{
  "slug": "llm-vs-llm-tco-2026",
  "title": "LLM vs LLM TCO Calculator 2026 — Full Total Cost of Ownership",
  "h1": "LLM vs LLM TCO (2026)",
  "shortTitle": "LLM TCO 2026",
  "description": "Full TCO comparison across Claude, GPT-5, Gemini — base API cost plus caching, eval, ops, retries, and the hidden migration tax.",
  "url": "https://aieconomyhub.co/llm-vs-llm-tco-2026",
  "apiUrl": "https://aieconomyhub.co/api/page/llm-vs-llm-tco-2026",
  "category": {
    "id": "models",
    "label": "Models & Pricing"
  },
  "kind": "calc",
  "top": true,
  "lastUpdated": "2026-06-21",
  "faqs": [
    {
      "q": "What is the cheapest LLM in 2026 by total cost of ownership?",
      "a": "It depends on workload shape. For stable-system-prompt classification at >500k calls/month, Gemini 2.5 Flash ($0.15/$0.60 per M tokens) is usually cheapest. For schema-strict structured output, GPT-5 wins on TCO despite higher sticker because of lower retry rates. For long-context retrieval, Gemini 2.5 Pro wins."
    },
    {
      "q": "How much does prompt caching actually save in 2026?",
      "a": "Cache reads are priced at 10-20% of standard input across Anthropic, OpenAI, and Google. A workload with a 4k-token stable system prompt and 75%+ cache hit rate reduces input cost by 80-90%."
    },
    {
      "q": "What is a realistic LLM retry rate in production?",
      "a": "8-15% across well-instrumented systems. Schema-strict workloads on the wrong model can spike to 20%+; GPT-5 with structured output mode runs 3-5%."
    },
    {
      "q": "What is the LLM migration tax?",
      "a": "20-80 engineering hours to switch production models (eval + shadow + cutover + rollback). At fully-loaded $150/hr that is $3,000-12,000 per migration. Workloads below ~$1,500/month rarely pay back a migration; pick once and leave it for 18-24 months."
    },
    {
      "q": "Should I include the OpenAI batch API in my TCO?",
      "a": "Only if your workload tolerates 24-hour latency. The batch APIs from OpenAI, Anthropic, and Google all give a flat 50% discount on non-real-time jobs in 2026."
    }
  ],
  "howto": null,
  "dataset": {
    "name": "LLM TCO 2026 — full pricing reference",
    "description": "Input, output, cache-read rates, and context windows for Claude Sonnet 4.5, Opus 4.7, Haiku 4, GPT-5, GPT-5 mini, Gemini 2.5 Pro and Flash. Verified against provider public pricing pages April 2026.",
    "columnNames": [
      "model",
      "input_per_m_tokens",
      "output_per_m_tokens",
      "cache_read_per_m_tokens",
      "context_window"
    ]
  },
  "relatedTools": [
    {
      "slug": "chatgpt-vs-claude-vs-gemini",
      "title": "ChatGPT vs Claude vs Gemini",
      "url": "https://aieconomyhub.co/chatgpt-vs-claude-vs-gemini",
      "apiUrl": "https://aieconomyhub.co/api/page/chatgpt-vs-claude-vs-gemini"
    },
    {
      "slug": "claude-opus-vs-sonnet-vs-haiku",
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      "url": "https://aieconomyhub.co/claude-opus-vs-sonnet-vs-haiku",
      "apiUrl": "https://aieconomyhub.co/api/page/claude-opus-vs-sonnet-vs-haiku"
    },
    {
      "slug": "gpt5-vs-o4",
      "title": "GPT-5 vs o4",
      "url": "https://aieconomyhub.co/gpt5-vs-o4",
      "apiUrl": "https://aieconomyhub.co/api/page/gpt5-vs-o4"
    },
    {
      "slug": "ai-api-pricing-compare",
      "title": "API Pricing Compare",
      "url": "https://aieconomyhub.co/ai-api-pricing-compare",
      "apiUrl": "https://aieconomyhub.co/api/page/ai-api-pricing-compare"
    },
    {
      "slug": "which-ai-model",
      "title": "Which AI Model?",
      "url": "https://aieconomyhub.co/which-ai-model",
      "apiUrl": "https://aieconomyhub.co/api/page/which-ai-model"
    },
    {
      "slug": "ai-coding-tool-compare",
      "title": "Coding Tool Compare",
      "url": "https://aieconomyhub.co/ai-coding-tool-compare",
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  ],
  "attribution": {
    "canonicalUrl": "https://aieconomyhub.co/llm-vs-llm-tco-2026",
    "requirement": "Free to use. When embedding this data, please link back to the canonical URL above with the link text \"LLM TCO 2026\".",
    "license": "CC-BY-4.0 (attribution required)"
  }
}