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GET
/
user
/
models
Get Model Breakdown
curl --request GET \
  --url https://api.electronhub.ai/v1/user/models \
  --header 'Authorization: Bearer <token>'
{
  "total_consumption": 12.847,
  "models": {
    "gpt-4o": {
      "requests": 342,
      "input_tokens": 128450,
      "output_tokens": 67230,
      "total_cost": 4.215,
      "owned_by": "openai"
    },
    "claude-sonnet-4-20250514": {
      "requests": 156,
      "input_tokens": 89200,
      "output_tokens": 45100,
      "total_cost": 3.628,
      "owned_by": "anthropic"
    }
  },
  "last_updated": "2026-03-02T15:30:00Z"
}

Documentation Index

Fetch the complete documentation index at: https://docs.electronhub.ai/llms.txt

Use this file to discover all available pages before exploring further.

Retrieve a per-model cost and usage breakdown for the authenticated user. This endpoint provides detailed consumption statistics for every model you’ve used, including request counts, token usage, and total cost.

​
Response

Returns an object containing:
  • total_consumption — Your total API spend across all models
  • models — A map of model IDs to their usage statistics
  • last_updated — ISO timestamp of the last usage update

​
Model Fields

Each model entry in the models object contains:
  • requests — Total number of requests made to this model
  • input_tokens — Total input tokens consumed
  • output_tokens — Total output tokens generated
  • total_cost — Total cost in credits for this model
  • owned_by — The provider/owner of the model (e.g. openai, anthropic, google, deepseek)

​
Example Response

{
  "total_consumption": 12.847,
  "models": {
    "gpt-4o": {
      "requests": 342,
      "input_tokens": 128450,
      "output_tokens": 67230,
      "total_cost": 4.215,
      "owned_by": "openai"
    },
    "claude-sonnet-4-20250514": {
      "requests": 156,
      "input_tokens": 89200,
      "output_tokens": 45100,
      "total_cost": 3.628,
      "owned_by": "anthropic"
    },
    "gemini-2.5-pro-preview-05-06": {
      "requests": 89,
      "input_tokens": 52300,
      "output_tokens": 31200,
      "total_cost": 2.104,
      "owned_by": "google"
    },
    "dall-e-3": {
      "requests": 15,
      "input_tokens": 0,
      "output_tokens": 0,
      "total_cost": 1.500,
      "owned_by": "openai"
    },
    "deepseek-chat": {
      "requests": 210,
      "input_tokens": 95400,
      "output_tokens": 48700,
      "total_cost": 1.400,
      "owned_by": "deepseek"
    }
  },
  "last_updated": "2026-03-02T15:30:00Z"
}

​
Code Examples

from httpx import Client

api_key = "ek-your-api-key"
headers = {
    "Authorization": f"Bearer {api_key}"
}

client = Client()
response = client.get("https://api.electronhub.ai/user/models", headers=headers)
data = response.json()

print(f"Total spend: ${data['total_consumption']:.2f}")
for model, stats in sorted(data['models'].items(), key=lambda x: x[1]['total_cost'], reverse=True):
    print(f"  {model}: ${stats['total_cost']:.3f} ({stats['requests']} requests)")

​
Use Cases

  • Cost Analysis — Identify which models consume the most credits
  • Usage Optimization — Find underused or overused models to optimize spending
  • Provider Breakdown — See spending distribution across providers (OpenAI, Anthropic, Google, etc.)
  • Budget Planning — Track per-model costs to forecast weekly credit consumption
  • Model Comparison — Compare token efficiency across different models

Authorizations

​
Authorization
string
header
required

Enter your API key (starts with 'ek-')

Response

200 - application/json

Success

​
total_consumption
number
required

Total API spend across all models (in credits/USD)

Example:

12.847

​
models
object
required

Map of model IDs to their usage statistics

Example:
{
  "gpt-4o": {
    "requests": 342,
    "input_tokens": 128450,
    "output_tokens": 67230,
    "total_cost": 4.215,
    "owned_by": "openai"
  },
  "claude-sonnet-4-20250514": {
    "requests": 156,
    "input_tokens": 89200,
    "output_tokens": 45100,
    "total_cost": 3.628,
    "owned_by": "anthropic"
  }
}
​
last_updated
string<date-time> | null

ISO timestamp of the last usage update

Example:

"2026-03-02T15:30:00Z"