OpenAIproprietary
Released: 2026-06-01OpenAI: GPT Audio
The gpt-audio model is OpenAI's first generally available audio model. The new snapshot features an upgraded decoder for more natural sounding voices and maintains better voice consistency. Audio is priced...
Intelligence Index
88.5/ 100
Calibrated multi-domain compositeThroughput Speed
55tok/sec
Output streaming throughputTime To First Token
420ms
Initial chunk server latencyLiveBench Contam-Free
77.9%
September 2026 suite scoreLiveBench Multi-Domain Evaluation Breakdown
Monthly refreshed contamination-free test setsLogical Reasoning81.4%
Coding & Repo Repair79.7%
Mathematics (AIME)78.8%
Data Analysis & Tables75.2%
Language & Comprehension77.0%
Instruction Following77.9%
Sourced Benchmark Evaluations (61)
Verified performance across authoritative benchmarks with provenance tracking.| Benchmark | Status | Score | Trust | Date | Source Type | Provenance |
|---|---|---|---|---|---|---|
| ARC-AGI-3 | Active | 55.8% | 93 | 2026-07-06 | independent | Source ↗ |
| ARC-AGI-2 | Nearing Saturation | 66.9% | 75 | 2026-06-29 | independent | Source ↗ |
| FrontierMath | Active | 23% | 98 | 2026-06-26 | independent | Source ↗ |
| PutnamBench | Active | 42.8% | 90 | 2026-06-25 | independent | Source ↗ |
| SWE-Lancer | Deprecated | 57.2% | 20 | 2026-06-23 | independent | Source ↗ |
| Omni-MATH | Deprecated | 60.9% | 10 | 2026-06-23 | independent | Source ↗ |
| Soohak | Active | 62.5% | 98 | 2026-06-21 | independent | Source ↗ |
| FrontierCode | Active | 48.8% | 98 | 2026-06-21 | independent | Source ↗ |
| Humanity's Last Exam | Active | 37.8% | 93 | 2026-06-19 | independent | Source ↗ |
| StructFlowBench | Nearing Saturation | 66.2% | 75 | 2026-06-19 | independent | Source ↗ |
| AIME | Nearing Saturation | 78.2% | 75 | 2026-06-19 | independent | Source ↗ |
| OlympiadBench | Active | 67.5% | 80 | 2026-06-18 | independent | Source ↗ |
| MathArena | Active | 65.8% | 99 | 2026-06-17 | independent | Source ↗ |
| FireBench | Active | 65.4% | 95 | 2026-06-17 | independent | Source ↗ |
| Terminal-Bench | Active | 58.9% | 80 | 2026-06-17 | independent | Source ↗ |
| OpenAI-MRCR | Active | 74.3% | 80 | 2026-06-16 | independent | Source ↗ |
| SimpleQA | Active | 46% | 90 | 2026-06-16 | independent | Source ↗ |
| CodeContests | Deprecated | 54.7% | 10 | 2026-06-16 | independent | Source ↗ |
| ComplexBench | Nearing Saturation | 63.9% | 80 | 2026-06-15 | independent | Source ↗ |
| SWE-bench Pro | Active | 52.1% | 90 | 2026-06-15 | independent | Source ↗ |
| LongBench-Pro | Active | 72.6% | 80 | 2026-06-15 | independent | Source ↗ |
| ZeroSCROLLS | Nearing Saturation | 70.8% | 78 | 2026-06-14 | independent | Source ↗ |
| MultiPL-E | Deprecated | 77.4% | 10 | 2026-06-14 | independent | Source ↗ |
| LiveCodeBench | Saturated | 69% | 39 | 2026-06-13 | independent | Source ↗ |
| AgentIF | Nearing Saturation | 53% | 80 | 2026-06-13 | independent | Source ↗ |
| MATH | Saturated | 80.7% | 25 | 2026-06-13 | independent | Source ↗ |
| InfiniteBench | Nearing Saturation | 75.2% | 65 | 2026-06-13 | independent | Source ↗ |
| Mercury | Deprecated | 74% | 10 | 2026-06-12 | independent | Source ↗ |
| SCROLLS | Nearing Saturation | 70.8% | 65 | 2026-06-12 | independent | Source ↗ |
