# Kimi Code 0.24.1

- Product: Kimi Code (https://whatsnew.fyi/product/kimi-code)
- Vendor: Moonshot AI
- Date: 2026-07-14
- Version: 0.24.1
- Original notes: https://github.com/MoonshotAI/kimi-code/releases/tag/%40moonshot-ai/kimi-code%400.24.1
- Permalink: https://whatsnew.fyi/product/kimi-code/releases/0.24.1
- Labels: Platforms: Desktop

What's New is an index, not a publisher: every entry below links to the vendor's own release notes, which are the authoritative source. Entries are labelled where they are hand-curated sample data, pre-releases, or drawn from a secondary source such as a developer blog.

Reuse: the summaries, labels and curation here are © What's New. Quote freely with attribution and a link back; wholesale republication of the corpus is not permitted — terms: https://whatsnew.fyi/terms. The vendors' own release notes remain their publishers'.

---

- **fixed** — Preserve goal completion summaries and show untyped LLM errors without an internal error-code prefix in step interruption events
- **fixed** — Fix built-in tools being unavailable when the model provider becomes ready after the session starts
- **fixed** — Fix Kimi sessions getting stuck when preserved-thinking history contains an empty reasoning step
- **changed** — Align thinking-level handling in web with the CLI: submit the selected level verbatim instead of silently downgrading it, pin the model's catalog default when nothing was chosen, pre-select the target model's default on model switches, and persist explicit picks as the daemon-wide default so new sessions inherit them
- **changed** — Show just the level name (e.g. Max) in the model pill instead of "thinking: max"
- **fixed** — Fix Thinking effort routing so non-Kimi providers preserve configured values for upstream validation, while Kimi models validate runtime selections, fall back safely during model resolution, and synchronize the effective effort back to clients

###### Patch Changes

- [#1678](https://github.com/MoonshotAI/kimi-code/pull/1678) [`ec1c974`](https://github.com/MoonshotAI/kimi-code/commit/ec1c9748c816d152bf06af2456e82ac35786bba9) Thanks [@chengluyu](https://github.com/chengluyu)! - Preserve goal completion summaries and show untyped LLM errors without an internal error-code prefix in step interruption events.

- [#1688](https://github.com/MoonshotAI/kimi-code/pull/1688) [`94c0ef8`](https://github.com/MoonshotAI/kimi-code/commit/94c0ef89d29ea8532be02828201328fa1281273c) Thanks [@sailist](https://github.com/sailist)! - Fix built-in tools being unavailable when the model provider becomes ready after the session starts.

- [#1684](https://github.com/MoonshotAI/kimi-code/pull/1684) [`e417ee7`](https://github.com/MoonshotAI/kimi-code/commit/e417ee7c2c282f00113dc0e4f4514ca5018b76c9) Thanks [@RealKai42](https://github.com/RealKai42)! - Fix Kimi sessions getting stuck when preserved-thinking history contains an empty reasoning step.

- [#1673](https://github.com/MoonshotAI/kimi-code/pull/1673) [`0f64b4d`](https://github.com/MoonshotAI/kimi-code/commit/0f64b4dcc4f2d295d0039b176d96d8003cb49991) Thanks [@wbxl2000](https://github.com/wbxl2000)! - web: Align thinking-level handling with the CLI: submit the selected level verbatim instead of silently downgrading it, pin the model's catalog default when nothing was chosen, pre-select the target model's default on model switches, and persist explicit picks as the daemon-wide default so new sessions inherit them.

- [#1689](https://github.com/MoonshotAI/kimi-code/pull/1689) [`ab22a2a`](https://github.com/MoonshotAI/kimi-code/commit/ab22a2adf0ca17cbb94f1abdab334ebc58814e8d) Thanks [@wbxl2000](https://github.com/wbxl2000)! - web: Show just the level name (e.g. Max) in the model pill instead of "thinking: max".

- [#1625](https://github.com/MoonshotAI/kimi-code/pull/1625) [`d158e0a`](https://github.com/MoonshotAI/kimi-code/commit/d158e0a7ac4e432046d56787263dd2dbac40285e) Thanks [@RealKai42](https://github.com/RealKai42)! - Fix Thinking effort routing so non-Kimi providers preserve configured values for upstream validation, while Kimi models validate runtime selections, fall back safely during model resolution, and synchronize the effective effort back to clients.