Rankings / Anthropic
Claude Opus 4.8
released 2026-05-28
BenchAtlas Index
as of 2026-09-11
max effort
rank #12
7 families · 4 categories · medium
max effort
rank #13
7 families · 4 categories · medium
low effort
rank #54
4 families · 3 categories · medium
Benchmark evidence
93 results
agentic coding
| Release 2026-06-25 tasks_counted=3 · livebench_version=2026-06-25 | xhigh effort | 56.1 % | independent | LiveBench |
| Release 2026-06-25 tasks_counted=3 · livebench_version=2026-06-25 | max effort | 50.5 % | independent | LiveBench |
| τ²-Bench | max effort | 94.4 % | independent | Artificial Analysis |
| τ²-Bench subset=banking | max effort | 34.2 % | independent | Artificial Analysis |
coding
| Release 2026-06-25 tasks_counted=2 · livebench_version=2026-06-25 | max effort | 81.8 % | independent | LiveBench |
| Release 2026-06-25 tasks_counted=2 · livebench_version=2026-06-25 | xhigh effort | 79.3 % | independent | LiveBench |
| SciCode | max effort | 54.4 % | independent | Artificial Analysis |
data analysis
| Release 2026-06-25 tasks_counted=3 · livebench_version=2026-06-25 | xhigh effort | 78.3 % | independent | LiveBench |
| Release 2026-06-25 tasks_counted=3 · livebench_version=2026-06-25 | max effort | 66.0 % | independent | LiveBench |
external indices
| AA Coding Index | max effort | 74.3 points | independent | Artificial Analysis |
| Intelligence Index v4.1 | max effort | 42.0 points | independent | Artificial Analysis |
| ECI | max effort | 158.2 points | independent | Epoch AI Benchmarking Hub |
| ECI | 24K budget | 158.2 points | independent | Epoch AI Benchmarking Hub |
| ECI | no reasoning | 158.2 points | independent | Epoch AI Benchmarking Hub |
| ECI | low effort | 158.2 points | independent | Epoch AI Benchmarking Hub |
| ECI | 158.2 points | independent | Epoch AI Benchmarking Hub | |
| ECI | high effort | 158.2 points | independent | Epoch AI Benchmarking Hub |
| ECI | xhigh effort | 158.2 points | independent | Epoch AI Benchmarking Hub |
| ECI | medium effort | 158.2 points | independent | Epoch AI Benchmarking Hub |
| Vals Index | max effort | 60.9 points | independent | Vals AI |
factuality
| SimpleQA Verified | max effort | 53.0 % | independent | Epoch AI Benchmarking Hub 2026-08-27 |
| SimpleQA Verified | max effort | 39.5 % | independent | Epoch AI Benchmarking Hub 2026-05-29 |
human preference
| Coding (style control)older version arena=text · category=coding · style_control=true | 1527.3 1520.9–1533.8 | community | LMArena Leaderboard Dataset | |
| Chinese (style control)older version arena=text · category=chinese · style_control=true | 1523.4 1511.5–1535.3 | community | LMArena Leaderboard Dataset | |
| Industry Software And It Services (style control)older version arena=text · category=industry_software_and_it_services · style_control=true | 1515.1 1509.4–1520.8 | community | LMArena Leaderboard Dataset | |
| Expert (style control)older version arena=text · category=expert · style_control=true | 1514.5 1505.6–1523.4 | community | LMArena Leaderboard Dataset | |
| French (style control)older version arena=text · category=french · style_control=true | 1504.4 1488.7–1520.1 | community | LMArena Leaderboard Dataset | |
| Hard Prompts English (style control)older version arena=text · category=hard_prompts_english · style_control=true | 1504.4 1498.1–1510.6 | community | LMArena Leaderboard Dataset | |
| Hard Prompts (style control)older version arena=text · category=hard_prompts · style_control=true | 1503.2 1498.1–1508.2 | community | LMArena Leaderboard Dataset | |
| Longer Query (style control)older version arena=text · category=longer_query · style_control=true | 1499.5 1493.7–1505.2 | community | LMArena Leaderboard Dataset | |
| Industry Life And Physical And Social Science (style control)older version arena=text · category=industry_life_and_physical_and_social_science · style_control=true | 1499.2 1491.7–1506.6 | community | LMArena Leaderboard Dataset | |
| Industry Medicine And Healthcare (style control)older version arena=text · category=industry_medicine_and_healthcare · style_control=true | 1497.4 1486.7–1508.1 | community | LMArena Leaderboard Dataset | |
| Multi Turn (style control)older version arena=text · category=multi_turn · style_control=true | 1495.3 1487.8–1502.7 | community | LMArena Leaderboard Dataset | |
