HELM Arabic
Stanford CRFM runs models on 7 Arabic benchmarks in the HELM harness and ranks them by mean score. The tasks are AlGhafa, ArabicMMLU, Arabic EXAMS, MadinahQA, AraTrust, ALRAGE and human-translated MMLU.
Release v1.0.0 came on 2025-12-18 with 29 models. Release v2.2.0 on 2026-06-25 had 41 models. The task list matches OALL v2, but HELM prompts and scores differ. ALRAGE is model-judged.
- Level
- School Students, from grade school to high school
- Scored
- Checked automatically A program checks the result against an answer key, unit tests or the expected final state.
- Answers
- Multiple choice
llm-x-2026-06-07 tops the leaderboard with 92.0
Best score per entry from the benchmark's own leaderboard, read on 2 Nov 2026. Where a model ran with several settings or harnesses, we keep its best. Names in gray aren't in our model list: fine-tunes, agent systems, products and older models. They don't count toward leaders. The best model we track is Claude Opus 4.7, at 84.1.
The newest model with a score here came out in Apr 2026, and nobody has tested a newer one. Among the 20 highest-ranked models on the capability index, these have no score yet:
- GPT-6 Astra
- Claude Opus 5.5
- GPT-6.1 Terra
- GPT-6.1 Sol
- and 16 more
- 92.0 llm-x-2026-06-07
- 88.3 incept-arabic-1
- 87.2 llm_x
- 84.1 Claude Opus 4.7
- 82.5
Gemini 2.5 Flash
- 82.5 GPT-5.4
- 82.3
Gemma 4 31B IT
- 81.7 GPT-5.1
- 81.5 Claude Sonnet 4.6
- 81.4 GPT-4.1
- 80.2
Qwen3.5 397B-A17B
- 80.2 llm_s
- 79.5
Qwen3-235B-A22B-Instruct
- 79.5
Gemini 2.5 Flash-Lite
- 79.1
Llama 4 Maverick
- 79.0
Mistral Large 3
- 79.0 GPT-5.4 Mini
- 78.8 Claude Haiku 4.5
- 78.4
Qwen3-Next-80B-A3B-Instruct
- 77.9
DeepSeek-V3.1
- 77.7
Cohere Command A
- 76.9
Qwen2.5-72B
- 76.8 GPT-4.1 mini
- 76.4
Llama 3.3 70B Instruct
- 75.6
Llama 4 Scout
- 74.7 acegpt-v2-70b-chat
- 73.1
Qwen3.5-9B
- 71.7
Mistral Large 2
- 71.6 acegpt-v2-32b-chat
- 70.8 allam-7b-instruct-preview
- 70.2 GPT-4.1 nano
- 68.2 GPT-5.4 Nano
- 67.4 jais-adapted-70b-chat
- 66.0
Qwen2.5-7B
- 64.5 jais-family-30b-16k-chat
- 64.3 silma-9b-instruct-v1.0
- 63.9 acegpt-v2-8b-chat
- 59.9 jais-adapted-13b-chat
- 53.1 jais-adapted-7b-chat
- 42.4
Falcon3-10B-Instruct
- 37.5
Falcon3-7B-Instruct
- 1 llm-x-2026-06-07 92.0
- 2 incept-arabic-1 88.3
- 3 llm_x 87.2
- 4 Claude Opus 4.7 84.1
- 5
Gemini 2.5 Flash Sep 2025, thinking disabled 82.5
- 6 GPT-5.4 82.5
- 7
Gemma 4 31B IT thinking disabled 82.3
- 8 GPT-5.1 81.7
- 9 Claude Sonnet 4.6 81.5
- 10 GPT-4.1 81.4
- 11
Qwen3.5 397B-A17B thinking disabled 80.2
- 12 llm_s 80.2
- 13
Qwen3-235B-A22B-Instruct Jul 2025 79.5
- 14
Gemini 2.5 Flash-Lite Sep 2025, thinking disabled 79.5
- 15
Llama 4 Maverick 79.1
- 16
Mistral Large 3 79.0
- 17 GPT-5.4 Mini 79.0
- 18 Claude Haiku 4.5 78.8
- 19
Qwen3-Next-80B-A3B-Instruct 78.4
- 20
DeepSeek-V3.1 77.9
- 21
Cohere Command A 77.7
- 22
Qwen2.5-72B 76.9
- 23 GPT-4.1 mini 76.8
- 24
Llama 3.3 70B Instruct 76.4
- 25
Llama 4 Scout 75.6
- 26 acegpt-v2-70b-chat 74.7
- 27
Qwen3.5-9B thinking disabled 73.1
- 28
Mistral Large 2 Nov 2024 71.7
- 29 acegpt-v2-32b-chat 71.6
- 30 allam-7b-instruct-preview 70.8
- 31 GPT-4.1 nano 70.2
