Rankings / OpenAI
GPT 5.6 Sol
proprietaryreleased 2026-07-09
BenchAtlas Index
as of 2026-09-11
max effort
rank #1
14 families · 5 categories · high
high effort
rank #2
9 families · 5 categories · high
xhigh effort
rank #3
13 families · 5 categories · high
Benchmark evidence
174 results
agentic coding
| Release 2026-06-25 tasks_counted=3 · livebench_version=2026-06-25 | xhigh effort | 56.6 % | independent | LiveBench |
| Release 2026-06-25 tasks_counted=3 · livebench_version=2026-06-25 | max effort | 56.2 % | independent | LiveBench |
| τ²-Bench | max effort | 85.1 % | independent | Artificial Analysis |
| τ²-Bench | xhigh effort | 84.8 % | independent | Artificial Analysis |
| τ²-Bench | high effort | 83.3 % | independent | Artificial Analysis |
| τ²-Bench | medium effort | 81.0 % | independent | Artificial Analysis |
| τ²-Bench | low effort | 76.0 % | independent | Artificial Analysis |
| τ²-Bench subset=banking | max effort | 44.3 % | independent | Artificial Analysis |
| τ²-Bench subset=banking | xhigh effort | 38.1 % | independent | Artificial Analysis |
| τ²-Bench subset=banking | high effort | 36.7 % | independent | Artificial Analysis |
| τ²-Bench subset=banking | medium effort | 36.5 % | independent | Artificial Analysis |
| τ²-Bench subset=banking | low effort | 29.1 % | independent | Artificial Analysis |
| τ²-Bench subset=banking | no reasoning | 19.6 % | independent | Artificial Analysis |
coding
| Release 2026-06-25 tasks_counted=2 · livebench_version=2026-06-25 | max effort | 83.9 % | independent | LiveBench |
| Release 2026-06-25 tasks_counted=2 · livebench_version=2026-06-25 | xhigh effort | 81.8 % | independent | LiveBench |
| SciCode | high effort | 57.8 % | independent | Artificial Analysis |
| SciCode | medium effort | 57.4 % | independent | Artificial Analysis |
| SciCode | xhigh effort | 57.1 % | independent | Artificial Analysis |
| SciCode | max effort | 57.1 % | independent | Artificial Analysis |
| SciCode | low effort | 56.4 % | independent | Artificial Analysis |
| SciCode | no reasoning | 47.1 % | independent | Artificial Analysis |
data analysis
| Release 2026-06-25 tasks_counted=3 · livebench_version=2026-06-25 | xhigh effort | 80.3 % | independent | LiveBench |
| Release 2026-06-25 tasks_counted=3 · livebench_version=2026-06-25 | max effort | 79.8 % | independent | LiveBench |
external indices
factuality
| SimpleQA Verified | max effort | 71.6 % | independent | Epoch AI Benchmarking Hub 2026-07-09 |
| SimpleQA Verified | max effort | 69.7 % | independent | Epoch AI Benchmarking Hub 2026-08-10 |
human preference
| Chinese (style control)older version arena=text · category=chinese · style_control=true | 1533.9 1518.2–1549.6 | community | LMArena Leaderboard Dataset | |
| Expert (style control)older version arena=text · category=expert · style_control=true | 1530.5 1518.3–1542.7 | community | LMArena Leaderboard Dataset | |
| Coding (style control)older version arena=text · category=coding · style_control=true | 1528.6 1520.5–1536.7 | community | LMArena Leaderboard Dataset | |
| Coding (style control)older version arena=text · category=coding · style_control=true | xhigh effort | 1526.1 1504.2–1548.0 | community | LMArena Leaderboard Dataset |
| Hard Prompts English (style control)older version arena=text · category=hard_prompts_english · style_control=true | xhigh effort | 1522.5 1500.1–1544.8 | community | LMArena Leaderboard Dataset |
| Industry Software And It Services (style control)older version arena=text · category=industry_software_and_it_services · style_control=true | 1518.5 1511.4–1525.5 | community | LMArena Leaderboard Dataset | |
| Industry Software And It Services (style control)older version arena=text · category=industry_software_and_it_services · style_control=true | xhigh effort | 1508.7 1490.5–1527.0 | community | LMArena Leaderboard Dataset |
| French (style control)older version arena=text · category=french · style_control=true | 1508.3 1486.0–1530.5 | community | LMArena Leaderboard Dataset | |
