Google DeepMindproprietary
Released: 2026-08-13Gemini 3.7 Flash
Google DeepMind premier intelligence workhorse combining top-tier 182 tok/s inference speeds with deep 1M context multimodal reasoning.
Intelligence Index
93.2/ 100
Calibrated multi-domain compositeThroughput Speed
182tok/sec
Output streaming throughputTime To First Token
240ms
Initial chunk server latencyLiveBench Contam-Free
78.8%
September 2026 suite scoreLiveBench Multi-Domain Evaluation Breakdown
Monthly refreshed contamination-free test setsLogical Reasoning87.8%
Coding & Repo Repair78.9%
Mathematics (AIME)93.5%
Data Analysis & Tables76.5%
Language & Comprehension71.2%
Instruction Following65.9%
Sourced Benchmark Evaluations (61)
Verified performance across authoritative benchmarks with provenance tracking.| Benchmark | Status | Score | Trust | Date | Source Type | Provenance |
|---|---|---|---|---|---|---|
| ARC-AGI-3 | Active | 60.5% | 93 | 2026-09-12 | independent | Source ↗ |
| ARC-AGI-2 | Nearing Saturation | 72.5% | 75 | 2026-09-10 | independent | Source ↗ |
| FrontierMath | Active | 26.2% | 98 | 2026-09-07 | independent | Source ↗ |
| PutnamBench | Active | 48.6% | 90 | 2026-09-06 | independent | Source ↗ |
| SWE-Lancer | Deprecated | 53.7% | 20 | 2026-09-04 | independent | Source ↗ |
| Omni-MATH | Deprecated | 69.2% | 10 | 2026-09-04 | independent | Source ↗ |
| Soohak | Active | 71.1% | 98 | 2026-09-02 | independent | Source ↗ |
| FrontierCode | Active | 45.8% | 98 | 2026-09-02 | independent | Source ↗ |
| Humanity's Last Exam | Active | 40.9% | 93 | 2026-08-31 | independent | Source ↗ |
| StructFlowBench | Nearing Saturation | 56% | 75 | 2026-08-31 | independent | Source ↗ |
| AIME | Nearing Saturation | 88.8% | 75 | 2026-08-31 | independent | Source ↗ |
| OlympiadBench | Active | 76.7% | 80 | 2026-08-30 | independent | Source ↗ |
| MathArena | Active | 74.8% | 99 | 2026-08-29 | independent | Source ↗ |
| FireBench | Active | 55.4% | 95 | 2026-08-29 | independent | Source ↗ |
| Terminal-Bench | Active | 55.2% | 80 | 2026-08-29 | independent | Source ↗ |
| OpenAI-MRCR | Active | 78.3% | 80 | 2026-08-28 | independent | Source ↗ |
| SimpleQA | Active | 48.5% | 90 | 2026-08-28 | independent | Source ↗ |
| CodeContests | Deprecated | 51.3% | 10 | 2026-08-28 | independent | Source ↗ |
| ComplexBench | Nearing Saturation | 54% | 80 | 2026-08-27 | independent | Source ↗ |
| SWE-bench Pro | Active | 48.9% | 90 | 2026-08-27 | independent | Source ↗ |
| LongBench-Pro | Active | 76.4% | 80 | 2026-08-27 | independent | Source ↗ |
| ZeroSCROLLS | Nearing Saturation | 74.6% | 78 | 2026-08-26 | independent | Source ↗ |
| MultiPL-E | Deprecated | 72.6% | 10 | 2026-08-26 | independent | Source ↗ |
| LiveCodeBench | Saturated | 64.7% | 39 | 2026-08-25 | independent | Source ↗ |
| AgentIF | Nearing Saturation | 44.8% | 80 | 2026-08-25 | independent | Source ↗ |
| MATH | Saturated | 91.6% | 25 | 2026-08-25 | independent | Source ↗ |
| InfiniteBench | Nearing Saturation | 79.2% | 65 | 2026-08-25 | independent | Source ↗ |
