GPT-4.1 via x402 Gateway (Balanced Tier)

x402

GPT-4.1 via x402 Gateway (Balanced Tier) is a paid API for AI agents from x402-gateway-production.up.railway.app, paid per call via x402, $0.035/call, status unknown (last checked 2026-09-15, last successful call 2026-05-08).

Calls OpenAI's GPT-4.1 model for general-purpose text generation and reasoning via a pay-per-call x402-enabled gateway

Price / call$0.035

Seller volume →—

Success100%

StatusUnknown

How this service works

OpenAI's efficient flagship model — strong all-around performance at lower cost than GPT-5.2

Output

Returns the model's generated text content along with token usage breakdown (prompt tokens, completion tokens, total), upstream inference cost in USD, and the model identifier (e.g. openai/gpt-4.1-20251113).

Example use cases

Example prompt

“Use GPT-4.1 to write me a one-paragraph explanation of how transformer neural networks work — I want it clear enough for a non-technical audience.”

Technical details

Endpoint

POSThttps://x402-gateway-production.up.railway.app/api/llm/gpt-5.1

When to prefer

Choose this endpoint when you need strong all-around language model performance (reasoning, summarization, drafting, Q&A) at a moderate cost point — better than the cheapest GPT-5 nano tier but less expensive than GPT-5.2. Ideal for medium-complexity tasks where quality matters but cost per call should stay low. Use when you want pay-per-call x402 billing without managing OpenAI API keys.

Side effects

Invalid or missing messages array returns 400 bad request
Insufficient USDC payment returns 402 Payment Required
Rate limiting or upstream OpenAI outage returns 503
Malformed role values in messages cause validation errors
Very long prompts may exceed model context window and return an error

Input

{
  "messages": [
    {
      "role": "user",
      "content": "Explain the concept of machine learning in one paragraph."
    }
  ]
}

Output

{
  "model": "openai/gpt-5.1-20251113",
  "usage": {
    "cost": 0.00141,
    "is_byok": false,
    "cost_details": {
      "upstream_inference_cost": 0.00141,
      "upstream_inference_prompt_cost": 0.00002,
      "upstream_inference_completions_cost": 0.00139
    },
    "total_tokens": 155,
    "prompt_tokens": 16,
    "completion_tokens": 139,
    "prompt_tokens_details": {
      "audio_tokens": 0,
      "video_tokens": 0,
      "cached_tokens": 0,
      "cache_write_tokens": 0
    },
    "completion_tokens_details": {
      "audio_tokens": 0,
      "image_tokens": 0,
      "reasoning_tokens": 0
    }
  },
  "content": "Machine learning is a branch of artificial intelligence where computers learn patterns from data instead of being explicitly programmed with step‑by‑step rules. You feed a model examples—such as images, text, or numerical records—along with the correct answers or outcomes (for supervised learning) or let it find structure on its own (for unsupervised learning). The system adjusts internal parameters to minimize errors, so over time it becomes better at tasks like predicting house prices, recognizing faces, translating languages, or recommending products. Rather than following fixed instructions, a machine learning system generalizes from past data to make informed predictions or decisions on new, unseen data."
}

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How this service works

OpenAI's efficient flagship model — strong all-around performance at lower cost than GPT-5.2

Output

Technical details

Endpoint

POSThttps://x402-gateway-production.up.railway.app/api/llm/gpt-5.1

When to prefer

Side effects

Invalid or missing messages array returns 400 bad request
Insufficient USDC payment returns 402 Payment Required
Rate limiting or upstream OpenAI outage returns 503
Malformed role values in messages cause validation errors
Very long prompts may exceed model context window and return an error

Input

{
  "messages": [
    {
      "role": "user",
      "content": "Explain the concept of machine learning in one paragraph."
    }
  ]
}

Output

{
  "model": "openai/gpt-5.1-20251113",
  "usage": {
    "cost": 0.00141,
    "is_byok": false,
    "cost_details": {
      "upstream_inference_cost": 0.00141,
      "upstream_inference_prompt_cost": 0.00002,
      "upstream_inference_completions_cost": 0.00139
    },
    "total_tokens": 155,
    "prompt_tokens": 16,
    "completion_tokens": 139,
    "prompt_tokens_details": {
      "audio_tokens": 0,
      "video_tokens": 0,
      "cached_tokens": 0,
      "cache_write_tokens": 0
    },
    "completion_tokens_details": {
      "audio_tokens": 0,
      "image_tokens": 0,
      "reasoning_tokens": 0
    }
  },
  "content": "Machine learning is a branch of artificial intelligence where computers learn patterns from data instead of being explicitly programmed with step‑by‑step rules. You feed a model examples—such as images, text, or numerical records—along with the correct answers or outcomes (for supervised learning) or let it find structure on its own (for unsupervised learning). The system adjusts internal parameters to minimize errors, so over time it becomes better at tasks like predicting house prices, recognizing faces, translating languages, or recommending products. Rather than following fixed instructions, a machine learning system generalizes from past data to make informed predictions or decisions on new, unseen data."
}