AA-LCR 1.1
Step 5 Preview 88.3% leads since Sep 2026 In use Models answer 100 questions that need reasoning across sets of real documents of about 100K tokens. An LLM equality checker with a fixed system prompt compares each answer with the key.
Version 1.1 corrects 16 answer keys and adds a judge system prompt. Questions and documents are unchanged, but the maker says 1.0 and 1.1 scores are not directly comparable.
- 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.
Step 5 Preview leads with 88.3%
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.
- 1 Step 5 Preview 88.3%
- 2
Solar Mini 4 83.3% - 3 Mercury 3 77.7%
- 4
Nemotron 3.5 Super VL 68.6% - 5
Spark-X2.6-4B 67.3%
| # | Model | Score | Setting | Date | Source |
|---|---|---|---|---|---|
| 1 | Step 5 Preview | 88.3% | Sep 2026 | Model card | |
| 2 | Solar Mini 4 | 83.3% | Oct 2026 | Model card | |
| 3 | Mercury 3 | 77.7% | Oct 2026 | Model card | |
| 4 | Nemotron 3.5 Super VL | 68.6% | Oct 2026 | Model card | |
| 5 | Spark-X2.6-4B | 67.3% | Oct 2026 | Model card |
Number one over time
Lab claims count from the day the card came out, independent runs from the model’s release.
The best score passed 85% in Sep 2026
All the scores we have, one dot each, so a model tested at several settings appears more than once.
5 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 |
|---|---|---|---|
| 22 Oct 2026 | Spark-X2.6-4B | 67.3 | AA-LCRv1.1 |
| 19 Oct 2026 | Mercury 3 | 77.7 | AA-LCR v1.1 |
| 15 Oct 2026 | Nemotron 3.5 Super VL | 68.6 | AA-LCR v1.1 |
| 1 Oct 2026 | Solar Mini 4 | 83.3 | AA-LCR (Artificial Analysis score quoted by Upstage) |
| 20 Sep 2026 | Step 5 Preview | 88.3 | AA-LCR v1.1 |
One system card reports it
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 |
|---|---|---|---|---|
| 15 Oct 2026 | Nemotron 3.5 Super VL technical report | 68.6 | AA-LCR v1.1, mean of 16 (Table 10) | 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%