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Download benchmarks/README.md from omida-ai/pluto-2.1: direct link, hf CLI and curl.
- Browser
- Download file 988 Bytes
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https://huggingface.co/omida-ai/pluto-2.1/resolve/main/benchmarks/README.md
- Command line
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hf download hf://omida-ai/pluto-2.1/benchmarks/README.md
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curl -L -o README.md https://huggingface.co/omida-ai/pluto-2.1/resolve/main/benchmarks/README.md
988 Bytes
Benchmark summaries
All numbers here were measured locally on one RTX 5060 Ti 16GB using the same rows and scorer for every model.
Typed Decisions
- Full independent test split: 400 held-out cases, 2,000 probabilistic decisions.
- Scored with the benchmark metric code: argmax accuracy, KL, Brier, ECE.
- Models: Pluto-2.1, Pluto-2, d1-2B, d1-3B. d1 checkpoints are zero-shot.
DecisionBench
- Public
Hanno-Labs/decision-benchevaluation split. - Matched accessibility subset: 1,565 of 23,900 rows, limited to ≤16 candidates and ≤2,048-token prompts.
- Models: Pluto-2.1, Pluto-2, Bosun 3.1 1.7B, d1-2B, d1-3B.
- This is not the full 23,900-row suite. No full-suite score is claimed.
Files
pluto21_*.json— Pluto-2.1 step 2,000pluto2_*.json— Pluto-2 400Mbosun_base_decisionbench_1565.json— Bosun 3.1 1.7B initializerd1_2b_*.json— Liquid d1-2Bd1_3b_*.json— Liquid d1-3B
The model card charts are generated from these values.