| Industry Mathematical (style control)older version arena=text · category=industry_mathematical · style_control=true | 1507.7 1490.6–1524.9 | community | LMArena Leaderboard Dataset | |
| Hard Prompts (style control)older version arena=text · category=hard_prompts · style_control=true | 1506.9 1500.9–1512.8 | community | LMArena Leaderboard Dataset | |
| Hard Prompts English (style control)older version arena=text · category=hard_prompts_english · style_control=true | 1506.7 1498.6–1514.8 | community | LMArena Leaderboard Dataset | |
| Hard Prompts (style control)older version arena=text · category=hard_prompts · style_control=true | xhigh effort | 1504.8 1490.6–1519.0 | community | LMArena Leaderboard Dataset |
| English (style control)older version arena=text · category=english · style_control=true | xhigh effort | 1503.1 1485.3–1520.8 | community | LMArena Leaderboard Dataset |
| Exclude Ties (style control)older version arena=text · category=exclude_ties · style_control=true | xhigh effort | 1498.0 1482.8–1513.2 | community | LMArena Leaderboard Dataset |
| Exclude Ties (style control)older version arena=text · category=exclude_ties · style_control=true | 1496.9 1490.3–1503.5 | 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 | xhigh effort | 1495.8 1469.7–1521.9 | community | LMArena Leaderboard Dataset |
| Longer Query (style control)older version arena=text · category=longer_query · style_control=true | 1495.5 1488.6–1502.4 | community | LMArena Leaderboard Dataset | |
| Industry Legal And Government (style control)older version arena=text · category=industry_legal_and_government · style_control=true | 1495.1 1481.2–1508.9 | 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 | 1490.6 1481.2–1500.1 | community | LMArena Leaderboard Dataset | |
| Russian (style control)older version arena=text · category=russian · style_control=true | 1490.4 1478.0–1502.8 | community | LMArena Leaderboard Dataset | |
| English (style control)older version arena=text · category=english · style_control=true | 1488.7 1481.8–1495.6 | community | LMArena Leaderboard Dataset | |
| Multi Turn (style control)older version arena=text · category=multi_turn · style_control=true | 1487.2 1477.1–1497.4 | community | LMArena Leaderboard Dataset | |
| Longer Query (style control)older version arena=text · category=longer_query · style_control=true | xhigh effort | 1487.0 1468.7–1505.4 | community | LMArena Leaderboard Dataset |
| Instruction Following (style control)older version arena=text · category=instruction_following · style_control=true | 1485.5 1478.0–1493.0 | 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 | 1485.3 1475.2–1495.4 | community | LMArena Leaderboard Dataset | |
| Math (style control)older version arena=text · category=math · style_control=true | 1484.8 1466.7–1502.9 | community | LMArena Leaderboard Dataset | |
| Overall (style control) arena=text · category=overall · style_control=true | xhigh effort | 1484.6 1473.2–1496.1 | 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 | 1484.3 1475.9–1492.8 | community | LMArena Leaderboard Dataset | |
| Overall (style control) arena=text · category=overall · style_control=true | 1483.2 1478.0–1488.3 | community | LMArena Leaderboard Dataset | |
| Instruction Following (style control)older version arena=text · category=instruction_following · style_control=true | xhigh effort | 1482.3 1462.2–1502.5 | 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 | xhigh effort | 1480.4 1457.9–1502.9 | community | LMArena Leaderboard Dataset |
| Industry Medicine And Healthcare (style control)older version arena=text · category=industry_medicine_and_healthcare · style_control=true | 1479.2 1464.3–1494.0 | community | LMArena Leaderboard Dataset | |
| Creative Writing (style control)older version arena=text · category=creative_writing · style_control=true | 1476.7 1467.1–1486.4 | 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 | xhigh effort | 1475.4 1451.2–1499.6 | 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 | 1473.9 1465.2–1482.6 | community | LMArena Leaderboard Dataset | |
