Rankings / Anthropic
Claude Sonnet 4 20250514
released 2025-05-14
BenchAtlas Index
as of 2026-09-11
thinking
rank #192
8 families · 4 categories · medium
base configuration
rank #289
8 families · 4 categories · medium
Benchmark evidence
82 results
external indices
| ECI | 141.7 points | independent | Epoch AI Benchmarking Hub | |
| ECI | 2K budget | 141.7 points | independent | Epoch AI Benchmarking Hub |
| ECI | 59K budget | 141.7 points | independent | Epoch AI Benchmarking Hub |
| ECI | 32K budget | 141.7 points | independent | Epoch AI Benchmarking Hub |
| ECI | 16K budget | 141.7 points | independent | Epoch AI Benchmarking Hub |
| ECI | 8K budget | 141.7 points | independent | Epoch AI Benchmarking Hub |
| ECI | 1K budget | 141.7 points | independent | Epoch AI Benchmarking Hub |
| ECI | 12K budget | 141.7 points | independent | Epoch AI Benchmarking Hub |
human preference
| Coding (style control)older version arena=text · category=coding · style_control=true | 1449.9 1442.5–1457.3 | community | LMArena Leaderboard Dataset | |
| Industry Software And It Services (style control)older version arena=text · category=industry_software_and_it_services · style_control=true | 1428.6 1422.5–1434.7 | community | LMArena Leaderboard Dataset | |
| Longer Query (style control)older version arena=text · category=longer_query · style_control=true | 1427.6 1420.3–1434.9 | community | LMArena Leaderboard Dataset | |
| French (style control)older version arena=text · category=french · style_control=true | 1427.5 1402.3–1452.6 | community | LMArena Leaderboard Dataset | |
| Hard Prompts English (style control)older version arena=text · category=hard_prompts_english · style_control=true | 1422.5 1415.3–1429.8 | community | LMArena Leaderboard Dataset | |
| Industry Medicine And Healthcare (style control)older version arena=text · category=industry_medicine_and_healthcare · style_control=true | 1420.0 1407.0–1433.0 | community | LMArena Leaderboard Dataset | |
| Hard Prompts (style control)older version arena=text · category=hard_prompts · style_control=true | 1418.7 1413.1–1424.2 | community | LMArena Leaderboard Dataset | |
| Industry Legal And Government (style control)older version arena=text · category=industry_legal_and_government · style_control=true | 1409.7 1397.6–1421.8 | 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 | 1409.7 1401.6–1417.7 | community | LMArena Leaderboard Dataset | |
| Multi Turn (style control)older version arena=text · category=multi_turn · style_control=true | 1409.5 1401.5–1417.4 | community | LMArena Leaderboard Dataset | |
| Chinese (style control)older version arena=text · category=chinese · style_control=true | 1405.3 1393.8–1416.8 | community | LMArena Leaderboard Dataset | |
| Expert (style control)older version arena=text · category=expert · style_control=true | 1401.0 1387.7–1414.3 | community | LMArena Leaderboard Dataset | |
| Russian (style control)older version arena=text · category=russian · style_control=true | 1399.6 1389.1–1410.1 | community | LMArena Leaderboard Dataset | |
| Spanish (style control)older version arena=text · category=spanish · style_control=true | 1398.7 1378.1–1419.2 | community | LMArena Leaderboard Dataset | |
| English (style control)older version arena=text · category=english · style_control=true | 1395.6 1390.0–1401.2 | community | LMArena Leaderboard Dataset | |
| Instruction Following (style control)older version arena=text · category=instruction_following · style_control=true | 1395.5 1388.9–1402.1 | community | LMArena Leaderboard Dataset | |
| Industry Mathematical (style control)older version arena=text · category=industry_mathematical · style_control=true | 1393.0 1380.5–1405.4 | community | LMArena Leaderboard Dataset | |
| German (style control)older version arena=text · category=german · style_control=true | 1391.3 1372.5–1410.1 | community | LMArena Leaderboard Dataset | |
| Overall (style control) arena=text · category=overall · style_control=true | 1390.4 1386.0–1394.8 | community | LMArena Leaderboard Dataset | |
| Math (style control)older version arena=text · category=math · style_control=true | 1389.8 1378.1–1401.6 | 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 | 1389.7 1382.6–1396.8 | community | LMArena Leaderboard Dataset | |
| Polish (style control)older version arena=text · category=polish · style_control=true | 1388.2 1376.2–1400.2 | community | LMArena Leaderboard Dataset | |
| Creative Writing (style control)older version arena=text · category=creative_writing · style_control=true | 1387.0 1378.1–1395.8 | 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 | 1386.8 1378.8–1394.7 | community | LMArena Leaderboard Dataset | |
| Non English (style control)older version arena=text · category=non_english · style_control=true | 1380.7 1375.4–1385.9 | 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 | 1374.7 1367.0–1382.5 | community | LMArena Leaderboard Dataset | |
| Exclude Ties (style control)older version arena=text · category=exclude_ties · style_control=true | 1369.6 1363.8–1375.4 | community | LMArena Leaderboard Dataset | |
