Rankings / Anthropic
Claude Sonnet 4.5 20250929
released 2025-09-29
BenchAtlas Index
as of 2026-09-11
thinking
rank #79
10 families · 4 categories · medium
32K budget
rank #126
6 families · 3 categories · medium
59K budget
rank #135
5 families · 3 categories · medium
Benchmark evidence
116 results
external indices
| ECI | 48K budget | 146.8 points | independent | Epoch AI Benchmarking Hub |
| ECI | 59K budget | 146.8 points | independent | Epoch AI Benchmarking Hub |
| ECI | 16K budget | 146.8 points | independent | Epoch AI Benchmarking Hub |
| ECI | 32K budget | 146.8 points | independent | Epoch AI Benchmarking Hub |
| ECI | low effort | 146.8 points | independent | Epoch AI Benchmarking Hub |
| ECI | 8K budget | 146.8 points | independent | Epoch AI Benchmarking Hub |
| ECI | 1K budget | 146.8 points | independent | Epoch AI Benchmarking Hub |
| ECI | 2K budget | 146.8 points | independent | Epoch AI Benchmarking Hub |
| ECI | 12K budget | 146.8 points | independent | Epoch AI Benchmarking Hub |
| ECI | 146.8 points | independent | Epoch AI Benchmarking Hub |
factuality
| MASK contamination=Potential contamination warning: This model was evaluated after the public release of MASK, allowing model builder access to the prompts and solutions. | thinking | 96.1 % 95.6–96.7 | independent | Scale Labs |
| MASK contamination=Potential contamination warning: This model was evaluated after the public release of MASK, allowing model builder access to the prompts and solutions. | 86.4 % 84.9–87.9 | independent | Scale Labs | |
| SimpleQA Verified | 59K budget | 30.7 % | independent | Epoch AI Benchmarking Hub 2026-08-27 |
| SimpleQA Verified | 23.7 % | independent | Epoch AI Benchmarking Hub 2026-08-10 | |
| SimpleQA Verified | 59K budget | 23.6 % | independent | Epoch AI Benchmarking Hub 2025-12-09 |
| SimpleQA Verified | 13.0 % | independent | Epoch AI Benchmarking Hub 2025-12-08 |
human preference
| Coding (style control)older version arena=text · category=coding · style_control=true | 1513.3 1508.2–1518.4 | community | LMArena Leaderboard Dataset | |
| Industry Software And It Services (style control)older version arena=text · category=industry_software_and_it_services · style_control=true | 1498.0 1493.7–1502.3 | community | LMArena Leaderboard Dataset | |
| Hard Prompts English (style control)older version arena=text · category=hard_prompts_english · style_control=true | 1490.3 1485.3–1495.2 | community | LMArena Leaderboard Dataset | |
| Expert (style control)older version arena=text · category=expert · style_control=true | 1483.7 1475.5–1491.8 | community | LMArena Leaderboard Dataset | |
| Hard Prompts (style control)older version arena=text · category=hard_prompts · style_control=true | 1483.4 1479.7–1487.1 | community | LMArena Leaderboard Dataset | |
| Longer Query (style control)older version arena=text · category=longer_query · style_control=true | 1482.9 1478.2–1487.6 | community | LMArena Leaderboard Dataset | |
| Multi Turn (style control)older version arena=text · category=multi_turn · style_control=true | 1478.6 1472.8–1484.3 | community | LMArena Leaderboard Dataset | |
| French (style control)older version arena=text · category=french · style_control=true | 1477.3 1462.3–1492.3 | community | LMArena Leaderboard Dataset | |
| Chinese (style control)older version arena=text · category=chinese · style_control=true | 1477.0 1468.3–1485.7 | 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 | 1472.1 1466.3–1477.9 | community | LMArena Leaderboard Dataset | |
| Industry Medicine And Healthcare (style control)older version arena=text · category=industry_medicine_and_healthcare · style_control=true | 1471.9 1462.9–1480.8 | community | LMArena Leaderboard Dataset | |
| English (style control)older version arena=text · category=english · style_control=true | 1466.8 1462.8–1470.8 | community | LMArena Leaderboard Dataset | |
| Industry Legal And Government (style control)older version arena=text · category=industry_legal_and_government · style_control=true | 1464.6 1456.3–1472.8 | community | LMArena Leaderboard Dataset | |
