{
  "schema_version": "1.1",
  "id": "auto-b3425f8b3f",
  "slug": "how-cursor-router-chooses-the-right-model-for-the-task-b3425f8b3f",
  "url": "https://feed7.dev/p/how-cursor-router-chooses-the-right-model-for-the-task-b3425f8b3f",
  "title": "How Cursor Router chooses the right model for the task",
  "why_included": "Route models using real task outcomes, corrections, cache costs, confidence thresholds, and an explicit per-turn budget.",
  "summary": "Cursor Router learns task complexity and model fit from production behavior, showing why agent routing should include correction signals, cache costs, and per-task performance.",
  "practical_implication": "Builders implementing model routing should learn from real task outcomes, including corrections and task progression, rather than rely only on benchmarks. Include token use, cache misses, model-switching costs, confidence thresholds, and an explicit per-turn budget.",
  "agent_context": "Cursor routes each turn in two stages: Compass estimates complexity, then a production-derived taxonomy selects among eligible frontier models. **Auto Intelligence costs 68% less than Fable**, while **Auto Balance costs 41% less than Opus 4.8** and reports higher satisfaction.\n\nBuilders implementing model routing should learn from real task outcomes, including corrections and task progression, rather than rely only on benchmarks. Include token use, cache misses, model-switching costs, confidence thresholds, and an explicit per-turn budget.\n\nCursor's satisfaction measure is inferred from subsequent user behavior, so it is a proxy rather than a direct quality score. The reported results come from Cursor traffic and may not transfer to another workload, user population, or pricing mix.",
  "source": {
    "name": "Cursor",
    "url": "https://cursor.com/blog/how-cursor-router-works",
    "published_at": "2026-08-06T00:00:00.000Z"
  },
  "source_class": "blog_post",
  "content_type": "Engineering Post",
  "layer": "agent",
  "domains": [
    "coding",
    "data"
  ],
  "topics": [
    "model-selection",
    "harness-engineering",
    "agent-reliability"
  ],
  "verification": {
    "status": "official_source",
    "label": "Official Source",
    "method": "source_feed",
    "verified_at": null
  },
  "uncertainty": [],
  "connected_context": null,
  "lifecycle": "New",
  "published_at": "2026-08-06T00:00:00.000Z",
  "modified_at": "2026-08-06T00:00:00.000Z",
  "supersedes": [],
  "expires_at": null,
  "formats": {
    "html": "https://feed7.dev/p/how-cursor-router-chooses-the-right-model-for-the-task-b3425f8b3f",
    "json": "https://feed7.dev/p/how-cursor-router-chooses-the-right-model-for-the-task-b3425f8b3f.json",
    "markdown": "https://feed7.dev/p/how-cursor-router-chooses-the-right-model-for-the-task-b3425f8b3f.md"
  }
}