AA-LCR (Artificial Analysis Long Context Reasoning)
Questions requiring reasoning across multiple real documents totaling about 100K tokens. Answers judged by an LLM.
Version 1.0.0 stays available at dataset revision bdae010. Version 1.1 (September 2026) fixed 16 answer keys, so scores differ.
- Level
- University Undergraduates and entry-level professionals
- Scored
- Checked automatically A program checks the result against an answer key, unit tests or the expected final state.
- Answers
- Short answer A number, word or short string matched to a key.
Muse Glimmer leads with 80%
Best score per model as labs report them in their own cards. Labs pick their own settings, so these compare less cleanly than independent runs.
- 80.0
Muse Glimmer
- 79.3 Beam 1.0
- 74.7 Kimi K3
- 73.4
Tencent Hy3
- 72.0
MiniMax-M2.7
- 71.2
Mistral Small 4
- 71.0
Solar Pro 4
- 69.5
MiniMax-M2.5
- 68.7
Qwen3-Max
- 68.7
Qwen3.5 397B-A17B
- 68.3
Qwen 3.6 Plus
- 68.0 Mercury 2.5
- 66.9
Qwen3.5-122B-A10B
- 66.3
Tencent Hy3 preview
- 65.4
Nemotron 3 Ultra
- 64.1
Nemotron 3.5 Bolt 74B-A9B
- 63.9
Step 3.7 Flash
- 62.3
Solar Open 2
- 62.0
MiniMax-M2.1
- 61.0
MiniMax-M2
- 58.3
Nemotron 3 Super
- 57.0
Qwen3.5-Omni-Plus
- 56.2
K-EXAONE 2.0
- 53.5
K-EXAONE
- 52.8 LFM3-1.7B
- 52.4
Nemotron 3.5 Lightning 30B-A3B
- 50.6
EXAONE 4.5 33B
- 41.0
Nemotron 3 Nano Omni 30B-A3B
- 39.1
Nemotron-Cascade 2 30B-A3B
- 35.9
Nemotron 3 Nano 30B-A3B
- 35.0
Solar Open 100B
- 1
Muse Glimmer 80%
- 2 Beam 1.0 79.3%
- 3 Kimi K3 74.7%
- 4
Tencent Hy3 73.4%
- 5
MiniMax-M2.7 72%
- 6
Mistral Small 4 71.2%
- 7
Solar Pro 4 71%
- 8
MiniMax-M2.5 69.5%
- 9
Qwen3-Max 68.7%
- 10
Qwen3.5 397B-A17B 68.7%
- 11
Qwen 3.6 Plus 68.3%
- 12 Mercury 2.5 68%
- 13
Qwen3.5-122B-A10B 66.9%
- 14
Tencent Hy3 preview 66.3%
- 15
Nemotron 3 Ultra 65.4%
- 16
Nemotron 3.5 Bolt 74B-A9B 64.1%
- 17
Step 3.7 Flash 63.9%
- 18
Solar Open 2 62.3%
- 19
MiniMax-M2.1 62%
- 20
MiniMax-M2 61%
- 21
Nemotron 3 Super 58.3%
- 22
Qwen3.5-Omni-Plus 57%
- 23
K-EXAONE 2.0 56.2%
- 24
K-EXAONE 53.5%
- 25 LFM3-1.7B 52.8%
- 26
Nemotron 3.5 Lightning 30B-A3B 52.4%
- 27
EXAONE 4.5 33B 50.6%
- 28
Nemotron 3 Nano Omni 30B-A3B 41%
- 29
Nemotron-Cascade 2 30B-A3B 39.1%
- 30
Nemotron 3 Nano 30B-A3B 35.9%
- 31
Solar Open 100B 35%
| # | Model | Score | Setting | Date | Source |
|---|---|---|---|---|---|
| 1 | | 80% | Aug 2026 | Model card | |
| 2 | Beam 1.0 | 79.3% | Oct 2026 | Model card | |
| 3 | Kimi K3 | 74.7% | Jul 2026 | Model card | |
| 4 | | 73.4% | Jul 2026 | Model card | |
| 5 | | 72% | May 2026 | Model card | |
| 6 | | 71.2% | Mar 2026 | Model card | |
| 7 | | 71% | Aug 2026 | Model card | |
| 8 | | 69.5% | Feb 2026 | Model card | |
| 9 | | 68.7% | Jan 2026 | Model card | |
| 10 | | 68.7% | Feb 2026 | Model card | |