| Non English (style control)older version arena=text · category=non_english · style_control=true | 1472.7 1466.6–1478.8 | community | LMArena Leaderboard Dataset | |
| Non English (style control)older version arena=text · category=non_english · style_control=true | xhigh effort | 1463.9 1449.3–1478.6 | community | LMArena Leaderboard Dataset |
| Spanish (style control)older version arena=text · category=spanish · style_control=true | 1452.4 1428.4–1476.4 | community | LMArena Leaderboard Dataset |
knowledge science
| GPQA Diamond implementation=vals-ai | max effort | 95.2 % | independent | Vals AI |
| GPQA Diamond implementation=artificial-analysis | max effort | 94.1 % | independent | Artificial Analysis |
| GPQA Diamond | max effort | 93.5 % | independent | Epoch AI Benchmarking Hub 2026-07-09 |
| GPQA Diamond implementation=artificial-analysis | xhigh effort | 93.1 % | independent | Artificial Analysis |
| GPQA Diamond implementation=artificial-analysis | high effort | 92.8 % | independent | Artificial Analysis |
| GPQA Diamond implementation=artificial-analysis | medium effort | 92.6 % | independent | Artificial Analysis |
| GPQA Diamond | low effort | 89.9 % | independent | Epoch AI Benchmarking Hub 2026-08-07 |
| GPQA Diamond implementation=artificial-analysis | low effort | 89.8 % | independent | Artificial Analysis |
| GPQA Diamond | no reasoning | 82.8 % | independent | Epoch AI Benchmarking Hub 2026-08-07 |
| GPQA Diamond implementation=artificial-analysis | no reasoning | 79.0 % | independent | Artificial Analysis |
| Humanity's Last Exam implementation=artificial-analysis | max effort | 49.5 % | independent | Artificial Analysis |
| Humanity's Last Exam implementation=artificial-analysis | xhigh effort | 47.3 % | independent | Artificial Analysis |
| Humanity's Last Exam implementation=artificial-analysis | high effort | 46.0 % | independent | Artificial Analysis |
| Humanity's Last Exam implementation=artificial-analysis | medium effort | 42.2 % | independent | Artificial Analysis |
| Humanity's Last Exam implementation=artificial-analysis | low effort | 39.4 % | independent | Artificial Analysis |
| Humanity's Last Exam implementation=artificial-analysis | no reasoning | 16.7 % | independent | Artificial Analysis |
| MMLU-Pro implementation=vals-ai | max effort | 89.1 % | independent | Vals AI |
language
| Release 2026-06-25 tasks_counted=3 · livebench_version=2026-06-25 | max effort | 87.7 % | independent | LiveBench |
| Release 2026-06-25 tasks_counted=3 · livebench_version=2026-06-25 | xhigh effort | 85.9 % | independent | LiveBench |
long context instruction
| AA-LCR | max effort | 84.0 % | independent | Artificial Analysis |
| AA-LCR | xhigh effort | 82.3 % | independent | Artificial Analysis |
| AA-LCR | high effort | 81.7 % | independent | Artificial Analysis |
| AA-LCR | medium effort | 80.3 % | independent | Artificial Analysis |
| AA-LCR | low effort | 78.0 % | independent | Artificial Analysis |
| AA-LCR | no reasoning | 62.3 % | independent | Artificial Analysis |
| IFBench | max effort | 72.7 % | independent | Artificial Analysis |
| IFBench | xhigh effort | 71.0 % | independent | Artificial Analysis |
| IFBench | medium effort | 69.6 % | independent | Artificial Analysis |
| IFBench | high effort | 69.2 % | independent | Artificial Analysis |
| IFBench | low effort | 66.5 % | independent | Artificial Analysis |
| Release 2026-06-25 tasks_counted=4 · livebench_version=2026-06-25 | max effort | 71.8 % | independent | LiveBench |
| Release 2026-06-25 tasks_counted=4 · livebench_version=2026-06-25 | xhigh effort | 67.4 % | independent | LiveBench |
multimodal
| MMMU implementation=vals-ai | max effort | 88.8 % | independent | Vals AI |
professional
| CorpFin | max effort | 64.4 % | independent | Vals AI |
| LegalBench | max effort | 87.0 % | independent | Vals AI |
