AA-Omniscience v1.1: accuracy leaderboard
As of 9 Nov 2026, the top score on AA-Omniscience v1.1: accuracy is 79.1% by Claude Fable 5.2 (Anthropic), ahead of Claude Fable 5.1 at 68.4%, across 132 model configurations with a published result (Artificial Analysis, result dated 9 Nov 2026). The share of AA-Omniscience questions answered correctly, before any penalty for confident wrong answers. AA-Omniscience v1.1: accuracy is shown for reference only and does not count toward the BenchLeader Index.
Key facts (as of 9 Nov 2026)
- Claude Fable 5.2 holds the top AA-Omniscience v1.1: accuracy score at 79.1% (Artificial Analysis, 9 Nov 2026).
- Claude Fable 5.1 is second on AA-Omniscience v1.1: accuracy at 68.4% (Artificial Analysis, 1 Sep 2026).
- AA-Omniscience v1.1: accuracy: The share of AA-Omniscience questions answered correctly, before any penalty for confident wrong answers (Artificial Analysis).
- 132 model configurations have a published AA-Omniscience v1.1: accuracy result on BenchLeader (BenchLeader, 9 Nov 2026).
- AA-Omniscience v1.1: accuracy does not feed the BenchLeader Index; it is shown for reference (BenchLeader methodology).
The share of AA-Omniscience questions answered correctly, before any penalty for confident wrong answers.
- Published by
- Artificial Analysis
- Category
- Knowledge
- Index weight
- Reference only
- Models
- 132
- Data as of
- 9 Nov 2026
Source: Artificial Analysis (artificialanalysis.ai). Data taken from the public leaderboard.
- 1Claude Fable 5.2 (max)79.1%
- 2Claude Fable 5.2 (xhigh)78.0%
- 3Claude Fable 5.2 (high)77.2%
- 4Claude Fable 5.2 (medium)77.0%
- 5Claude Fable 5.2 (low)76.3%
- 6Claude Fable 5.1 (max)68.4%
- 7Claude Fable 5.1 (xhigh)67.2%
- 8Claude Opus 5.5 (xhigh)65.5%
- 9Claude Opus 5.5 (max)65.5%
- 10Claude Opus 5.5 (high)64.8%
- 11Claude Fable 5.1 (high)64.7%
- 12Claude Opus 5.5 (medium)63.9%
- 13Claude Opus 5.5 (low)63.3%
- 14Claude Fable 5.1 (medium)62.6%
- 15GPT-6.1 Sol (max)61.8%
| # | ||||
|---|---|---|---|---|
| 1 | New | 79.1% | 69.4 | 2026-11-09 |
| 2 | New | 78.0% | 68.7 | 2026-11-09 |
| 3 | New | 77.2% | 68.9 | 2026-11-09 |
| 4 | New | 77.0% | 66.3 | 2026-11-09 |
| 5 | New | 76.3% | 65.3 | 2026-11-09 |
| 6 | 68.4% | 66.9 | 2026-09-01 | |
| 7 | 67.2% | 64.6 | 2026-09-01 | |
| 8 | 65.5% | 65.5 | 2026-09-22 | |
| 9 | 65.5% | 68.9 | 2026-09-22 | |
| 10 | 64.8% | 65.4 | 2026-09-22 | |
| 11 | 64.7% | 63.3 | 2026-09-01 | |
| 12 | 63.9% | 61.5 | 2026-09-22 | |
| 13 | 63.3% | 59.0 | 2026-09-22 | |
| 14 | 62.6% | 61.7 | 2026-09-01 | |
| 15 | 61.8% | 67.0 | 2026-09-29 | |
| 16 | 61.6% | 67.4 | 2026-09-03 | |
| 17 | 61.1% | 66.5 | 2026-09-03 | |
| 18 | 61.1% | 63.8 | 2026-09-29 | |
| 19 | 61.0% | 66.2 | 2026-09-03 | |
| 20 | 60.9% | 65.1 | 2026-07-24 | |
| 21 | 60.4% | 63.5 | 2026-09-29 | |
| 22 | 59.6% | 64.5 | 2026-09-03 | |
| 23 | 59.6% | 62.9 | 2026-09-29 | |
| 24 | 58.7% | 58.7 | 2026-09-01 | |
| 25 | 58.6% | 60.2 | 2026-09-29 | |
