reasoning benchmark
PostTrainBench Lite
PostTrainBench Lite measures whether an agent can design and execute a full post-training strategy (data, prompts, RL recipe, and eval loop) for a pretrained base model under a constrained time budget, scored as normalized mean reward over the improvement window.
Updated Aug 11, 2026
Models3
Model coverage3
MetricScore
EvidenceB
PostTrainBench Lite Ranking
Higher score ranks better on this benchmark.
| 01 | OP | 51.5% | 100.0% | 3 | C | |
| 02 | OP | 50.3% | 50.0% | 3 | C | |
| 03 | OP | 29.6% | 0.0% | 3 | C |
PostTrainBench Lite Score Distribution
A closer view of the leading scores on this benchmark.
PostTrainBench Lite Highlights
The leading models and scores on this benchmark.
What is PostTrainBench Lite?
What PostTrainBench Lite measures and how its scores work.
PostTrainBench Lite measures whether an agent can design and execute a full post-training strategy (data, prompts, RL recipe, and eval loop) for a pretrained base model under a constrained time budget, scored as normalized mean reward over the improvement window.
Scores are shown in ratio. This benchmark is not independently verified and has an evidence level of B.
- Family
- PostTrainBench Lite
- Modality
- text
- Primary category
- reasoning
- Score direction
- higher
- LLMBoard eligible
- Yes
- Evaluation key
- posttrainbench-lite|llm-stats-current
Benchmark scores retain their original unit. Overall score eligibility is shown separately.
FAQ
Common questions about PostTrainBench Lite.
Which model scores highest on PostTrainBench Lite?
GPT-5.6 Terra is currently ranked first with 51.5%.
What does PostTrainBench Lite measure?
PostTrainBench Lite measures whether an agent can design and execute a full post-training strategy (data, prompts, RL recipe, and eval loop) for a pretrained base model under a constrained time budget, scored as normalized mean reward over the improvement window.
Is a higher score better?
Yes. Higher values rank better for this benchmark.
How many models are compared?
3 model results are currently shown.
Does this benchmark affect the overall score?
Yes. This benchmark can contribute to the current LLMBoard capability score.