| 11 | | 68.3% | Apr 2026 | Model card | |
| 12 | Mercury 2.5 | 68% | Sep 2026 | Model card | |
| 13 | | 66.9% | Feb 2026 | Model card | |
| 14 | | 66.3% | Apr 2026 | Model card | |
| 15 | | 65.4% | Jun 2026 | Model card | |
| 16 | | 64.1% | Oct 2026 | Model card | |
| 17 | | 63.9% | May 2026 | Model card | |
| 18 | | 62.3% | Jul 2026 | Model card | |
| 19 | | 62% | Dec 2025 | Model card | |
| 20 | | 61% | Oct 2025 | Model card | |
| 21 | | 58.3% | Mar 2026 | Model card | |
| 22 | | 57% | Mar 2026 | Model card | |
| 23 | | 56.2% | Jul 2026 | Model card | |
| 24 | | 53.5% | Dec 2025 | Model card | |
| 25 | LFM3-1.7B | 52.8% | Oct 2026 | Model card | |
| 26 | | 52.4% | Oct 2026 | Model card | |
| 27 | | 50.6% | Apr 2026 | Model card | |
| 28 | | 41% | Apr 2026 | Model card | |
| 29 | | 39.1% | Mar 2026 | Model card | |
| 30 | | 35.9% | Dec 2025 | Model card | |
| 31 | | 35% | Dec 2025 | Model card |
9 models have held number one since its release in Aug 2025
Lab claims count from the day the card came out, independent runs from the model’s release.
Scores over time
All the scores we have, one dot each, so a model tested at several settings appears more than once.
9 labs put it in a launch post in the last six months
Launch posts from every lab that has listed it, one tick per post. Tall colored ticks include it, and short gray ones leave it out.
| Date | Launch post | Score | As the post writes it |
|---|---|---|---|
| 27 Oct 2026 | LFM3-1.7B | 52.8 | AA-LCR |
| 15 Oct 2026 | 64.1 | AA-LCR | |
| 5 Oct 2026 | Beam 1.0 | 79.3 | AA-LCR |
| 8 Sep 2026 | Mercury 2.5 | 68 | AA-LCR (version not stated) |
| 11 Aug 2026 | 52 | AA-LCR | |
| 11 Aug 2026 | 71 | AA-LCR (Artificial Analysis score quoted by Upstage) | |
| 10 Aug 2026 | 80 | AA-LCR | |
| 31 Jul 2026 | 56.2 | AA-LCR | |
| 22 Jul 2026 | 62.3 | AA-LCR | |
| 16 Jul 2026 | Kimi K3 | 74.7 | AA-LCR |
| 2 Jul 2026 | 73.4 | AA-LCR | |
| 4 Jun 2026 | 65.4 | AA-LCR | |
| 29 May 2026 | 63.9 | AA-LCR (avg@16/acc) | |
| 23 Apr 2026 | 66.3 | AA-LCR | |
| 9 Apr 2026 | 50.6 | AA-LCR | |
| 2 Apr 2026 | 68.3 | AA-LCR | |
| 30 Mar 2026 | 57 | AA-LCR | |
| 19 Mar 2026 | 39.1 | AA-LCR | |
| 16 Mar 2026 | 71.2 | LCR [Mistral Small 4 - High] (text: 'AA LCR ... 0.72') | |
| 11 Mar 2026 | 58.3 | AA-LCR | |
| 24 Feb 2026 | 66.9 | AA-LCR | |
| 16 Feb 2026 | 68.7 | AA-LCR | |
| 12 Feb 2026 | 69.5 | AA-LCR | |
| 23 Jan 2026 | 68.7 | AA-LCR | |
| 31 Dec 2025 | 35 | AA-LCR | |
| 31 Dec 2025 | 53.5 | AA-LCR | |
| 23 Dec 2025 | 62 | AA-LCR | |
| 15 Dec 2025 | 35.9 | AA-LCR | |
| 27 Oct 2025 | 61 | AA-LCR |
18 system cards report it, from 7 labs
Besides launch posts, we read the system cards, model cards and technical reports labs publish with a release. They report far more, including safety and frontier-risk tests.