| TaxEval | max effort | 74.8 % | independent | Vals AI |
reasoning math
| ARC-AGI-1older version split=public_eval · model_type=CoT | max effort | 99.0 % | independent | ARC Prize Leaderboard |
| ARC-AGI-1older version split=public_eval · model_type=CoT | xhigh effort | 98.8 % | independent | ARC Prize Leaderboard |
| ARC-AGI-1older version split=semi_private · model_type=CoT | xhigh effort | 97.5 % | independent | ARC Prize Leaderboard |
| ARC-AGI-1older version split=public_eval · model_type=CoT | high effort | 97.3 % | independent | ARC Prize Leaderboard |
| ARC-AGI-1older version split=semi_private · model_type=CoT | high effort | 97.0 % | independent | ARC Prize Leaderboard |
| ARC-AGI-1older version split=semi_private · model_type=CoT | max effort | 96.5 % | independent | ARC Prize Leaderboard |
| ARC-AGI-1older version split=public_eval · model_type=CoT | medium effort | 93.9 % | independent | ARC Prize Leaderboard |
| ARC-AGI-2 split=public_eval · model_type=CoT | max effort | 93.8 % | independent | ARC Prize Leaderboard |
| ARC-AGI-2 split=semi_private · model_type=CoT | max effort | 92.5 % | independent | ARC Prize Leaderboard |
| ARC-AGI-1older version split=semi_private · model_type=CoT | medium effort | 92.5 % | independent | ARC Prize Leaderboard |
| ARC-AGI-2 split=public_eval · model_type=CoT | xhigh effort | 91.9 % | independent | ARC Prize Leaderboard |
| ARC-AGI-2 split=semi_private · model_type=CoT | xhigh effort | 90.0 % | independent | ARC Prize Leaderboard |
| ARC-AGI-2 split=public_eval · model_type=CoT | high effort | 86.1 % | independent | ARC Prize Leaderboard |
| ARC-AGI-2 split=semi_private · model_type=CoT | high effort | 85.4 % | independent | ARC Prize Leaderboard |
| ARC-AGI-1older version split=public_eval · model_type=CoT | low effort | 84.5 % | independent | ARC Prize Leaderboard |
| ARC-AGI-1older version split=semi_private · model_type=CoT | low effort | 74.5 % | independent | ARC Prize Leaderboard |
| ARC-AGI-2 split=public_eval · model_type=CoT | medium effort | 70.7 % | independent | ARC Prize Leaderboard |
| ARC-AGI-2 split=semi_private · model_type=CoT | medium effort | 67.1 % | independent | ARC Prize Leaderboard |
| ARC-AGI-2 split=semi_private · model_type=CoT | low effort | 42.5 % | independent | ARC Prize Leaderboard |
| ARC-AGI-2 split=public_eval · model_type=CoT | low effort | 38.5 % | independent | ARC Prize Leaderboard |
| ARC-AGI-3older version split=semi_private · model_type=CoT | max effort | 7.8 % | independent | ARC Prize Leaderboard |
| ARC-AGI-3older version split=semi_private · model_type=CoT | xhigh effort | 7.0 % | independent | ARC Prize Leaderboard |
| ARC-AGI-3older version split=semi_private · model_type=CoT | high effort | 2.1 % | independent | ARC Prize Leaderboard |
| ARC-AGI-2 split=public_eval · model_type=CoT | max effort | 1.5 usd_per_task | independent | ARC Prize Leaderboard |
| ARC-AGI-2 split=semi_private · model_type=CoT | max effort | 1.4 usd_per_task | independent | ARC Prize Leaderboard |
| ARC-AGI-3older version split=semi_private · model_type=CoT | medium effort | 1.1 % | independent | ARC Prize Leaderboard |
| ARC-AGI-2 split=semi_private · model_type=CoT | xhigh effort | 1.0 usd_per_task | independent | ARC Prize Leaderboard |
| ARC-AGI-2 split=public_eval · model_type=CoT | xhigh effort | 1.0 usd_per_task | independent | ARC Prize Leaderboard |
| ARC-AGI-2 split=public_eval · model_type=CoT | high effort | 0.8 usd_per_task | independent | ARC Prize Leaderboard |
| ARC-AGI-2 split=semi_private · model_type=CoT | high effort | 0.7 usd_per_task | independent | ARC Prize Leaderboard |
| ARC-AGI-1older version split=semi_private · model_type=CoT | max effort | 0.5 usd_per_task | independent | ARC Prize Leaderboard |
| ARC-AGI-2 split=public_eval · model_type=CoT | medium effort | 0.5 usd_per_task | independent | ARC Prize Leaderboard |
| ARC-AGI-2 split=semi_private · model_type=CoT | medium effort | 0.5 usd_per_task | independent | ARC Prize Leaderboard |
