API Documentation

An OpenAI-compatible chat completion LLM API to easily integrate AI into your applications.

Quick Start

All mammouth subscribers have some credits included.

Plan	Starter	Standard	Expert
Monthly credits	2$	4$	10$

➡️ Get your API key.

With the Mammouth API directly

Generates a chat completion response based on your prompt.

PythonJavaScriptcURL

import requests
url = "https://api.mammouth.ai/v1/chat/completions"
headers = {
    "Authorization": "Bearer YOUR_API_KEY",
    "Content-Type": "application/json"
}
data = {
    "model": "gpt-4.1",
    "messages": [
        {
            "role": "user",
            "content": "Explain the basics of machine learning"
        }
    ]
}
response = requests.post(url, headers=headers, json=data)
print(response.json())

const fetch = require("node-fetch");

async function callMammouth() {
  const url = "https://api.mammouth.ai/v1/chat/completions";
  const headers = {
    Authorization: "Bearer YOUR_API_KEY",
    "Content-Type": "application/json",
  };

  const data = {
    model: "gpt-4.1",
    messages: [
      {
        role: "user",
        content: "Create an example JavaScript function",
      },
    ],
  };

  try {
    const response = await fetch(url, {
      method: "POST",
      headers: headers,
      body: JSON.stringify(data),
    });

    const result = await response.json();
    console.log(result.choices[0].message.content);
  } catch (error) {
    console.error("Error:", error);
  }
}

callMammouth();

curl -X POST https://api.mammouth.ai/v1/chat/completions \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "gpt-4.1",
    "messages": [
      {
        "role": "user",
        "content": "Hello, how are you doing?"
      }
    ]
  }'

➡️ Get your API key in your settings.

With OpenAI Library

import openai

# Configure the client to use Mammouth.ai
openai.api_base = "https://api.mammouth.ai/v1"
openai.api_key = "YOUR_API_KEY"

response = openai.ChatCompletion.create(
    model="gpt-4.1",
    messages=[
        {"role": "user", "content": "What are the benefits of renewable energy?"}
    ]
)

print(response.choices[0].message.content)

Response Format

Successful Response

{
  "id": "chatcmpl-123",
  "object": "chat.completion",
  "created": 1677652288,
  "model": "gpt-4.1",
  "choices": [
    {
      "index": 0,
      "message": {
        "role": "assistant",
        "content": "Hello! I'm doing very well, thank you for asking. How can I help you today?"
      },
      "finish_reason": "stop"
    }
  ],
  "usage": {
    "prompt_tokens": 12,
    "completion_tokens": 19,
    "total_tokens": 31
  }
}

Streaming Response

When stream: true is set, responses are returned as Server-Sent Events:

data: {"id":"chatcmpl-123","object":"chat.completion.chunk","created":1677652288,"model":"gpt-4.1","choices":[{"index":0,"delta":{"content":"Hello"},"finish_reason":null}]}

data: {"id":"chatcmpl-123","object":"chat.completion.chunk","created":1677652288,"model":"gpt-4.1","choices":[{"index":0,"delta":{"content":"!"},"finish_reason":null}]}

data: [DONE]

Models & Pricing

Model	Input ($/M tokens)	Output ($/M tokens)
gpt-4.1	2	8
gpt-4.1-mini	0.4	1.6
gpt-4.1-nano	0.1	0.4
gpt-4o	2.5	10
o4-mini	1.1	4.4
o3	2	8
mistral-large-2411	2	6
mistral-medium-3	0.4	2
mistral-small-3.2-24b-instruct	0.1	0.3
magistral-medium-2506	2	5
codestral-2501	0.3	0.9
grok-3	3	15
grok-3-mini	0.3	0.5
gemini-2.5-flash	0.3	2.5
gemini-2.5-pro	2.5	15
deepseek-r1-0528	3	8
deepseek-v3-0324	0.9	0.9
llama-4-maverick	0.22	0.88
llama-4-scout	0.15	0.6
claude-3-5-haiku-20241022	0.8	4
claude-3-7-sonnet-20250219	3	15
claude-sonnet-4-20250514	3	15
claude-opus-4-20250514	15	75

Prices may vary and not be up to date in this table.

📜 Usage and cost are logged in your settings.

💡 We added aliases aligned with the Mammouth app to facilitate your model selection: if you write mistral, it will use mistral-medium-3.

Error Codes

Code	Description
400	Bad Request - Missing or incorrect parameters
401	Unauthorized - Invalid API key
429	Too Many Requests - Rate limit exceeded
500	Internal Server Error - Server-side issue
503	Service Unavailable - Server temporarily unavailable

Error Response Format

{
  "error": {
    "message": "Invalid API key provided",
    "type": "invalid_request_error",
    "code": "invalid_api_key"
  }
}

Parameters

Required Parameters

Parameter	Type	Description
messages	array	List of messages in the conversation
model	string	Model identifier to use

Optional Parameters

Parameter	Type	Default	Description
temperature	number	0.7	Controls creativity (0.0 to 2.0)
max_tokens	integer	2048	Maximum number of tokens to generate
top_p	number	1.0	Controls response diversity
stream	boolean	false	Real-time response streaming

Optimization Tips

Temperature Settings

• 0.0 - 0.3: Very consistent and predictable responses
• 0.4 - 0.7: Balance between creativity and coherence
• 0.8 - 1.0: More creative and varied responses

Message Structure

{
  "messages": [
    {
      "role": "system",
      "content": "You are an AI assistant specialized in programming."
    },
    {
      "role": "user",
      "content": "How to optimize a for loop in Python?"
    }
  ]
}

Role Types

• system: Sets the behavior and context for the assistant
• user: Represents messages from the user
• assistant: Represents previous responses from the AI

Migration from OpenAI

If you're already using OpenAI's API, migrating to Mammouth.ai is simple:

1. Change the base URL from https://api.openai.com/v1 to https://api.mammouth.ai/v1
2. Update your API key
3. Keep all other parameters the same

OpenAI Python Library

import openai

# Before
openai.api_base = "https://api.openai.com/v1"
openai.api_key = "sk-openai-key"

# After
openai.api_base = "https://api.mammouth.ai/v1"
openai.api_key = "your-mammouth-key"

➡️ Get your API key.