
        "name": "Development Pool",
        "allocated_gpu_hours": 4000,
        "used_gpu_hours": 2300,
        "remaining_gpu_hours": 1700,
        "instance_types": ["g5.xlarge", "g5.2xlarge"]
      }
    ],
    "initiatives": [
      {
        "initiative_id": "init_ml_team",
        "name": "ML Platform Team",
        "allocated_gpu_hours": 5000,
        "used_gpu_hours": 3200,
        "remaining_gpu_hours": 1800
      },
      {
        "initiative_id": "init_research",
        "name": "Research Team",
        "allocated_gpu_hours": 5000,
        "used_gpu_hours": 3300,
        "remaining_gpu_hours": 1700
      }
    ]
  },
  "request_id": "req_abc123"
}
```

### Response Fields

| Field | Description |
| - | - |
| `total_allocated_gpu_hours` | Total GPU hours allocated to the organization |
| `total_used_gpu_hours` | GPU hours consumed across all workloads |
| `total_remaining_gpu_hours` | Available GPU hours remaining |
| `current_active_gpus` | Number of GPUs currently in use |
| `pools` | Breakdown by capacity pool |
| `initiatives` | Breakdown by team |


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