Integration guides ยท 2026-09-22
Choosing reasoning_effort for a multi-step coding agent with Muse Spark 1.2
Different from the RAG source-ranking article, this covers how to choose Muse Spark 1.2's reasoning_effort levels, from minimal to xhigh, for a multi-step coding or agent task.
Five levels, a different task class
Muse Spark 1.2 is positioned on its catalog page as a reasoning model tuned for coding and agent workflows, and accepts a `reasoning_effort` field across minimal, low, medium, high, and xhigh. The RAG source-ranking article covers using this model in a retrieval context; this article looks at how to choose among the same five levels on a multi-step coding task (reading a bug report, finding the relevant files, and proposing a fix, for example).
The 1,048,576-token context window makes it possible to carry a large codebase or a long diff history in a single request; using that wide context effectively requires matching reasoning_effort to the task's complexity.
Map the level to the task type
On a simple task proposing a small fix in a single file, minimal or low is usually sufficient and keeps latency low. On a task tracing a bug's root cause across several layers with dependencies between multiple files, moving to medium or high lets the model evaluate intermediate steps more thoroughly.
xhigh should be reserved for the most complex, multi-step agent loops (calling a tool and revising the plan based on its result, for example); this level carries the highest latency and reasoning-token cost, and using it on simple tasks unnecessarily raises both.
- Simple single-file fix: minimal or low.
- Multi-file, layered root-cause analysis: medium or high.
- Multi-step agent loop: xhigh, but only when needed.
Reasoning tokens are deducted from your output budget
Reasoning tokens are returned inside `completion_tokens` and billed as output; if you don't keep `max_tokens` large enough at a high effort level, the reasoning can consume the budget and the actual content can come back empty. Adjust your `max_tokens` budget accordingly when raising the effort level.
Frequently asked questions
Should I use xhigh on every coding task?
No. xhigh carries the highest latency and cost; minimal or low is usually enough on simple tasks. Choose the level based on task complexity and test it with your own tasks.
Does changing reasoning_effort affect tool-calling behavior?
Tool calling works at every effort level; the difference is how much intermediate-step evaluation the model does before deciding on a tool call.