LongBench v2: long-context reasoning is still hard
Answer: LongBench v2 assesses whether LLMs can handle long-context problems that require deep understanding and reasoning. It consists of 503 challenging multiple-choice questions, with contexts ranging from 8k to 2M words.
What LongBench v2 measures
The questions span six major task categories, among them multi-document QA, code repo understanding, and long-dialogue history. The majority of contexts are under 128k words.
Results reported in the README
- Human experts reached only 53.7% accuracy under a 15-minute time constraint.
- The best-performing model answering directly reached 50.1%.
- o1-preview, with longer reasoning, reached 57.7%, surpassing the human baseline by 4%.
The README highlights enhanced reasoning ability and scaling inference-time compute as the way to tackle these long-context challenges.
Same direction from RULER
RULER generates synthetic examples with configurable sequence length. Almost all models fall below its threshold before reaching their claimed context lengths.
Artifacts
See also
Claims
- id: C1 claim: LongBench v2 has 503 multiple-choice questions. source: S1 evidence: "LongBench v2 consists of 503 challenging multiple-choice questions"
- id: C2 claim: Experts scored 53.7% in 15 minutes. source: S1 evidence: "human experts achieving only 53.7% accuracy under a 15-minute time constraint."
- id: C3 claim: The best direct model scored 50.1%. source: S1 evidence: "achieves only 50.1% accuracy."
- id: C4 claim: Most models fail before their claimed length. source: S2 evidence: "Almost all models fall below the threshold before reaching the claimed context lengths."
Sources
- [S1] LongBench v2 README. THUDM LongBench (GitHub). https://github.com/THUDM/LongBench/blob/main/README.md . License: MIT (THUDM/LongBench LICENSE). Accessed 2026-11-09.
- [S2] RULER README. NVIDIA RULER (GitHub). https://github.com/NVIDIA/RULER/blob/main/README.md . License: Apache-2.0 (NVIDIA/RULER LICENSE). Accessed 2026-11-09.
License: this note is CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/). Summary by iinventedlight (AI-assisted). Sources: GitHub repository docs under Apache License 2.0 (https://www.apache.org/licenses/LICENSE-2.0) or MIT License (https://opensource.org/licenses/MIT), as listed per source; copyright notices remain with the original authors. Text was condensed and changed from the originals.
License: CC-BY-4.0 · Summary by iinventedlight (AI-assisted). Sources: THUDM LongBench (GitHub), LongBench v2 README, MIT (THUDM/LongBench LICENSE); NVIDIA RULER (GitHub), RULER README, Apache-2.0 (NVIDIA/RULER LICENSE).
Cite this
iinventedlight. 2026. "LongBench v2: long-context reasoning is still hard." iinventedlight Library, iil:note:8z8t6k79, version of 2026-11-09. https://iinventedlight.com/library/notes/ao-context-longbench-v2/. License: CC-BY-4.0.
@misc{iil_note_8z8t6k79,
author = {{iinventedlight}},
title = {{LongBench v2: long-context reasoning is still hard}},
howpublished = {iinventedlight Library},
year = {2026},
date = {2026-11-09},
url = {https://iinventedlight.com/library/notes/ao-context-longbench-v2/},
note = {Permanent ID iil:note:8z8t6k79. License: CC-BY-4.0.},
}
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For language models and agents: start at /llms.txt | /agents.md | /.well-known/agent-library.json. This page in Markdown: /library/notes/ao-context-longbench-v2.md.