| Date | Document | Score | As the document writes it | Section |
|---|---|---|---|---|
| 19 Oct 2026 | | 80 | AA-LCR, high (Tables 2 and 5) | Capabilities |
| 15 Oct 2026 | | 52.4 | AA-LCR, BF16 acc. (Table 22) | Capabilities |
| 15 Oct 2026 | | 64.1 | AA-LCR, released 24GB checkpoint (Table 7). BF16 67.38 | Capabilities |
| 5 Aug 2026 | | 56.2 | AA-LCR (Table 6, Reasoning mode) | Capabilities |
| 27 Jul 2026 | Kimi K3 technical report | 74.7 | AA-LCR, cited from Artificial Analysis (Table 2) | Capabilities |
| 22 Jul 2026 | | 62.3 | AA-LCR (Table 3) | Capabilities |
| 9 Jun 2026 | | 65.4 | AA-LCR (Table 10) | Capabilities |
| 26 May 2026 | | 61 | AA-LCR, MiniMax-M2 bar, printed label (Figure 9) | Capabilities |
| 26 May 2026 | | 72 | AA-LCR, AA Index v4.0 protocol (Table 4) | Capabilities |
| 26 May 2026 | | 65 | AA-LCR, AA Index v4.0 protocol (Table 4) | Capabilities |
| 27 Apr 2026 | | 41 | AA-LCR (Table 10) | Capabilities |
| 17 Apr 2026 | | 57 | AA-LCR (Table 4) | Capabilities |
| 9 Apr 2026 | | 50.6 | AA-LCR (Table 3, Reasoning mode) | Capabilities |
| 19 Mar 2026 | | 39.1 | AA-LCR (Table 1) | Capabilities |
| 11 Mar 2026 | | 58.3 | AA-LCR (Table 5) | Capabilities |
| 11 Jan 2026 | | 35 | AA-LCR (Table 6) | Capabilities |
| 5 Jan 2026 | | 53.5 | AA-LCR (Table 3, Reasoning mode). Non-reasoning 45.2 (Table 4) | Capabilities |
| 23 Dec 2025 | | 35.9 | AA-LCR, reasoning on (Table 3) | Capabilities |
Versions
We switch the top row to each new version when it comes out. Open it for one row per version. An old version stays in play while people still test it, so whoever first takes it past 85% gets credit for closing it out.
More in Long context
- MRCR v2 In use Multi-round coreference: retrieve the n-th of several similar requests hidden in a long synthetic conversation, up to 1M tokens.
Muse Spark 1.3 98.5%
- LongBench v2 In use 503 multiple-choice questions over 8K-2M-word contexts (QA, dialogue, code repos, structured data). Accuracy. Beam 1.0 66.9%
- GraphWalks In use A graph is given as an edge list in long context. The model answers BFS or parent queries, scored by F1. Claude Fable 5 100%
- OpenAI MRCR v2 In use Models read a long synthetic chat that hides 2, 4 or 8 identical writing requests and must reproduce the response to the i-th one. Scored by mean string match ratio per context bin.
K-EXAONE 2.0 94.4%
- CL-bench In use Model must learn new knowledge from a supplied long context (rules, procedures, data) and solve tasks. Strict LLM-verified rubrics. GPT-5.4 27.9%
- LOCA-Bench In use Agentic tasks whose environment state is scaled to grow context length while task semantics stay fixed. Success rate versus context length. GPT-5.2 21.3%