| Spanish (style control)older version arena=text · category=spanish · style_control=true | 1464.5 1451.7–1477.3 | community | LMArena Leaderboard Dataset | |
| Instruction Following (style control)older version arena=text · category=instruction_following · style_control=true | 1462.6 1457.9–1467.3 | 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 | 1461.2 1455.7–1466.7 | community | LMArena Leaderboard Dataset | |
| Exclude Ties (style control)older version arena=text · category=exclude_ties · style_control=true | 1458.9 1455.0–1462.9 | community | LMArena Leaderboard Dataset | |
| Overall (style control) arena=text · category=overall · style_control=true | 1455.1 1452.2–1458.1 | 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 | 1454.0 1448.9–1459.1 | community | LMArena Leaderboard Dataset | |
| Creative Writing (style control)older version arena=text · category=creative_writing · style_control=true | 1453.5 1447.4–1459.7 | community | LMArena Leaderboard Dataset | |
| Russian (style control)older version arena=text · category=russian · style_control=true | 1452.7 1446.0–1459.4 | community | LMArena Leaderboard Dataset | |
| Industry Mathematical (style control)older version arena=text · category=industry_mathematical · style_control=true | 1452.3 1442.6–1462.0 | community | LMArena Leaderboard Dataset | |
| German (style control)older version arena=text · category=german · style_control=true | 1443.8 1427.0–1460.5 | community | LMArena Leaderboard Dataset | |
| Polish (style control)older version arena=text · category=polish · style_control=true | 1442.9 1430.3–1455.5 | 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 | 1442.5 1437.0–1448.1 | community | LMArena Leaderboard Dataset | |
| Non English (style control)older version arena=text · category=non_english · style_control=true | 1440.9 1437.3–1444.5 | community | LMArena Leaderboard Dataset | |
| Math (style control)older version arena=text · category=math · style_control=true | 1427.0 1418.4–1435.5 | community | LMArena Leaderboard Dataset | |
| Korean (style control)older version arena=text · category=korean · style_control=true | 1418.0 1400.5–1435.4 | community | LMArena Leaderboard Dataset | |
| Japanese (style control)older version arena=text · category=japanese · style_control=true | 1412.9 1390.6–1435.2 | community | LMArena Leaderboard Dataset |
knowledge science
| GPQA Diamond | 59K budget | 82.3 % | independent | Epoch AI Benchmarking Hub 2025-10-28 |
| GPQA Diamond | 32K budget | 81.7 % | independent | Epoch AI Benchmarking Hub 2025-10-21 |
| GPQA Diamond implementation=vals-ai | thinking | 81.6 % | independent | Vals AI |
| GPQA Diamond | 16K budget | 78.8 % | independent | Epoch AI Benchmarking Hub 2025-10-28 |
| GPQA Diamond | 73.7 % | independent | Epoch AI Benchmarking Hub 2025-09-29 | |
| Humanity's Last Exam contamination=Potential contamination warning: This model was evaluated after the public release of HLE, allowing model builder access to the prompts and solutions. · implementation=scale | thinking | 13.7 % 12.4–15.1 | independent | Scale Labs |
| Humanity's Last Exam contamination=Potential contamination warning: This model was evaluated after the public release of HLE, allowing model builder access to the prompts and solutions. · implementation=scale | 7.5 % 6.5–8.6 | independent | Scale Labs | |
| MMLU-Pro implementation=vals-ai | thinking | 87.4 % | independent | Vals AI |
long context instruction
| MultiChallenge | thinking | 55.3 % 53.9–56.8 | independent | Scale Labs |
multimodal
| MMMU implementation=vals-ai | thinking | 79.3 % | independent | Vals AI |
| VISTA | thinking | 48.8 % 47.1–50.4 | independent | Scale Labs |
| VISTA | 45.0 % 44.9–45.1 | independent | Scale Labs |
professional
| CaseLaw | thinking | 62.2 % | independent | Vals AI |
| CorpFin | thinking | 62.0 % | independent | Vals AI |
| CorpFin | 60.8 % | independent | Vals AI | |