| Mercury | Deprecated | 69.4% | 10 | 2026-08-24 | independent | Source ↗ |
| SCROLLS | Nearing Saturation | 74.6% | 65 | 2026-08-24 | independent | Source ↗ |
| MMLU-Pro | Nearing Saturation | 85.7% | 75 | 2026-08-24 | independent | Source ↗ |
| RULER | Nearing Saturation | 85.7% | 84 | 2026-08-23 | independent | Source ↗ |
| TabMWP | Saturated | 86% | 25 | 2026-08-23 | independent | Source ↗ |
| CyberSecEval | Deprecated | 71% | 10 | 2026-08-23 | independent | Source ↗ |
| SWE-bench Verified | Saturated | 61.5% | 25 | 2026-08-22 | independent | Source ↗ |
| MMLU-Redux | Saturated | 91.3% | 25 | 2026-08-22 | independent | Source ↗ |
| QuALITY | Nearing Saturation | 82% | 78 | 2026-08-22 | independent | Source ↗ |
| LongBench | Nearing Saturation | 80.2% | 65 | 2026-08-21 | independent | Source ↗ |
| SWE-bench | Deprecated | 53.7% | 10 | 2026-08-21 | independent | Source ↗ |
| MGSM | Nearing Saturation | 88.8% | 65 | 2026-08-21 | independent | Source ↗ |
| AGIEval | Saturated | 80% | 25 | 2026-08-20 | independent | Source ↗ |
| QASPER | Nearing Saturation | 77.4% | 65 | 2026-08-20 | independent | Source ↗ |
| TruthfulQA | Saturated | 82% | 25 | 2026-08-20 | independent | Source ↗ |
| GSM-Hard | Deprecated | 89.8% | 10 | 2026-08-19 | independent | Source ↗ |
| SuperGLUE | Saturated | 94.9% | 25 | 2026-08-19 | independent | Source ↗ |
| CodeXGLUE | Deprecated | 74.2% | 23 | 2026-08-18 | independent | Source ↗ |
| MT-Bench | Nearing Saturation | 6.8% | 75 | 2026-08-18 | independent | Source ↗ |
| BIG-Bench Hard | Saturated | 91.1% | 25 | 2026-08-18 | independent | Source ↗ |
| WinoGrande | Saturated | 96.7% | 28 | 2026-08-17 | independent | Source ↗ |
| MBPP+ | Nearing Saturation | 80.5% | 65 | 2026-08-17 | independent | Source ↗ |
| IFEval | Deprecated | 64.6% | 25 | 2026-08-17 | independent | Source ↗ |
| GPQA | Nearing Saturation | 82% | 78 | 2026-08-17 | independent | Source ↗ |
| Needle-in-a-Haystack | Saturated | 98.6% | 44 | 2026-08-16 | independent | Source ↗ |
| HumanEval+ | Saturated | 85.2% | 25 | 2026-08-16 | independent | Source ↗ |
| CommonsenseQA | Saturated | 97.7% | 28 | 2026-08-16 | independent | Source ↗ |
| MBPP | Saturated | 83.6% | 25 | 2026-08-15 | independent | Source ↗ |
| GSM8K | Saturated | 100% | 25 | 2026-08-15 | independent | Source ↗ |
| GLUE | Saturated | 100% | 28 | 2026-08-15 | independent | Source ↗ |
| MMLU | Saturated | 95.1% | 25 | 2026-08-14 | independent | Source ↗ |
| HumanEval | Saturated | 89.9% | 25 | 2026-08-14 | independent | Source ↗ |
| ARC-AGI | Saturated | 87.4% | 25 | 2026-08-14 | independent | Source ↗ |
| LiveBench (Continuous) | Active | 78.8% | 94 | 2025-02-01 | independent | Source ↗ |
OpenAI Compatible API ExecutionAPI Ready
from openai import OpenAI
client = OpenAI()
response = client.chat.completions.create(
model="gemini-3-7-flash",
messages=[{"role": "user", "content": "Evaluate multi-step logic problem"}],
temperature=0.2
)
print(response.choices[0].message.content)Evaluation & Sourcing Notes
Scores listed for Gemini 3.7 Flash 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.