| Korean (style control)older version arena=text · category=korean · style_control=true | 1357.8 1337.4–1378.2 | community | LMArena Leaderboard Dataset | |
| Japanese (style control)older version arena=text · category=japanese · style_control=true | 1355.1 1335.1–1375.1 | community | LMArena Leaderboard Dataset |
knowledge science
| GPQA Diamond | 32K budget | 78.3 % | independent | Epoch AI Benchmarking Hub 2025-05-22 |
| GPQA Diamond | 59K budget | 77.8 % | independent | Epoch AI Benchmarking Hub 2025-05-26 |
| GPQA Diamond | 16K budget | 75.8 % | independent | Epoch AI Benchmarking Hub 2025-05-22 |
| GPQA Diamond implementation=vals-ai | thinking | 75.0 % | independent | Vals AI |
| GPQA Diamond implementation=vals-ai | 69.4 % | independent | Vals AI | |
| GPQA Diamond | 66.7 % | independent | Epoch AI Benchmarking Hub 2025-05-22 | |
| MMLU-Pro implementation=vals-ai | thinking | 83.9 % | independent | Vals AI |
| MMLU-Pro implementation=vals-ai | 79.4 % | independent | Vals AI |
multimodal
| MMMU implementation=vals-ai | thinking | 74.9 % | independent | Vals AI |
| MMMU implementation=vals-ai | 72.4 % | independent | Vals AI |
professional
| CorpFin | thinking | 61.2 % | independent | Vals AI |
| CorpFin | 54.7 % | independent | Vals AI | |
| LegalBench | 83.0 % | independent | Vals AI | |
| LegalBench | thinking | 82.1 % | independent | Vals AI |
| MedQA | thinking | 92.7 % | independent | Vals AI |
| MedQA | 90.3 % | independent | Vals AI | |
| TaxEval | thinking | 72.0 % | independent | Vals AI |
| TaxEval | 69.6 % | independent | Vals AI |
reasoning math
| AIME implementation=vals-ai | thinking | 76.3 % | independent | Vals AI |
| AIME implementation=vals-ai | 38.5 % | independent | Vals AI | |
| ARC-AGI-1older version split=public_eval · model_type=Base LLM | 33.0 % | independent | ARC Prize Leaderboard | |
| ARC-AGI-1older version split=public_eval · model_type=CoT | thinking · 1K budget | 31.3 % | independent | ARC Prize Leaderboard |
| ARC-AGI-1older version split=semi_private · model_type=CoT | thinking · 1K budget | 28.0 % | independent | ARC Prize Leaderboard |
| ARC-AGI-1older version split=semi_private · model_type=Base LLM | 23.8 % | independent | ARC Prize Leaderboard | |
| ARC-AGI-2 split=public_eval · model_type=Base LLM | 2.1 % | independent | ARC Prize Leaderboard | |
| ARC-AGI-2 split=semi_private · model_type=Base LLM | 1.3 % | independent | ARC Prize Leaderboard | |
| ARC-AGI-2 split=public_eval · model_type=CoT | thinking · 1K budget | 1.3 % | independent | ARC Prize Leaderboard |
| ARC-AGI-2 split=semi_private · model_type=CoT | thinking · 1K budget | 0.8 % | independent | ARC Prize Leaderboard |
| ARC-AGI-2 split=public_eval · model_type=CoT | thinking · 1K budget | 0.1 usd_per_task | independent | ARC Prize Leaderboard |
| ARC-AGI-2 split=semi_private · model_type=CoT | thinking · 1K budget | 0.1 usd_per_task | independent | ARC Prize Leaderboard |
| ARC-AGI-2 split=public_eval · model_type=Base LLM | 0.1 usd_per_task | independent | ARC Prize Leaderboard | |
| ARC-AGI-2 split=semi_private · model_type=Base LLM | 0.1 usd_per_task | independent | ARC Prize Leaderboard | |
| ARC-AGI-1older version split=semi_private · model_type=CoT | thinking · 1K budget | 0.1 usd_per_task | independent | ARC Prize Leaderboard |
| ARC-AGI-1older version split=public_eval · model_type=CoT | thinking · 1K budget | 0.1 usd_per_task | independent | ARC Prize Leaderboard |
| ARC-AGI-1older version split=semi_private · model_type=Base LLM | 0.1 usd_per_task | independent | ARC Prize Leaderboard | |
| ARC-AGI-1older version split=public_eval · model_type=Base LLM | 0.1 usd_per_task | independent | ARC Prize Leaderboard | |
| FrontierMath | 4.1 % | independent | Epoch AI Benchmarking Hub 2025-07-04 | |
| FrontierMath Tier 4older version | 0.0 % | independent | Epoch AI Benchmarking Hub 2025-07-01 | |
| MATH-500 implementation=vals-ai | thinking | 93.8 % | independent | Vals AI |
| MATH-500 implementation=vals-ai | 90.3 % | independent | Vals AI | |
| MATH Level 5 | 84.4 % | independent | Epoch AI Benchmarking Hub 2025-05-22 | |
| OTIS Mock AIME 2024–2025 | 32K budget | 71.1 % | independent | Epoch AI Benchmarking Hub 2025-05-22 |
| OTIS Mock AIME 2024–2025 | 59K budget | 68.9 % | independent | Epoch AI Benchmarking Hub 2025-05-23 |
| OTIS Mock AIME 2024–2025 | 16K budget | 53.3 % | independent | Epoch AI Benchmarking Hub 2025-05-22 |
| OTIS Mock AIME 2024–2025 | 28.9 % | independent | Epoch AI Benchmarking Hub 2025-05-22 |
Agent + model results
systems, not bare-model scores
| agent + model EPAM AI/Run Developer Agent v20250719 + Claude Sonnet 4 20250514 | SWE-bench Verified | 76.8 % | unverified | SWE-bench Leaderboard |
| agent + model Harness AI + Claude Sonnet 4 20250514 | SWE-bench Verified | 74.8 % | unverified | SWE-bench Leaderboard |
| agent + model Artemis Agent v2 (2025-09-24) + Claude Sonnet 4 20250514 | SWE-bench Verified | 57.0 % | unverified | SWE-bench Leaderboard |
These scores measure the whole agent system (scaffold, tools, budgets) — they are never merged into the bare model’s numbers.
