MLS-Bench Lite
We show this table for reference; we do not rank on it.
A 30-task subset of MLS-Bench that evaluates whether AI systems can invent generalizable and scalable machine-learning methods.
Benchmark score on MLS-Bench Lite — November 13, 2026
We compile the MLS-Bench Lite rows from provider self-reports. Kimi K3 leads the table at 48.3%, followed by Qwen3.8 Max (41.0%) and Step 5 Preview (40.5%). We do not use these results to rank models overall.
Kimi K3
Moonshot AI
Reported by Moonshot AIQwen3.8 Max
Alibaba
Reported by AlibabaStep 5 Preview
StepFun
Reported by StepFun4 modelsCodingCurrentDisplay onlyUpdated November 13, 2026
Benchmark score table (4 models)
All 4 results on this page were reported by the labs that built the models.
| Rank | Model / configuration | Score | Who ran it | Parameters (B) | Open / closed |
|---|---|---|---|---|---|
| 1 | Kimi K3Moonshot AIReported by Moonshot AI | 48.3% | Reported by Moonshot AI | Not reported | Open |
| 2 | Qwen3.8 MaxAlibabaReported by Alibaba | 41.0% | Reported by Alibaba | Not reported | Open |
| 3 | Step 5 PreviewStepFunReported by StepFun | 40.5% | Reported by StepFun | Not reported | Open |
| 4 | Kimi K2.7 CodeMoonshot AIReported by Moonshot AI | 35.1% | Reported by Moonshot AI | Not reported | Open |
- Lab-reported
- Benchmark-run
- Independent
Among the reported MLS-Bench Lite rows, Kimi K3 is first at 48.3%. The third row is 7.8 points behind. The broader top-10 range is 13.2 points, so the table still separates the published systems.
4 models have been evaluated on MLS-Bench Lite. The benchmark falls in the Coding category. MLS-Bench Lite is currently displayed for reference but excluded from the scoring formula, so it does not directly affect overall rankings.
About MLS-Bench Lite
Year
2026
Tasks
30 machine-learning research tasks
Format
Agentic ML task evaluation
Difficulty
ML research and systems engineering
Moonshot reports MLS-Bench Lite as a coding-agent result for Kimi K2.7 Code. BenchLM stores the provider-reported exact value separately from weighted coding benchmarks because the row is a newly reported benchmark variant with sparse public model coverage.
Freshness and provenance
Version
MLS-Bench Lite 2026
Refresh cadence
Quarterly
Staleness state
Current
Question availability
Public benchmark set
BenchLM uses freshness metadata to decide whether a benchmark should still be treated as a strong differentiator, a benchmark to watch, or a display-only reference. For the full scoring policy, see the BenchLM methodology page.
Questions
What does MLS-Bench Lite measure?
A 30-task subset of MLS-Bench that evaluates whether AI systems can invent generalizable and scalable machine-learning methods.
Which model scores highest on MLS-Bench Lite?
Kimi K3 by Moonshot AI currently leads with a score of 48.3% on MLS-Bench Lite.
How many models are evaluated on MLS-Bench Lite?
4 AI models have published results on MLS-Bench Lite in the BenchLM catalog.
Compare top models on MLS-Bench Lite
Know when it’s worth switching models
The model to choose, the cheaper alternative, and the release we would wait on.
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