85.3%
MMLU-Pro (AA run)
Modelle / OpenAI
OpenAI o · Release 2025-04-16
OpenAIs Reasoning-Modell April 2025. Extended Thinking für Mathe, Code und Wissenschaft. LiveBench 68,5 %, LongBench v2 51,2 %, BFCL 78,1 %.
OpenAI-Reasoning-Tier, wenn Latenz und Kosten hinter schwierigster Single-Shot-Problemlösung zurückstehen.
85average across 7 tested families
Wo OpenAI o3 auf jeder öffentlichen Benchmark-Quelle mit Zeile steht. Rang zählt jedes Modell mit neuester Zeile im selben Test — kein universeller Qualitätsscore.
| Benchmark | Family | Rang | Score | Quelle | Datum |
|---|---|---|---|---|---|
| MATH | Math | #1/ 20 | 99 | Artificial Analysis | 2026-07-21 |
| LiveCodeBench | Coding | #4/ 13 | 81 | Artificial Analysis | 2026-07-21 |
| MMLU-Pro | Knowledge | #6/ 21 | 85 | Artificial Analysis | 2026-07-21 |
| AIME | Math | #8/ 19 | 88 | Artificial Analysis | 2026-07-21 |
| τ³-Bench Banking | Agentic | #11/ 64 | 81 | Artificial Analysis | 2026-07-21 |
| AA output speed | Performance | #16/ 69 | Artificial Analysis | 2026-07-21 | |
| AA time to first token | Performance | #26/ 69 | Artificial Analysis | 2026-07-21 | |
| AA-LCR | Long context | #27/ 64 | 69 | Artificial Analysis | 2026-07-21 |
| IFBench | Reasoning | #30/ 57 | 71 | Artificial Analysis | 2026-07-21 |
| GPQA Diamond | Reasoning | #43/ 69 | 83 | Artificial Analysis | 2026-07-21 |
| Humanity's Last Exam | Reasoning | #45/ 65 | 20 | Artificial Analysis | 2026-07-21 |
| Artificial Analysis Intelligence Index | Reasoning | #48/ 67 | 30 | Artificial Analysis | 2026-07-21 |
| SciCode | Coding | #49/ 65 | 41 | Artificial Analysis | 2026-07-21 |
| Terminal-Bench | Agentic | #55/ 69 | 37 | Artificial Analysis | 2026-07-21 |
Die drei höchstscorierenden kartierten Modelle pro Capability-Family. Wo OpenAI o3 auftaucht, ist es hervorgehoben.
Benchmark-Zeilen im öffentlichen Ledger für OpenAI o3 in den letzten 120 Tagen. Ältere Zeilen stehen in der vollen Tabelle unten.
| Benchmark | Family | Score | Quelle | Tage her |
|---|---|---|---|---|
| AA-LCR | Long context | 69.33% | Artificial Analysis | 2 |
| AA output speed | Performance | 155 t/s | Artificial Analysis | 2 |
| AA time to first token | Performance | 4.84s | Artificial Analysis | 2 |
| AIME | Math | 88.33% | Artificial Analysis | 2 |
| Artificial Analysis Intelligence Index | Reasoning | 30.4% | Artificial Analysis | 2 |
| GPQA Diamond | Reasoning | 82.7% | Artificial Analysis | 2 |
| Humanity's Last Exam | Reasoning | 20% | Artificial Analysis | 2 |
| IFBench | Reasoning | 71.43% | Artificial Analysis | 2 |
| LiveCodeBench | Coding | 80.8% | Artificial Analysis | 2 |
| MATH | Math | 99.2% | Artificial Analysis | 2 |
| MMLU-Pro | Knowledge | 85.3% | Artificial Analysis | 2 |
| SciCode | Coding | 41% | Artificial Analysis | 2 |
| τ³-Bench Banking | Agentic | 80.7% | Artificial Analysis | 2 |
| Terminal-Bench | Agentic | 37.12% | Artificial Analysis | 2 |
| BFCL | Tool use | 78.1% | Berkeley Function Calling Leaderboard V4 | 99 |
| LiveBench | Reasoning | 68.5% | LiveBench leaderboard | 99 |
| LongBench v2 | Long context | 51.2% | LongBench v2 leaderboard | 113 |
Ein hoher Composite, der eine schwache Family versteckt, ist eine Falle. Diese Balken zeigen Families ohne öffentlichen Test — und wo das Modell führt.
Hover or tab any dot for name, score, and input price.
Jeder Katalog-Benchmark für OpenAI o3. Scores verlinken zur Originalquelle; Lücken heißen: noch keine öffentliche Zeile.
19 of 32 catalog benchmarks have a sourced row for OpenAI o3.
85.3%
MMLU-Pro (AA run)
87.5%
ARC-AGI-1 high compute
30.4%
AA Intelligence Index v4.1
82.7%
GPQA Diamond (AA run)
20%
HLE (AA run)
71.43%
IFBench (AA run)
68.5%
LiveBench
94.8% pass@1
HumanEval
80.8%
LiveCodeBench (AA run)
41%
SciCode (AA run)
37.12%
Terminal-Bench Hard (AA run)
80.7%
τ²-Bench Banking (AA run; maps to τ³ explainer)
69.33%
AA-LCR (AA run)
51.2%
LongBench v2
78.1%
BFCL
155 t/s
Median output tokens/s (1k prompt, default provider)
4.84s
Median time to first token (1k prompt, default provider)