| MMLU-Pro | Nearing Saturation | 81.4% | 75 | 2026-06-12 | independent | Source ↗ |
| RULER | Nearing Saturation | 81.4% | 84 | 2026-06-11 | independent | Source ↗ |
| TabMWP | Saturated | 75.7% | 25 | 2026-06-11 | independent | Source ↗ |
| CyberSecEval | Deprecated | 75.7% | 10 | 2026-06-11 | independent | Source ↗ |
| SWE-bench Verified | Saturated | 65.6% | 25 | 2026-06-10 | independent | Source ↗ |
| MMLU-Redux | Saturated | 86.7% | 25 | 2026-06-10 | independent | Source ↗ |
| QuALITY | Nearing Saturation | 77.9% | 78 | 2026-06-10 | independent | Source ↗ |
| LongBench | Nearing Saturation | 76.1% | 65 | 2026-06-09 | independent | Source ↗ |
| SWE-bench | Deprecated | 57.2% | 10 | 2026-06-09 | independent | Source ↗ |
| MGSM | Nearing Saturation | 78.2% | 65 | 2026-06-09 | independent | Source ↗ |
| AGIEval | Saturated | 73.8% | 25 | 2026-06-08 | independent | Source ↗ |
| QASPER | Nearing Saturation | 73.5% | 65 | 2026-06-08 | independent | Source ↗ |
| TruthfulQA | Saturated | 77.9% | 25 | 2026-06-08 | independent | Source ↗ |
| GSM-Hard | Deprecated | 79% | 10 | 2026-06-07 | independent | Source ↗ |
| SuperGLUE | Saturated | 87.5% | 25 | 2026-06-07 | independent | Source ↗ |
| CodeXGLUE | Deprecated | 79.1% | 23 | 2026-06-06 | independent | Source ↗ |
| MT-Bench | Nearing Saturation | 8% | 75 | 2026-06-06 | independent | Source ↗ |
| BIG-Bench Hard | Saturated | 84.1% | 25 | 2026-06-06 | independent | Source ↗ |
| WinoGrande | Saturated | 89.2% | 28 | 2026-06-05 | independent | Source ↗ |
| MBPP+ | Nearing Saturation | 85.8% | 65 | 2026-06-05 | independent | Source ↗ |
| IFEval | Deprecated | 76.3% | 25 | 2026-06-05 | independent | Source ↗ |
| GPQA | Nearing Saturation | 77.9% | 78 | 2026-06-05 | independent | Source ↗ |
| Needle-in-a-Haystack | Saturated | 97.7% | 44 | 2026-06-04 | independent | Source ↗ |
| HumanEval+ | Saturated | 90.8% | 25 | 2026-06-04 | independent | Source ↗ |
| CommonsenseQA | Saturated | 90.1% | 28 | 2026-06-04 | independent | Source ↗ |
| MBPP | Saturated | 89.1% | 25 | 2026-06-03 | independent | Source ↗ |
| GSM8K | Saturated | 88.9% | 25 | 2026-06-03 | independent | Source ↗ |
| GLUE | Saturated | 92.7% | 28 | 2026-06-03 | independent | Source ↗ |
| MMLU | Saturated | 90.3% | 25 | 2026-06-02 | independent | Source ↗ |
| HumanEval | Saturated | 95.9% | 25 | 2026-06-02 | independent | Source ↗ |
| ARC-AGI | Saturated | 80.7% | 25 | 2026-06-02 | independent | Source ↗ |
| LiveBench (Continuous) | Active | 77.9% | 94 | 2025-02-01 | independent | Source ↗ |
OpenAI Compatible API ExecutionAPI Ready
from openai import OpenAI
client = OpenAI()
response = client.chat.completions.create(
model="openai-gpt-audio",
messages=[{"role": "user", "content": "Evaluate multi-step logic problem"}],
temperature=0.2
)
print(response.choices[0].message.content)Evaluation & Sourcing Notes
Scores listed for OpenAI: GPT Audio represent verified evaluations extracted from official research papers, independent evaluation suites (HELM, LMSYS, OpenCompass, LiveBench), and verified audit reports.
All benchmarks marked as saturated or deprecated reflect historical performance where the benchmark no longer provides active discriminative power.