--- title: "13 — Model Configuration — Picking the Right Brain for the Job" uid: model-configuration tags: ["effort", "opus", "roadmap:claude-code", "haiku", "opusplan", "sonnet", "models", "claude-code"] excerpt: "Opus, Sonnet, Haiku sit on one reasoning-vs-speed curve — match the brain to the task, tune effort, and let planning use opusplan when it deserves more than execution." date: 2026-08-13T03:28:20+0000 source: https://www.aveshina.my.id/en/blog/model-configuration --- "Just pick the biggest" was my model-selection strategy, and it was wrong in three ways at once: slowest, priciest, and often unnecessary. The curve that replaced it: **the three Claude models sit on a single reasoning-versus-speed curve, and the job is to match the brain to the task — deep reasoning for hard architecture, balance for daily building, speed for mechanical work.** [1] "Biggest" is wrong because the biggest is also the slowest and the most expensive; it's the right choice for one kind of task and a costly waste for another. The framing that clicked is to think of Opus, Sonnet, and Haiku as three points on the same tradeoff curve, not three unrelated products. As I move along the curve toward more reasoning, I give up speed and pay more. As I move toward speed, I give up depth and pay less. The configuration tools — /model, the --model flag, the model key in settings, the effort dial, and opusplan — are all mechanisms for picking the right point on that curve for the task at hand [1]. ## The three models on the curve The roadmap describes each model with a one-line role, and once I read them as positions on the curve they snapped into place [1]: - **Opus** — the deep thinker. The most capable, used for complex reasoning, high-level system design, and surgical bug fixes in large codebases. Slowest and most expensive. The right pick when a wrong answer is expensive and the problem is genuinely hard. - **Sonnet** — the balanced builder. Strikes a balance between reasoning and speed; handles multi-file refactoring and autonomous debugging while running faster and cheaper than Opus. The default for daily coding, and for good reason — most tasks are neither trivial nor research-grade. - **Haiku** — the fast-response specialist. Fastest and cheapest, for near-instant execution of lightweight tasks: rapid UI prototypes, commit messages, or parallel subagents scanning logs and running quick checks [2]. The right pick when the answer is easy and I'm paying for throughput. ```figure ``` ## The configuration hierarchy The roadmap describes a layered configuration system, and reading it as "most specific wins" made it click [1]: - **/model** — switch the model instantly during a session. The override for "this task needs a different brain." - **--model flag** — specify the model at launch. The override for "this whole session is one kind of work." - **model key in ~/.claude/settings.json** — the permanent default. The right place for the model I want on every session unless I say otherwise. Semantic aliases (sonnet, haiku, opus) make these readable. Sonnet is the documented default for daily coding, which matches what I reach for — most work is in the balanced middle of the curve. ## Effort: tuning within a model A separate axis from _which_ model is _how hard_ the model tries. The roadmap calls it **effort** — a parameter (low, medium, high) available through /model that controls how much thinking time the model allocates to solving a problem versus generating a rapid response [3]. Effort composes with the model choice, and the combination is the real lever. A low-effort Haiku for "draft a commit message" is cheap and fast. A high-effort Opus for "design the auth architecture" is slow and expensive but right. The mistake is leaving effort pinned high always — the thinking tokens cost money on API billing, so dialing effort down for mechanical work is a real saving, not a nicety. ## opusplan: plan deep, build balanced The cleverest configuration in the roadmap is **opusplan**, and it deserves its own moment. When I start a session with claude opusplan, the tool uses Opus to analyze the request, explore the codebase, and draft a comprehensive technical strategy — getting the hard architectural decisions right — and then automatically switches to Sonnet for the actual code implementation [4]. The point is that planning and execution sit at different points on the curve, and most tasks benefit from deep reasoning on the _plan_ and balanced speed on the _build_. The way of thinking: opusplan automates the habit I described in the workflow post (don't collapse explore+plan into implement) and assigns the best brain to each phase. It's the right default for non-trivial features where the architecture matters more than the typing speed — Opus nails the strategy, Sonnet efficiently executes it, and I get depth where it counts without paying Opus prices for every edit. ## How I use this The habit these notes left me with is a two-axis match before any non-trivial session. First, _which model_: Haiku for throwaway drafts and parallel log-scanning subagents, Sonnet for daily building, Opus reserved for genuinely hard reasoning. Second, _what effort_: low for mechanical work, high for architectural puzzles, and I dial it down whenever I notice I'm paying for thinking on a task that doesn't need it. For features where the plan matters more than the typing, opusplan is the default — deep strategy, balanced execution. The throughline: the biggest model is a tool, not a setting; matching the brain (and the effort) to the task is the whole craft. ## References [1] Anthropic, "Model configuration," Claude Code Docs, 2025. [Online]. Available: [https://code.claude.com/docs/en/model-config#model-configuration](https://code.claude.com/docs/en/model-config#model-configuration) [2] Anthropic, "Models," Claude Code Docs, 2025. [Online]. Available: [https://code.claude.com/docs/en/how-claude-code-works#models](https://code.claude.com/docs/en/how-claude-code-works#models) [3] Anthropic, "Adjust effort level," Claude Code Docs, 2025. [Online]. Available: [https://code.claude.com/docs/en/model-config#adjust-ef](https://code.claude.com/docs/en/model-config#adjust-ef) [4] Anthropic, "opusplan model setting," Claude Code Docs, 2025. [Online]. Available: [https://code.claude.com/docs/en/model-config#opusplan-model-setting](https://code.claude.com/docs/en/model-config#opusplan-model-setting) ```quiz Q: How are Opus, Sonnet, and Haiku best understood? - As three unrelated products for different industries - As three points on a single reasoning-vs-speed curve correct: 1 explain: All three sit on the same tradeoff curve. Toward Opus = more reasoning, slower, pricier. Toward Haiku = faster, cheaper, shallower. The job is matching the point to the task. Q: Which model is the documented default for daily coding, and why? - Opus, because it is the most capable - Sonnet, because it balances reasoning and speed for typical multi-file work correct: 1 explain: Sonnet is the default. Most tasks are neither trivial nor research-grade, so the balanced middle of the curve fits. Opus is reserved for genuinely hard reasoning. Q: What does the effort parameter control? - Which model is selected - How much thinking time the model allocates (low/medium/high) within a model correct: 1 explain: Effort is a separate axis from model choice. It tunes thinking tokens, which also affect API cost. Dial it down for mechanical work, up for hard problems. Q: What does `claude opusplan` do? - Uses Opus for the entire session - Uses Opus to plan (explore + strategize), then switches to Sonnet for implementation correct: 1 explain: opusplan assigns the best brain to each phase: deep reasoning for the plan, balanced speed for the build. It automates "don't collapse explore+plan into implement." Q: You need to draft commit messages and scan logs across 50 files. Best model choice? - Opus, for accuracy - Haiku, for near-instant lightweight work (and it's ideal as a parallel subagent) correct: 1 explain: These are lightweight, high-volume tasks where the answer is easy and throughput matters. Haiku is the fast-response specialist — cheap and quick, and well-suited to parallel subagents. ```