| LegalBench | thinking | 84.1 % | independent | Vals AI |
| MedQA | thinking | 94.7 % | independent | Vals AI |
| TaxEval | thinking | 73.3 % | independent | Vals AI |
reasoning math
| AIME implementation=vals-ai | thinking | 88.2 % | independent | Vals AI |
| ARC-AGI-1older version split=public_eval · model_type=CoT | thinking · 32K budget | 73.8 % | independent | ARC Prize Leaderboard |
| ARC-AGI-1older version split=semi_private · model_type=CoT | thinking · 32K budget | 63.7 % | independent | ARC Prize Leaderboard |
| ARC-AGI-1older version split=public_eval · model_type=CoT | thinking · 16K budget | 63.6 % | independent | ARC Prize Leaderboard |
| ARC-AGI-1older version split=public_eval · model_type=CoT | thinking · 8K budget | 53.5 % | independent | ARC Prize Leaderboard |
| ARC-AGI-1older version split=semi_private · model_type=CoT | thinking · 16K budget | 48.3 % | independent | ARC Prize Leaderboard |
| ARC-AGI-1older version split=semi_private · model_type=CoT | thinking · 8K budget | 46.5 % | independent | ARC Prize Leaderboard |
| ARC-AGI-1older version split=public_eval · model_type=CoT | thinking · 1K budget | 36.6 % | independent | ARC Prize Leaderboard |
| ARC-AGI-1older version split=public_eval · model_type=Base LLM | 35.4 % | independent | ARC Prize Leaderboard | |
| ARC-AGI-1older version split=semi_private · model_type=CoT | thinking · 1K budget | 31.0 % | independent | ARC Prize Leaderboard |
| ARC-AGI-1older version split=semi_private · model_type=Base LLM | 25.5 % | independent | ARC Prize Leaderboard | |
| ARC-AGI-2 split=public_eval · model_type=CoT | thinking · 32K budget | 14.7 % | independent | ARC Prize Leaderboard |
| ARC-AGI-2 split=semi_private · model_type=CoT | thinking · 32K budget | 13.6 % | independent | ARC Prize Leaderboard |
| ARC-AGI-2 split=semi_private · model_type=CoT | thinking · 8K budget | 6.9 % | independent | ARC Prize Leaderboard |
| ARC-AGI-2 split=semi_private · model_type=CoT | thinking · 16K budget | 6.9 % | independent | ARC Prize Leaderboard |
| ARC-AGI-2 split=public_eval · model_type=CoT | thinking · 16K budget | 6.5 % | independent | ARC Prize Leaderboard |
| ARC-AGI-2 split=semi_private · model_type=CoT | thinking · 1K budget | 5.8 % | independent | ARC Prize Leaderboard |
| ARC-AGI-2 split=public_eval · model_type=CoT | thinking · 8K budget | 4.9 % | independent | ARC Prize Leaderboard |
| ARC-AGI-2 split=semi_private · model_type=Base LLM | 3.8 % | independent | ARC Prize Leaderboard | |
| ARC-AGI-2 split=public_eval · model_type=Base LLM | 3.8 % | independent | ARC Prize Leaderboard | |
| ARC-AGI-2 split=public_eval · model_type=CoT | thinking · 1K budget | 2.1 % | independent | ARC Prize Leaderboard |
| ARC-AGI-2 split=public_eval · model_type=CoT | thinking · 32K budget | 0.8 usd_per_task | independent | ARC Prize Leaderboard |
| ARC-AGI-2 split=semi_private · model_type=CoT | thinking · 32K budget | 0.8 usd_per_task | independent | ARC Prize Leaderboard |
| ARC-AGI-1older version split=semi_private · model_type=CoT | thinking · 32K budget | 0.5 usd_per_task | independent | ARC Prize Leaderboard |
| ARC-AGI-1older version split=public_eval · model_type=CoT | thinking · 32K budget | 0.4 usd_per_task | independent | ARC Prize Leaderboard |
| ARC-AGI-2 split=public_eval · model_type=CoT | thinking · 16K budget | 0.4 usd_per_task | independent | ARC Prize Leaderboard |
| ARC-AGI-2 split=semi_private · model_type=CoT | thinking · 16K budget | 0.3 usd_per_task | independent | ARC Prize Leaderboard |
| ARC-AGI-1older version split=semi_private · model_type=CoT | thinking · 16K budget | 0.3 usd_per_task | independent | ARC Prize Leaderboard |
| ARC-AGI-1older version split=public_eval · model_type=CoT | thinking · 16K budget | 0.2 usd_per_task | independent | ARC Prize Leaderboard |
| ARC-AGI-2 split=public_eval · model_type=CoT | thinking · 8K budget | 0.2 usd_per_task | independent | ARC Prize Leaderboard |
| ARC-AGI-2 split=semi_private · model_type=CoT | thinking · 8K budget | 0.2 usd_per_task | independent | ARC Prize Leaderboard |
