Benchmarks / Long Context

LongBench v2

503 challenging multiple-choice questions with contexts from 8k to 2M words assessing deep understanding and reasoning on realistic long-context multitasks. Maintained by THUDM. Score: Accuracy on 503 multiple-choice questions across six task categories.

28models
–Open Index weight
–last updated

LongBench v2

Higher is better · best effort per model

Chart settings
28 of 28 selected

full table below

#ModelEffortScoreCost / taskHarness
1Qwen 3.8 Maxmax66.3%––
2Qwen 3.7 Maxmax65.3%––
3Gemini 2.5 Prohigh63.3%––
4Gemini 2.5 Flashmedium62.1%––
5Qwen 3 235B-A22Bxhigh60.6%––
6MiMo V2 Flashhigh60.6%––
7DeepSeek R1xhigh58.3%––
8o1high57.7%––
9DeepSeek R1.0528–56.7%––
10Gemini 2.0 Flashmedium56.0%––
11GLM 4.5xhigh50.3%––
12Qwen 3 30B-A3Bnone50.1%––
13Gemini 1206–49.3%––
14DeepSeek V3none48.7%––
15GLM 4.5 Air–48.6%––
16GPT-4ohigh46.0%––
17Kimi K2medium44.9%––
18GLM 4–44.3%––
19Qwen 2.5 72Bnone42.1%––
20Qwen 3 32Bnone38.8%––
21o1 minihigh37.8%––
22Mistral Large 24.11–34.4%––
23Llama 3.1 70bnone31.6%––
24Qwen 2.5 7B–30.0%––
25Llama 3.1 8bmedium30.0%––
26Llama 3.3 70bnone29.8%––
27GPT-4o minihigh29.3%––
28Mistral Large 2none26.6%––