[KongchangAI]
Conceptreasoning_effort / 推理努力程度 / 推理强度

Effort

A parameter in large language model reasoning systems that controls the depth of internal chain-of-thought computation before an answer is generated. Commonly offered at Low, Medium, and High levels, it directly affects output quality, token consumption, and response latency.

Core Facts

Timeline (last 90 days)

Oct 17

Claude Code's Effort (thinking budget) setting can cause roughly a 11.9x cost difference for the same model on the same task.

Unverified50%
Oct 17

For teams that invoke Claude Code in large volumes every day, using Effort tiers is a necessary cost-control practice.

Unverified50%
Oct 17

In Claude Code, the way to view the current Effort level is to enter the Effort command, press S to change it only for this session, or press Enter to save it as the default.

Unverified50%
Oct 17

In Claude Code, allocating Effort by task type can optimize cost: the Low level is sufficient for search-type subagents, while only refactoring and complex reasoning need High or higher levels.

Unverified50%
Oct 17

In Claude Code, the Max Effort level only applies to the current session and does not automatically carry over to the next session.

Unverified50%
Oct 17

In Claude Code, when a user specifies an unsupported Effort level (such as X High) for an older model, the system silently downgrades to the highest level that model supports (usually High) and continues execution, without error or notice.

Unverified50%
Oct 17

The three ways Effort is implemented are: the definition layer (hard-coded in the Agent definition file), the cap layer (set an Effort ceiling in settings, with automatic downgrade when exceeded), and the audit layer (Tasks marks the model and level of each subagent).

Unverified50%
Oct 17

The Effort override chain has four layers: environment variables can override per-call parameters; settings still take effect after Resume; definition file fields can lock in a level; and writing Effort in an Agent definition file can fix that agent to a low budget.

Unverified50%
Oct 17

Claude Code allows specifying the Effort parameter individually for each subagent, replacing the previous mechanism where the entire session had only one global level.

Unverified50%
Oct 17

Claude Code's official cost table shows the relative cost index of Effort levels with High as the baseline: Low is 0.47X, High is 1X, Max is 5.59X, and the deepest level is about 11.9X.

Unverified50%

13 more timeline events

All Facts (20)

Verified

Haiku 5.5 is the first Haiku model with an adjustable effort setting.

70%
Unverified

For teams that invoke Claude Code in large volumes every day, using Effort tiers is a necessary cost-control practice.

50%
Unverified

In Claude Code, the way to view the current Effort level is to enter the Effort command, press S to change it only for this session, or press Enter to save it as the default.

50%
Unverified

In Claude Code, allocating Effort by task type can optimize cost: the Low level is sufficient for search-type subagents, while only refactoring and complex reasoning need High or higher levels.

50%
Unverified

In Claude Code, the Max Effort level only applies to the current session and does not automatically carry over to the next session.

50%
Unverified

In Claude Code, when a user specifies an unsupported Effort level (such as X High) for an older model, the system silently downgrades to the highest level that model supports (usually High) and continues execution, without error or notice.

50%
Unverified

The three ways Effort is implemented are: the definition layer (hard-coded in the Agent definition file), the cap layer (set an Effort ceiling in settings, with automatic downgrade when exceeded), and the audit layer (Tasks marks the model and level of each subagent).

50%
Unverified

The Effort override chain has four layers: environment variables can override per-call parameters; settings still take effect after Resume; definition file fields can lock in a level; and writing Effort in an Agent definition file can fix that agent to a low budget.

50%
Unverified

Claude Code allows specifying the Effort parameter individually for each subagent, replacing the previous mechanism where the entire session had only one global level.

50%
Unverified

Claude Code's official cost table shows the relative cost index of Effort levels with High as the baseline: Low is 0.47X, High is 1X, Max is 5.59X, and the deepest level is about 11.9X.

50%
Unverified

Claude Code's Effort (thinking budget) setting can cause roughly a 11.9x cost difference for the same model on the same task.

50%
Unverified

The Effort adjustment mechanism dynamically controls the depth of the model's reasoning chain, allowing low-Effort settings to respond quickly and high-Effort settings to trigger deeper reasoning, thereby balancing speed and accuracy.

50%
Unverified

Effort setting is an adjustment knob introduced by Anthropic in the extended thinking feature, allowing users to specify how much compute the model invests in internal reasoning before generating a response.

50%
Unverified

Low effort is suitable for deterministic tasks such as information retrieval and format conversion, while high effort is suitable for complex analysis requiring multi-step reasoning and weighing multiple solutions.

50%
Unverified

Effort control is a parameter provided at the Claude Opus 5.5 API level that allows specifying how much computational resource the model invests in reasoning at call time, with the default value being Medium.

50%
Unverified

For everyday Q&A, the Medium or High tier of a lightweight model is sufficient, and in most cases it is unnecessary to go up to Max.

50%
Unverified

Lightweight model + Max is suitable for large-scale batch tasks that are budget-sensitive, require high throughput, and can tolerate slight quality fluctuations.

50%
Unverified

Effort is an amplifier, while model tier is the capability ceiling; adding thinking budget to a smaller model cannot bridge the capability gap inherent to the model itself.

50%
Unverified

The combination of a lightweight model plus maximum Effort can often approach the perceived performance of a flagship model plus medium Effort.

50%
Unverified

Raising Effort for simple tasks yields almost no benefit, while simultaneously driving up both cost and latency.

50%

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