DeepSeek V3.2 Speciale Enhanced Reasoning LLM

Name: DeepSeek V3.2 Speciale Enhanced Reasoning LLM
Price: 0.008 USD

x402

DeepSeek V3.2 Speciale Enhanced Reasoning LLM is a paid API for AI agents from x402-gateway-production.up.railway.app, paid per call via x402, $0.008000/call, status unknown (last checked 2026-09-15).

Runs DeepSeek's enhanced chain-of-thought reasoning variant (deepseek-v3.2-speciale) for complex multi-step tasks via a pay-per-call gateway

Price / call$0.008000

Seller volume →—

Success—

StatusUnknown

How this service works

DeepSeek's enhanced reasoning variant — improved chain-of-thought for complex tasks

Output

Returns a text completion from deepseek-v3.2-speciale-20251201 with the model's response, token usage breakdown (prompt tokens, completion tokens, reasoning tokens), and upstream inference cost details in USDC.

Example use cases

Example prompt

“Use DeepSeek's enhanced chain-of-thought reasoning model to solve this step by step: A train leaves Chicago at 60mph and another leaves New York at 80mph toward each other 1,000 miles apart — when and where do they meet?”

Technical details

Endpoint

POSThttps://x402-gateway-production.up.railway.app/api/llm/deepseek-v3.2-speciale

When to prefer

Choose this endpoint when you need DeepSeek's enhanced reasoning model specifically — it includes visible reasoning_tokens in the response, making it ideal for complex multi-step math, logic, coding, or analysis tasks where chain-of-thought quality matters. Prefer over generic GPT-4 or Claude endpoints when you want DeepSeek's specific reasoning style at a low per-call cost ($0.008 USDC) without managing your own API keys.

Side effects

Invalid or missing messages array returns 400 error
Payment not included or insufficient USDC causes x402 payment required error
Upstream model unavailable returns 503 or timeout
Malformed JSON body returns parse error
Rate limiting if too many concurrent requests

Input

{
  "messages": [
    {
      "role": "user",
      "content": "Solve this multi-step math problem step by step: If a store sells apples at $2 per pound and oranges at $3 per pound, and a customer buys 5 pounds of apples and 3 pounds of oranges, what is the total cost?"
    }
  ]
}

Output

{
  "model": "deepseek/deepseek-v3.2-speciale-20251201",
  "usage": {
    "cost": 0.0002556,
    "is_byok": false,
    "cost_details": {
      "upstream_inference_cost": 0.0002556,
      "upstream_inference_prompt_cost": 0.000024,
      "upstream_inference_completions_cost": 0.0002316
    },
    "total_tokens": 253,
    "prompt_tokens": 60,
    "completion_tokens": 193,
    "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": 105
    }
  },
  "content": "The total cost is calculated as follows:\n\n- Cost of apples: \\(5 \\text{ pounds} \\times \\$2 \\text{ per pound} = \\$10\\)\n- Cost of oranges: \\(3 \\text{ pounds} \\times \\$3 \\text{ per pound} = \\$9\\)\n- Total: \\(\\$10 + \\$9 = \\$19\\)\n\nSo, the total cost is \\(\\$19\\)."
}

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How this service works

DeepSeek's enhanced reasoning variant — improved chain-of-thought for complex tasks

Output

Technical details

Endpoint

POSThttps://x402-gateway-production.up.railway.app/api/llm/deepseek-v3.2-speciale

When to prefer

Side effects

Invalid or missing messages array returns 400 error
Payment not included or insufficient USDC causes x402 payment required error
Upstream model unavailable returns 503 or timeout
Malformed JSON body returns parse error
Rate limiting if too many concurrent requests

Input

{
  "messages": [
    {
      "role": "user",
      "content": "Solve this multi-step math problem step by step: If a store sells apples at $2 per pound and oranges at $3 per pound, and a customer buys 5 pounds of apples and 3 pounds of oranges, what is the total cost?"
    }
  ]
}

Output

{
  "model": "deepseek/deepseek-v3.2-speciale-20251201",
  "usage": {
    "cost": 0.0002556,
    "is_byok": false,
    "cost_details": {
      "upstream_inference_cost": 0.0002556,
      "upstream_inference_prompt_cost": 0.000024,
      "upstream_inference_completions_cost": 0.0002316
    },
    "total_tokens": 253,
    "prompt_tokens": 60,
    "completion_tokens": 193,
    "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": 105
    }
  },
  "content": "The total cost is calculated as follows:\n\n- Cost of apples: \\(5 \\text{ pounds} \\times \\$2 \\text{ per pound} = \\$10\\)\n- Cost of oranges: \\(3 \\text{ pounds} \\times \\$3 \\text{ per pound} = \\$9\\)\n- Total: \\(\\$10 + \\$9 = \\$19\\)\n\nSo, the total cost is \\(\\$19\\)."
}