OpenAIproprietary
Released: 2026-09-03GPT-6 Astra
GPT-6 Astra is OpenAI's flagship model for demanding end-to-end work. It is suited for advanced analysis, software engineering, deep research, scientific work, and document creation, with particular strengths in long-horizon...
Intelligence Index
91.5/ 100
Calibrated multi-domain compositeThroughput Speed
55tok/sec
Output streaming throughputTime To First Token
420ms
Initial chunk server latencyLiveBench Contam-Free
80.5%
September 2026 suite scoreLiveBench Multi-Domain Evaluation Breakdown
Monthly refreshed contamination-free test setsLogical Reasoning84.2%
Coding & Repo Repair82.4%
Mathematics (AIME)81.4%
Data Analysis & Tables77.8%
Language & Comprehension79.6%
Instruction Following80.5%
Sourced Benchmark Evaluations (61)
Verified performance across authoritative benchmarks with provenance tracking.| Benchmark | Status | Score | Trust | Date | Source Type | Provenance |
|---|---|---|---|---|---|---|
| StructFlowBench | Nearing Saturation | 68.4% | 75 | 2026-09-12 | independent | Source ↗ |
| SWE-bench Pro | Active | 53.9% | 90 | 2026-09-12 | independent | Source ↗ |
| InfiniteBench | Nearing Saturation | 77.8% | 65 | 2026-09-12 | independent | Source ↗ |
| LongBench-Pro | Active | 75% | 80 | 2026-09-12 | independent | Source ↗ |
| MATH | Saturated | 83.4% | 25 | 2026-09-12 | independent | Source ↗ |
| MathArena | Active | 68.1% | 99 | 2026-09-12 | independent | Source ↗ |
| AgentIF | Nearing Saturation | 54.7% | 80 | 2026-09-12 | independent | Source ↗ |
| Mercury | Deprecated | 76.5% | 10 | 2026-09-12 | independent | Source ↗ |
| MMLU-Pro | Nearing Saturation | 84.2% | 75 | 2026-09-12 | independent | Source ↗ |
| MMLU-Redux | Saturated | 89.7% | 25 | 2026-09-12 | independent | Source ↗ |
| MultiPL-E | Deprecated | 79.9% | 10 | 2026-09-12 | independent | Source ↗ |
| LiveCodeBench | Saturated | 71.3% | 39 | 2026-09-12 | independent | Source ↗ |
| OlympiadBench | Active | 69.8% | 80 | 2026-09-12 | independent | Source ↗ |
| Omni-MATH | Deprecated | 63% | 10 | 2026-09-12 | independent | Source ↗ |
| OpenAI-MRCR | Active | 76.9% | 80 | 2026-09-12 | independent | Source ↗ |
| PutnamBench | Active | 44.3% | 90 | 2026-09-12 | independent | Source ↗ |
| QuALITY | Nearing Saturation | 80.5% | 78 | 2026-09-12 | independent | Source ↗ |
| RULER | Nearing Saturation | 84.2% | 84 | 2026-09-12 | independent | Source ↗ |
| SCROLLS | Nearing Saturation | 73.2% | 65 | 2026-09-12 | independent | Source ↗ |
| SimpleQA | Active | 47.6% | 90 | 2026-09-12 | independent | Source ↗ |
| Soohak | Active | 64.7% | 98 | 2026-09-12 | independent | Source ↗ |
| SWE-bench Verified | Saturated | 67.8% | 25 | 2026-09-12 | independent | Source ↗ |
| AIME | Nearing Saturation | 80.8% | 75 | 2026-09-12 | independent | Source ↗ |
| ZeroSCROLLS | Nearing Saturation | 73.2% | 78 | 2026-09-12 | independent | Source ↗ |
| ARC-AGI-2 | Nearing Saturation | 69.3% | 75 | 2026-09-12 | independent | Source ↗ |
| ARC-AGI-3 | Active | 57.7% | 93 | 2026-09-12 | independent | Source ↗ |