| ARC-AGI-1older version split=semi_private · model_type=CoT | thinking · 8K budget | 0.2 usd_per_task | independent | ARC Prize Leaderboard |
| ARC-AGI-1older version split=public_eval · model_type=CoT | thinking · 8K budget | 0.2 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=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 | |
| EnigmaEval contamination=Potential contamination warning: This model was evaluated after the public release of EnigmaEval, allowing model builder access to the prompts and solutions. | thinking | 6.0 % 4.7–7.3 | independent | Scale Labs |
| EnigmaEval contamination=Potential contamination warning: This model was evaluated after the public release of EnigmaEval, allowing model builder access to the prompts and solutions. | 3.4 % 2.4–4.4 | independent | Scale Labs | |
| FrontierMath | 32K budget | 15.2 % | independent | Epoch AI Benchmarking Hub 2025-11-16 |
| FrontierMath | 59K budget | 13.5 % | independent | Epoch AI Benchmarking Hub 2025-11-13 |
| FrontierMath | 9.3 % | independent | Epoch AI Benchmarking Hub 2025-11-16 | |
| FrontierMath Tier 4older version | 32K budget | 4.2 % | independent | Epoch AI Benchmarking Hub 2025-10-22 |
| FrontierMath Tier 4older version | 2.1 % | independent | Epoch AI Benchmarking Hub 2025-09-29 | |
| MATH Level 5 | 32K budget | 97.7 % | independent | Epoch AI Benchmarking Hub 2025-10-21 |
| OTIS Mock AIME 2024–2025 | 32K budget | 77.8 % | independent | Epoch AI Benchmarking Hub 2025-10-21 |
| OTIS Mock AIME 2024–2025 | 59K budget | 77.8 % | independent | Epoch AI Benchmarking Hub 2025-10-28 |
| OTIS Mock AIME 2024–2025 | 16K budget | 71.1 % | independent | Epoch AI Benchmarking Hub 2025-10-28 |
| OTIS Mock AIME 2024–2025 | 35.6 % | independent | Epoch AI Benchmarking Hub 2025-09-29 |
Agent + model results
systems, not bare-model scores
| agent + model mini-SWE-agent + Claude Sonnet 4.5 20250929 | SWE-bench bash-only | 71.4 % | unverified | SWE-bench Leaderboard |
| agent + model mini-SWE-agent + Claude Sonnet 4.5 20250929 | SWE-bench Verified | 71.4 % | unverified | SWE-bench Leaderboard |
| agent + model Epoch Inspect harness + Claude Sonnet 4.5 20250929 | SWE-bench Verified | 71.3 % | independent | Epoch AI Benchmarking Hub |
| agent + model mini-SWE-agent + Claude Sonnet 4.5 20250929 | SWE-bench bash-only | 70.6 % | community | SWE-bench Leaderboard |
| agent + model mini-SWE-agent + Claude Sonnet 4.5 20250929 | SWE-bench Verified | 70.6 % | community | SWE-bench Leaderboard |
| agent + model mini-SWE-agent + Claude Sonnet 4.5 20250929 | SWE-bench Multilingual | 67.0 % | community | SWE-bench Leaderboard |
| agent + model mini-SWE-agent + Claude Sonnet 4.5 20250929 | SWE-bench Multilingual | 0.7 usd_per_task | community | SWE-bench Leaderboard |
| agent + model mini-SWE-agent + Claude Sonnet 4.5 20250929 | SWE-bench Verified | 0.7 usd_per_task | unverified | SWE-bench Leaderboard |
| agent + model mini-SWE-agent + Claude Sonnet 4.5 20250929 | SWE-bench bash-only | 0.7 usd_per_task | unverified | SWE-bench Leaderboard |
| agent + model mini-SWE-agent + Claude Sonnet 4.5 20250929 | SWE-bench Verified | 0.6 usd_per_task | community | SWE-bench Leaderboard |
| agent + model mini-SWE-agent + Claude Sonnet 4.5 20250929 | SWE-bench bash-only | 0.6 usd_per_task | community | SWE-bench Leaderboard |
| agent + model terminus-2 + Claude Sonnet 4.5 20250929 | Terminal-Bench 2.0 | 42.8 % | community | Terminal-Bench Leaderboard |
| agent + model OpenHands + Claude Sonnet 4.5 20250929 | Terminal-Bench 2.0 | 42.6 % | community | Terminal-Bench Leaderboard |
| agent + model mini-SWE-agent + Claude Sonnet 4.5 20250929 | Terminal-Bench 2.0 | 42.5 % | community | Terminal-Bench Leaderboard |
| agent + model Claude Code + Claude Sonnet 4.5 20250929 | Terminal-Bench 2.0 | 40.1 % | community | Terminal-Bench Leaderboard |
These scores measure the whole agent system (scaffold, tools, budgets) — they are never merged into the bare model’s numbers.