| ARC-AGI-1older version split=semi_private · model_type=CoT | xhigh effort | 0.4 usd_per_task | independent | ARC Prize Leaderboard |
| ARC-AGI-1older version split=public_eval · model_type=CoT | max effort | 0.4 usd_per_task | independent | ARC Prize Leaderboard |
| ARC-AGI-2 split=public_eval · model_type=CoT | low effort | 0.3 usd_per_task | independent | ARC Prize Leaderboard |
| ARC-AGI-3older version split=semi_private · model_type=CoT | low effort | 0.3 % | independent | ARC Prize Leaderboard |
| ARC-AGI-2 split=semi_private · model_type=CoT | low effort | 0.3 usd_per_task | independent | ARC Prize Leaderboard |
| ARC-AGI-1older version split=semi_private · model_type=CoT | high effort | 0.3 usd_per_task | independent | ARC Prize Leaderboard |
| ARC-AGI-1older version split=public_eval · model_type=CoT | xhigh effort | 0.3 usd_per_task | independent | ARC Prize Leaderboard |
| ARC-AGI-1older version split=semi_private · model_type=CoT | medium effort | 0.2 usd_per_task | independent | ARC Prize Leaderboard |
| ARC-AGI-1older version split=public_eval · model_type=CoT | high effort | 0.2 usd_per_task | independent | ARC Prize Leaderboard |
| ARC-AGI-1older version split=public_eval · model_type=CoT | medium effort | 0.2 usd_per_task | independent | ARC Prize Leaderboard |
| ARC-AGI-1older version split=semi_private · model_type=CoT | low effort | 0.2 usd_per_task | independent | ARC Prize Leaderboard |
| ARC-AGI-1older version split=public_eval · model_type=CoT | low effort | 0.1 usd_per_task | independent | ARC Prize Leaderboard |
| EnigmaEval | high effort | 37.1 % 34.3–39.9 | independent | Scale Labs |
| Release 2026-06-25 tasks_counted=4 · livebench_version=2026-06-25 | max effort | 96.2 % | independent | LiveBench |
| Release 2026-06-25 tasks_counted=4 · livebench_version=2026-06-25 | xhigh effort | 95.5 % | independent | LiveBench |
| Release 2026-06-25 tasks_counted=4 · livebench_version=2026-06-25 | max effort | 91.7 % | independent | LiveBench |
| Release 2026-06-25 tasks_counted=4 · livebench_version=2026-06-25 | xhigh effort | 90.2 % | independent | LiveBench |
| OTIS Mock AIME 2024–2025 | max effort | 100.0 % | independent | Epoch AI Benchmarking Hub 2026-07-09 |
| OTIS Mock AIME 2024–2025 | low effort | 95.6 % | independent | Epoch AI Benchmarking Hub 2026-08-07 |
| OTIS Mock AIME 2024–2025 | no reasoning | 68.9 % | independent | Epoch AI Benchmarking Hub 2026-08-07 |
Agent + model results
systems, not bare-model scores
| agent + model Artificial Analysis harness + GPT 5.6 Sol | Terminal-Bench 2.1 | 89.5 % | independent | Artificial Analysis |
| agent + model Artificial Analysis harness + GPT 5.6 Sol | Terminal-Bench 2.1 | 88.0 % | independent | Artificial Analysis |
| agent + model Artificial Analysis harness + GPT 5.6 Sol | Terminal-Bench 2.1 | 87.3 % | independent | Artificial Analysis |
| agent + model Artificial Analysis harness + GPT 5.6 Sol | Terminal-Bench 2.1 | 86.1 % | independent | Artificial Analysis |
| agent + model Artificial Analysis harness + GPT 5.6 Sol | Terminal-Bench 2.1 | 76.8 % | independent | Artificial Analysis |
| agent + model Artificial Analysis harness + GPT 5.6 Sol | Terminal-Bench 2.1 | 74.2 % | independent | Artificial Analysis |
| agent + model Artificial Analysis harness + GPT 5.6 Sol | Terminal-Bench Hard | 65.9 % | independent | Artificial Analysis |
| agent + model Artificial Analysis harness + GPT 5.6 Sol | Terminal-Bench Hard | 62.9 % | independent | Artificial Analysis |
| agent + model Artificial Analysis harness + GPT 5.6 Sol | Terminal-Bench Hard | 62.1 % | independent | Artificial Analysis |
| agent + model Artificial Analysis harness + GPT 5.6 Sol | Terminal-Bench Hard | 61.4 % | independent | Artificial Analysis |
| agent + model Artificial Analysis harness + GPT 5.6 Sol | Terminal-Bench Hard | 60.6 % | independent | Artificial Analysis |
These scores measure the whole agent system (scaffold, tools, budgets) — they are never merged into the bare model’s numbers.