| Industry Legal And Government (style control)older version arena=text · category=industry_legal_and_government · style_control=true | 1494.6 1484.4–1504.7 | community | LMArena Leaderboard Dataset | |
| Industry Business And Management And Financial Operations (style control)older version arena=text · category=industry_business_and_management_and_financial_operations · style_control=true | 1488.3 1481.2–1495.4 | community | LMArena Leaderboard Dataset | |
| Industry Mathematical (style control)older version arena=text · category=industry_mathematical · style_control=true | 1487.1 1474.9–1499.4 | community | LMArena Leaderboard Dataset | |
| Russian (style control)older version arena=text · category=russian · style_control=true | 1486.8 1477.7–1495.9 | community | LMArena Leaderboard Dataset | |
| Polish (style control)older version arena=text · category=polish · style_control=true | 1482.8 1463.2–1502.4 | community | LMArena Leaderboard Dataset | |
| Exclude Ties (style control)older version arena=text · category=exclude_ties · style_control=true | 1482.4 1476.8–1488.0 | community | LMArena Leaderboard Dataset | |
| English (style control)older version arena=text · category=english · style_control=true | 1479.6 1474.1–1485.1 | community | LMArena Leaderboard Dataset | |
| Instruction Following (style control)older version arena=text · category=instruction_following · style_control=true | 1476.9 1470.9–1482.8 | community | LMArena Leaderboard Dataset | |
| German (style control)older version arena=text · category=german · style_control=true | 1475.6 1454.8–1496.5 | community | LMArena Leaderboard Dataset | |
| Math (style control)older version arena=text · category=math · style_control=true | 1474.0 1461.5–1486.5 | community | LMArena Leaderboard Dataset | |
| Overall (style control) arena=text · category=overall · style_control=true | 1472.8 1468.6–1477.1 | community | LMArena Leaderboard Dataset | |
| Industry Writing And Literature And Language (style control)older version arena=text · category=industry_writing_and_literature_and_language · style_control=true | 1469.0 1462.4–1475.5 | community | LMArena Leaderboard Dataset | |
| Spanish (style control)older version arena=text · category=spanish · style_control=true | 1468.0 1451.5–1484.5 | community | LMArena Leaderboard Dataset | |
| Creative Writing (style control)older version arena=text · category=creative_writing · style_control=true | 1465.3 1457.9–1472.7 | community | LMArena Leaderboard Dataset | |
| Non English (style control)older version arena=text · category=non_english · style_control=true | 1462.9 1457.7–1468.1 | community | LMArena Leaderboard Dataset | |
| Industry Entertainment And Sports And Media (style control)older version arena=text · category=industry_entertainment_and_sports_and_media · style_control=true | 1455.5 1448.7–1462.3 | community | LMArena Leaderboard Dataset | |
| Korean (style control)older version arena=text · category=korean · style_control=true | 1448.5 1426.7–1470.4 | community | LMArena Leaderboard Dataset | |
| Japanese (style control)older version arena=text · category=japanese · style_control=true | 1448.0 1423.0–1473.0 | community | LMArena Leaderboard Dataset |
knowledge science
| GPQA Diamond implementation=vals-ai | max effort | 92.4 % | independent | Vals AI |
| GPQA Diamond implementation=artificial-analysis | max effort | 92.0 % | independent | Artificial Analysis |
| GPQA Diamond | max effort | 91.0 % | independent | Epoch AI Benchmarking Hub 2026-06-07 |
| GPQA Diamond | low effort | 88.4 % | independent | Epoch AI Benchmarking Hub 2026-08-06 |
| GPQA Diamond | no reasoning | 85.3 % | independent | Epoch AI Benchmarking Hub 2026-08-06 |
| Humanity's Last Exam implementation=artificial-analysis | max effort | 48.7 % | independent | Artificial Analysis |
| MMLU-Pro implementation=vals-ai | max effort | 89.6 % | independent | Vals AI |
language
| Release 2026-06-25 tasks_counted=3 · livebench_version=2026-06-25 | xhigh effort | 81.4 % | independent | LiveBench |
| Release 2026-06-25 tasks_counted=3 · livebench_version=2026-06-25 | max effort | 79.7 % | independent | LiveBench |
long context instruction
