MLS Bench LiteBrowse 296

MLS Bench Lite

Can the model complete substantial programming work under this benchmark's agent setup?

Version not specifiedExact reported variant
Coding4 ranked models4 reported values1 reportsHigher is better

Top rankings

One row per model, using its best reported score across effort settings.

4
RankModelBest scoreBest reported setting
1Claude Opus 4.8Anthropic42.8%xhigh effortMoonshot AI report1 value · 1 reportJul 22, 2026 · source
2GPT-5.5OpenAI35.5%xhigh effortMoonshot AI report1 value · 1 reportJul 22, 2026 · source
3Kimi K2.7 CodeMoonshot AI35.1%thinking effortMoonshot AI report1 value · 1 reportJul 22, 2026 · source
4Kimi K2.6Moonshot AI26.7%thinking effortMoonshot AI report1 value · 1 reportJul 22, 2026 · source

Effort curve

Every sourced cost-linked effort value for this exact version. Lines connect complete sweeps only.

0
No cost-linked effort sweep for this version.
Definition and comparison boundarypublic methodology

Can the model complete substantial programming work under this benchmark's agent setup?

Software implementation, debugging, or repository work under the published evaluation protocol. Higher is better. The value is the percentage reported in this lab's table.

Harness, tools, prompts, attempt count, and benchmark version can materially change the result. Compare within one reporting context.

Kimi Code CLI with thinking enabled, temperature 1.0, top-p 0.95, and 262,144-token context; GPT-5.5 used Codex xhigh and Claude Opus 4.8 used Claude Code xhigh.

Method / source