# AA-Omniscience-Decision accuracy

> d1 leads Artificial Analysis' October 15, 2026 snapshot of AA-Omniscience-Decision accuracy at 41.0. Share of 500 private knowledge questions answered correctly. Each question offers four answers and an "I don't know" option.

Canonical page: https://benchlm.ai/benchmarks/aa-omniscience-decision-accuracy

- Category: [Decision Models](/decision-models)
- Last updated: October 15, 2026 snapshot

Evaluation results published by [Artificial Analysis](https://artificialanalysis.ai/evaluations/artificial-analysis-decision-index). undefined

Artificial Analysis publishes the Decision Index v1.0 as a live leaderboard of decision models, models that answer a typed question in one call with a probability for each option. Share of 500 private knowledge questions answered correctly. Each question offers four answers and an "I don't know" option.

Artificial Analysis runs every evaluation itself, so these are independent measurements and not provider reports. We mirror its decision-model rows and keep the language-model baselines it runs for comparison on its own page.

Scores are rounded to one decimal; Artificial Analysis charts print integers. The index is a different protocol from Decision Index 0.2.1 and 0.3, so values do not carry across.

- [Artificial Analysis Decision Index](https://artificialanalysis.ai/evaluations/artificial-analysis-decision-index)
- [Launch article and methodology](https://artificialanalysis.ai/articles/artificial-analysis-decision-index)
- [Decision Models](/decision-models)
- [d1-ultra profile and pricing](/models/d1-ultra)

## About AA-Omniscience-Decision accuracy

- Year: 2026
- Format: Accuracy
- Difficulty: Knowledge questions with an abstain option
- Paper: [Artificial Analysis Decision Index v1.0](https://artificialanalysis.ai/articles/artificial-analysis-decision-index)

Artificial Analysis runs every evaluation itself and poses each question as one typed decision with a probability for each option. We mirror its decision-model rows, round values to one decimal, and keep the language-model baselines it also runs on its own page. These results are separate from Decision Index 0.2.1, Decision Index 0.3, JevBench, and general model rankings.

AA-Omniscience-Decision accuracy is currently displayed on BenchLM for reference, but it is excluded from the weighted scoring formula.

## Leaderboard (13 decision models)

| Rank | Model | Index | Knowledge accuracy | Non-hallucination | HLE-MultiChoice | When2Call | WildGuardTest | Cost per 1M tasks | Time per task |
|---|---|---|---|---|---|---|---|---|---|
| 1 | [d1](/models/liquid-d1) | 50.3 | 41.0 | 1.7 | 11.5 | 77.4 | 90.9 | $30.29 | 299 ms |
| 2 | [GPT-6 Luna (Decisions)](https://artificialanalysis.ai/evaluations/artificial-analysis-decision-index) | 48.5 | 40.6 | 10.1 | 11.7 | 74.1 | 82.8 | $78.87 | 168 ms |
| 3 | [Decider v1.1 27B](https://artificialanalysis.ai/evaluations/artificial-analysis-decision-index) | 53.1 | 39.8 | 13.3 | 15.4 | 76.5 | 93.8 | $16.53 | 170 ms |
| 4 | [Clef](/models/cloudflare-clef) | 48.6 | 39.0 | 4.3 | 11.1 | 71.0 | 90.7 | $199.41 | 309 ms |
| 5 | [Celeris-1 Decision](/models/celeris-1-decision) | 52.3 | 37.8 | 0.0 | 13.3 | 83.7 | 93.3 | $31.57 | 63 ms |
| 6 | [GLiDE](/models/fastino-glide) | 53.9 | 36.4 | 16.4 | 10.5 | 83.7 | 95.1 | $119.02 | 217 ms |
| 7 | [Clef-Omni](https://artificialanalysis.ai/evaluations/artificial-analysis-decision-index) | 44.3 | 36.0 | 1.6 | 9.0 | 62.1 | 87.2 | $123.08 | 172 ms |
| 8 | [Mercury Decide](https://artificialanalysis.ai/evaluations/artificial-analysis-decision-index) | 52.7 | 35.0 | 32.0 | 10.1 | 79.3 | 88.0 | $15.2 | 500 ms |
| 9 | [Jev 1.13](https://artificialanalysis.ai/evaluations/artificial-analysis-decision-index) | 57.5 | 34.6 | 35.2 | 20.9 | 80.7 | 93.6 | $41.53 | 127 ms |
| 10 | [Jev 1.14](https://artificialanalysis.ai/evaluations/artificial-analysis-decision-index) | 57.1 | 33.8 | 37.2 | 18.9 | 80.8 | 93.1 | $41.53 | 78 ms |
| 11 | [Clef-Flash](/models/cloudflare-clef-flash) | 45.8 | 32.6 | 2.7 | 10.3 | 64.4 | 90.9 | $31.57 | 298 ms |
| 12 | [d1-ultra](/models/d1-ultra) | 65.2 | 31.6 | 84.5 | 15.0 | 92.6 | 95.4 | $31.8 | 93 ms |
| 13 | [Microsoft-Decision-1](https://artificialanalysis.ai/evaluations/artificial-analysis-decision-index) | 53.8 | 28.2 | 39.8 | 10.9 | 81.9 | 88.2 | $30.71 | 207 ms |

Artificial Analysis runs every evaluation. The index weights AA-Omniscience-Decision accuracy and non-hallucination rate at 12.5% each and HLE-MultiChoice, When2Call and WildGuardTest at 25% each. Values are rounded to one decimal; language-model baselines on the source leaderboard are not mirrored.
## FAQ

### What does AA-Omniscience-Decision accuracy measure?

AA-Omniscience-Decision accuracy is one component of the Artificial Analysis Decision Index v1.0, run by Artificial Analysis. It is the share of 500 private knowledge questions answered correctly, each with four answers and an "I don't know" option.

### Which model leads the published AA-Omniscience-Decision accuracy snapshot?

d1 currently leads the published AA-Omniscience-Decision accuracy snapshot with a score of 41.0%.

### How many models are evaluated on AA-Omniscience-Decision accuracy?

The October 15, 2026 snapshot contains 13 decision models scored by Artificial Analysis.

### Does AA-Omniscience-Decision accuracy affect BenchLM's overall score?

Not directly. AA-Omniscience-Decision accuracy is still displayed on BenchLM for reference, but it is excluded from the weighted scoring formula.