- 32 GPT-5.4 Nano 68.2
- 33 jais-adapted-70b-chat 67.4
- 34
Qwen2.5-7B 66.0
- 35 jais-family-30b-16k-chat 64.5
- 36 silma-9b-instruct-v1.0 64.3
- 37 acegpt-v2-8b-chat 63.9
- 38 jais-adapted-13b-chat 59.9
- 39 jais-adapted-7b-chat 53.1
- 40
Falcon3-10B-Instruct 42.4
- 41
Falcon3-7B-Instruct 37.5
| # | Entry | Score | Setting | Date | Source |
|---|---|---|---|---|---|
| 1 | llm-x-2026-06-07 | 92.0 | Jun 2026 | Official leaderboard | |
| 2 | incept-arabic-1 | 88.3 | Official leaderboard | ||
| 3 | llm_x | 87.2 | Official leaderboard | ||
| 4 | Claude Opus 4.7 | 84.1 | Apr 2026 | Official leaderboard | |
| 5 | | 82.5 | thinking disabled | Sep 2025 | Official leaderboard |
| 6 | GPT-5.4 | 82.5 | Mar 2026 | Official leaderboard | |
| 7 | | 82.3 | thinking disabled | Apr 2026 | Official leaderboard |
| 8 | GPT-5.1 | 81.7 | Nov 2025 | Official leaderboard | |
| 9 | Claude Sonnet 4.6 | 81.5 | Feb 2026 | Official leaderboard | |
| 10 | GPT-4.1 | 81.4 | Apr 2025 | Official leaderboard | |
| 11 | | 80.2 | thinking disabled | Feb 2026 | Official leaderboard |
| 12 | llm_s | 80.2 | Official leaderboard | ||
| 13 | | 79.5 | Jul 2025 | Official leaderboard | |
| 14 | | 79.5 | thinking disabled | Sep 2025 | Official leaderboard |
| 15 | | 79.1 | Apr 2025 | Official leaderboard | |
| 16 | | 79.0 | Dec 2025 | Official leaderboard | |
| 17 | GPT-5.4 Mini | 79.0 | Mar 2026 | Official leaderboard | |
| 18 | Claude Haiku 4.5 | 78.8 | Oct 2025 | Official leaderboard | |
| 19 | | 78.4 | Sep 2025 | Official leaderboard | |
| 20 | | 77.9 | Aug 2025 | Official leaderboard | |
| 21 | | 77.7 | Mar 2025 | Official leaderboard | |
| 22 | | 76.9 | Sep 2024 | Official leaderboard | |
| 23 | GPT-4.1 mini | 76.8 | Apr 2025 | Official leaderboard | |
| 24 | | 76.4 | Dec 2024 | Official leaderboard | |
| 25 | | 75.6 | Apr 2025 | Official leaderboard | |
| 26 | acegpt-v2-70b-chat | 74.7 | Official leaderboard | ||
| 27 | | 73.1 | thinking disabled | Feb 2026 | Official leaderboard |
| 28 | | 71.7 | Nov 2024 | Official leaderboard | |
| 29 | acegpt-v2-32b-chat | 71.6 | Official leaderboard | ||
| 30 | allam-7b-instruct-preview | 70.8 | Official leaderboard | ||
| 31 | GPT-4.1 nano | 70.2 | Apr 2025 | Official leaderboard | |
| 32 | GPT-5.4 Nano | 68.2 | Mar 2026 | Official leaderboard | |
| 33 | jais-adapted-70b-chat | 67.4 | Official leaderboard | ||
| 34 | | 66.0 | Sep 2024 | Official leaderboard | |
| 35 | jais-family-30b-16k-chat | 64.5 | Official leaderboard | ||
| 36 | silma-9b-instruct-v1.0 | 64.3 | Official leaderboard | ||
| 37 | acegpt-v2-8b-chat | 63.9 | Official leaderboard | ||
| 38 | jais-adapted-13b-chat | 59.9 | Official leaderboard | ||
| 39 | jais-adapted-7b-chat | 53.1 | Official leaderboard | ||
| 40 | | 42.4 | Dec 2024 | Official leaderboard | |
| 41 | | 37.5 | Dec 2024 | Official leaderboard |
2 models have held number one since its release in Dec 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.
No lab model card reports it yet
We read the headline results of 479 launch posts from 51 labs, and none of them list this benchmark.
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