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Run the agentsAvailable in v0.3.0

Models chosen from benchmarks

New in v0.3.0: benchmark scores pick the model. Difficulty and a profile — performance, balanced or efficient — set the score a job needs. Balanced takes the cheapest model that reaches it, efficient the best score per price, and performance the top scorer for the hardest work. No table ties a difficulty to a model.

When you need it

A fixed table from difficulty to model goes stale every time a new model ships, and it cannot weigh price against quality.

How it works

  1. Inside the engine [stages] names, the model is the first that applies: a model pinned for the tier, the first listed model in that tier's tier_pools, a quality_order naming a listed model, then the score rule.
  2. Tiers count low 0, medium 1, high 2, max 3; performance adds 1 and balanced adds nothing, and the step never goes below the floor of the task's kind.
  3. performance and balanced take the cheapest model by list price that reaches the step; efficient may go one step lower, never below the floor, and takes the most score per list price.
  4. balanced and efficient accept a model within 2 percent of the scale below the mark; performance and floors have no such margin. The tier still sets the effort.
  5. oah models and oah doctor show the profile, scores with source and date, each tier's model and each left-out model with its reason; oah recommend --engine <engine> --stage <stage> answers for one task, launches nothing and writes nothing.

Example

See the model choice for one task without launching anything (from Concepts).

oah recommend --engine <engine> --stage <stage>

Requirements

  • Requires v0.3.0 or later.
  • Claude Code and Codex CLI that list their models.

Limits and recovery

  • Published scores measure general quality on someone else's tests, not your repository; Epoch AI's tasks are mostly maths, puzzles and reasoning, not coding, and there are few of them.
  • List prices stand in for what you pay; a subscription pays in quota instead.
  • A wrong or stale score can send work to a weaker model; to decide for yourself, pin a model.
  • efficient can cost more than balanced at a low tier.
  • With no model list (OAH_MODEL_CATALOG_UNAVAILABLE) or no usable scores (OAH_MODEL_NO_SCORES), automatic choice stops; a pin gets past both, and oah never falls back to a default model.

Original documents

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