| AA-LCR | max effort | 77.7 % | independent | Artificial Analysis |
| IFBench | max effort | 62.2 % | independent | Artificial Analysis |
| Release 2026-06-25 tasks_counted=4 · livebench_version=2026-06-25 | xhigh effort | 72.4 % | independent | LiveBench |
| Release 2026-06-25 tasks_counted=4 · livebench_version=2026-06-25 | max effort | 72.0 % | independent | LiveBench |
multimodal
| MMMU implementation=vals-ai | max effort | 86.6 % | independent | Vals AI |
professional
| CorpFin | max effort | 66.7 % | independent | Vals AI |
| LegalBench | max effort | 83.6 % | independent | Vals AI |
| TaxEval | max effort | 75.6 % | independent | Vals AI |
reasoning math
| ARC-AGI-1older version split=semi_private · model_type=CoT | max effort | 92.5 % | independent | ARC Prize Leaderboard |
| ARC-AGI-1older version split=semi_private · model_type=CoT | high effort | 92.0 % | independent | ARC Prize Leaderboard |
| ARC-AGI-1older version split=semi_private · model_type=CoT | medium effort | 91.5 % | independent | ARC Prize Leaderboard |
| ARC-AGI-1older version split=semi_private · model_type=CoT | low effort | 88.0 % | independent | ARC Prize Leaderboard |
| ARC-AGI-2 split=semi_private · model_type=CoT | high effort | 72.1 % | independent | ARC Prize Leaderboard |
| ARC-AGI-2 split=semi_private · model_type=CoT | medium effort | 71.7 % | independent | ARC Prize Leaderboard |
| ARC-AGI-2 split=semi_private · model_type=CoT | low effort | 62.2 % | independent | ARC Prize Leaderboard |
| ARC-AGI-2 split=semi_private · model_type=CoT | high effort | 2.7 usd_per_task | independent | ARC Prize Leaderboard |
| ARC-AGI-2 split=semi_private · model_type=CoT | medium effort | 2.4 usd_per_task | independent | ARC Prize Leaderboard |
| ARC-AGI-1older version split=semi_private · model_type=CoT | max effort | 2.3 usd_per_task | independent | ARC Prize Leaderboard |
| ARC-AGI-2 split=semi_private · model_type=CoT | low effort | 1.7 usd_per_task | independent | ARC Prize Leaderboard |
| ARC-AGI-3older version split=semi_private · model_type=CoT | high effort | 1.5 % | independent | ARC Prize Leaderboard |
| ARC-AGI-1older version split=semi_private · model_type=CoT | high effort | 1.0 usd_per_task | independent | ARC Prize Leaderboard |
| ARC-AGI-1older version split=semi_private · model_type=CoT | medium effort | 0.9 usd_per_task | independent | ARC Prize Leaderboard |
| ARC-AGI-1older version split=semi_private · model_type=CoT | low effort | 0.7 usd_per_task | independent | ARC Prize Leaderboard |
| EnigmaEval | xhigh effort | 23.5 % 21.1–25.9 | independent | Scale Labs |
| FrontierMath | max effort | 47.2 % | independent | Epoch AI Benchmarking Hub 2026-06-08 |
| FrontierMath Tier 4older version | max effort | 31.3 % | independent | Epoch AI Benchmarking Hub 2026-06-08 |
| Release 2026-06-25 tasks_counted=4 · livebench_version=2026-06-25 | xhigh effort | 95.3 % | independent | LiveBench |
| Release 2026-06-25 tasks_counted=4 · livebench_version=2026-06-25 | max effort | 94.3 % | independent | LiveBench |
| Release 2026-06-25 tasks_counted=4 · livebench_version=2026-06-25 | xhigh effort | 89.7 % | independent | LiveBench |
| Release 2026-06-25 tasks_counted=4 · livebench_version=2026-06-25 | max effort | 89.2 % | independent | LiveBench |
| OTIS Mock AIME 2024–2025 | max effort | 98.3 % | independent | Epoch AI Benchmarking Hub 2026-06-07 |
| OTIS Mock AIME 2024–2025 | low effort | 97.8 % | independent | Epoch AI Benchmarking Hub 2026-08-06 |
| OTIS Mock AIME 2024–2025 | no reasoning | 84.4 % | independent | Epoch AI Benchmarking Hub 2026-08-06 |
Agent + model results
systems, not bare-model scores
| agent + model Artificial Analysis harness + Claude Opus 4.8 | Terminal-Bench 2.1 | 84.6 % | independent | Artificial Analysis |
| agent + model Claude Code + Claude Opus 4.8 | Terminal-Bench 2.1 | 78.9 % | community | Terminal-Bench Leaderboard |
| agent + model terminus-2 + Claude Opus 4.8 | Terminal-Bench 2.1 | 74.6 % | community | Terminal-Bench Leaderboard |
| agent + model Artificial Analysis harness + Claude Opus 4.8 | Terminal-Bench Hard | 58.3 % | independent | Artificial Analysis |
These scores measure the whole agent system (scaffold, tools, budgets) — they are never merged into the bare model’s numbers.