| 26 | 58.6% | 62.2 | 2026-09-03 | |
| 27 | 58.3% | 68.5 | 2026-10-28 | |
| 28 | 51.5% | 65.0 | 2026-09-28 | |
| 29 | 51.1% | 62.9 | 2026-09-22 | |
| 30 | 50.9% | 62.7 | 2026-09-28 | |
| 31 | 50.5% | 61.8 | 2026-09-02 | |
| 32 | 50.3% | 58.0 | 2026-09-28 | |
| 33 | 50.0% | 55.3 | 2026-11-03 | |
| 34 | 49.6% | 60.3 | 2026-09-02 | |
| 35 | 49.2% | – | 2026-10-28 | |
| 36 | 48.9% | 64.1 | 2026-10-28 | |
| 37 | 48.9% | 61.2 | 2026-10-23 | |
| 38 | 48.3% | 65.7 | 2026-09-30 | |
| 39 | 48.3% | 55.9 | 2026-09-02 | |
| 40 | 48.0% | 60.1 | 2026-10-26 | |
| 41 | 47.6% | 65.0 | 2026-10-26 | |
| 42 | 47.4% | 58.6 | 2026-10-26 | |
| 43 | 47.3% | 59.7 | 2026-10-26 | |
| 44 | 46.2% | 57.6 | 2026-08-12 | |
| 45 | 46.0% | 50.8 | 2026-09-28 | |
| 46 | 45.8% | 50.9 | 2026-09-28 | |
| 47 | 45.7% | 55.5 | 2026-09-21 | |
| 48 | 45.6% | 56.7 | 2026-10-26 | |
| 49 | 45.2% | 56.9 | 2026-08-13 | |
| 50 | 45.1% | 53.9 | 2026-10-19 | |
| 51 | 44.9% | 56.3 | 2026-06-01 | |
| 52 | 42.7% | 58.1 | 2026-09-21 | |
| 53 | 42.4% | 53.7 | 2026-07-16 | |
| 54 | 42.3% | 60.5 | 2026-07-09 | |
| 55 | 42.0% | 53.6 | 2026-10-15 | |
| 56 | 41.8% | 57.0 | 2026-09-21 | |
| 57 | 41.3% | 60.3 | 2026-07-09 | |
| 58 | 41.2% | 56.9 | 2026-07-09 | |
| 59 | 41.0% | 62.2 | 2026-10-12 | |
| 60 | 40.7% | 51.9 | 2026-10-26 |
More knowledge benchmarks · All LLM benchmarks
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Top head-to-heads on AA-Omniscience v1.1: accuracy
Cite as: BenchLeader, “AA-Omniscience v1.1: accuracy leaderboard”, data as of 9 Nov 2026, https://www.benchleader.com/benchmarks/aa_omniscience_accuracy.
AA-Omniscience v1.1: accuracy: questions
- What does AA-Omniscience v1.1: accuracy measure?
- The share of AA-Omniscience questions answered correctly, before any penalty for confident wrong answers. Scores are reported in percent of tasks solved; higher is better.
- What is the top score on AA-Omniscience v1.1: accuracy?
- As of 9 Nov 2026, the highest score on AA-Omniscience v1.1: accuracy is 79.1% by Claude Fable 5.2 (result dated 9 Nov 2026), ahead of Claude Fable 5.1 at 68.4%. Scores come from Artificial Analysis and are re-read daily.
- Which AI model leads AA-Omniscience v1.1: accuracy?
- Claude Fable 5.2 leads AA-Omniscience v1.1: accuracy with 79.1% as of 9 Nov 2026 (result dated 9 Nov 2026), ahead of Claude Fable 5.1 at 68.4%.
- How many models have AA-Omniscience v1.1: accuracy results?
- 132 model configurations have a AA-Omniscience v1.1: accuracy result on BenchLeader, all taken from Artificial Analysis.
- Who runs AA-Omniscience v1.1: accuracy and how often is it updated?
- AA-Omniscience v1.1: accuracy is published by Artificial Analysis. BenchLeader re-reads the published results once a day and records the date each result was published.
- Does AA-Omniscience v1.1: accuracy count toward the BenchLeader Index?
- No. AA-Omniscience v1.1: accuracy is shown for reference but left out of the composite index.