| CodeContests | Deprecated | 56.5% | 10 | 2026-09-12 | independent | Source ↗ |
| ComplexBench | Nearing Saturation | 66% | 80 | 2026-09-12 | independent | Source ↗ |
| CyberSecEval | Deprecated | 78.2% | 10 | 2026-09-12 | independent | Source ↗ |
| FireBench | Active | 67.6% | 95 | 2026-09-12 | independent | Source ↗ |
| FrontierCode | Active | 50.4% | 98 | 2026-09-12 | independent | Source ↗ |
| FrontierMath | Active | 23.8% | 98 | 2026-09-12 | independent | Source ↗ |
| Humanity's Last Exam | Active | 39.1% | 93 | 2026-09-12 | independent | Source ↗ |
| SWE-Lancer | Deprecated | 59.1% | 20 | 2026-09-12 | independent | Source ↗ |
| Terminal-Bench | Active | 60.8% | 80 | 2026-09-12 | independent | Source ↗ |
| TabMWP | Saturated | 78.3% | 25 | 2026-09-12 | independent | Source ↗ |
| MGSM | Nearing Saturation | 80.8% | 65 | 2026-09-11 | independent | Source ↗ |
| SWE-bench | Deprecated | 59.1% | 10 | 2026-09-11 | independent | Source ↗ |
| LongBench | Nearing Saturation | 78.7% | 65 | 2026-09-11 | independent | Source ↗ |
| AGIEval | Saturated | 76.4% | 25 | 2026-09-10 | independent | Source ↗ |
| QASPER | Nearing Saturation | 75.9% | 65 | 2026-09-10 | independent | Source ↗ |
| TruthfulQA | Saturated | 80.5% | 25 | 2026-09-10 | independent | Source ↗ |
| GSM-Hard | Deprecated | 81.7% | 10 | 2026-09-09 | independent | Source ↗ |
| SuperGLUE | Saturated | 90.6% | 25 | 2026-09-09 | independent | Source ↗ |
| CodeXGLUE | Deprecated | 81.7% | 23 | 2026-09-08 | independent | Source ↗ |
| BIG-Bench Hard | Saturated | 87% | 25 | 2026-09-08 | independent | Source ↗ |
| MT-Bench | Nearing Saturation | 8.3% | 75 | 2026-09-08 | independent | Source ↗ |
| WinoGrande | Saturated | 92.4% | 28 | 2026-09-07 | independent | Source ↗ |
| MBPP+ | Nearing Saturation | 88.6% | 65 | 2026-09-07 | independent | Source ↗ |
| IFEval | Deprecated | 78.9% | 25 | 2026-09-07 | independent | Source ↗ |
| GPQA | Nearing Saturation | 80.5% | 78 | 2026-09-07 | independent | Source ↗ |
| Needle-in-a-Haystack | Saturated | 98.3% | 44 | 2026-09-06 | independent | Source ↗ |
| HumanEval+ | Saturated | 93.9% | 25 | 2026-09-06 | independent | Source ↗ |
| CommonsenseQA | Saturated | 93.2% | 28 | 2026-09-06 | independent | Source ↗ |
| MBPP | Saturated | 92.1% | 25 | 2026-09-05 | independent | Source ↗ |
| GSM8K | Saturated | 91.9% | 25 | 2026-09-05 | independent | Source ↗ |
| GLUE | Saturated | 95.9% | 28 | 2026-09-05 | independent | Source ↗ |
| MMLU | Saturated | 93.3% | 25 | 2026-09-04 | independent | Source ↗ |
| HumanEval | Saturated | 99.1% | 25 | 2026-09-04 | independent | Source ↗ |
| ARC-AGI | Saturated | 83.5% | 25 | 2026-09-04 | independent | Source ↗ |
| LiveBench (Continuous) | Active | 80.5% | 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-6-astra",
messages=[{"role": "user", "content": "Evaluate multi-step logic problem"}],
temperature=0.2
)
print(response.choices[0].message.content)Evaluation & Sourcing Notes
Scores listed for GPT-6 Astra 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.