# Gemini 3.7 Flash vs GPT-6 Astra

> GPT-6 Astra is the stronger model overall, scoring 70.8 to 59.8 on the Noometry Index. Gemini 3.7 Flash costs 13× less per token, which makes it the better buy when GPT-6 Astra's lead doesn't matter for your workload.

- Canonical page: https://noometry.com/compare/gemini-3-7-flash-vs-gpt-6-astra
- Last updated: 2026-10-10
- Shared benchmarks: 44

## Summary

- They share 44 benchmarks with published results for both. Gemini 3.7 Flash scores higher in 3 categories and GPT-6 Astra in 7 categories; 10 gaps are clear of the uncertainty.
- The widest gap is in math, where GPT-6 Astra leads 93.5 to 69.6.
- The biggest single-benchmark swing is FrontierMath Tier 4: 36.6% for Gemini 3.7 Flash and 97.6% for GPT-6 Astra.
- Gemini 3.7 Flash is cheaper at $0.75 / $3.75 per million input/output tokens, against $10 / $50 for GPT-6 Astra.
- GPT-6 Astra accepts more context: 1.05M tokens versus 1.05M.

## Snapshot

| | Gemini 3.7 Flash | GPT-6 Astra |
|---|---|---|
| Provider | Google | OpenAI |
| Noometry Index | 59.8 | 70.8 |
| Rank | 14 | 1 |
| Context | 1.05M | 1.05M |
| Input $/M | $0.75 | $10 |
| Output $/M | $3.75 | $50 |
| Weights | Proprietary | Proprietary |

## Coding

- Gemini 3.7 Flash: 56.2 (#22)
- GPT-6 Astra: 73.7 (#2)

| Benchmark | Gemini 3.7 Flash | GPT-6 Astra |
|---|---|---|
| DeepSWE | 65.5% | 74.1% |
| FrontierCode | 43.6% | 53.3% |
| LMArena WebDev | 1592 | 1786 |
| FrontierSWE | 20.3% | 65.5% |
| SciCode | 59.8% | 56.5% |
| LMArena Coding | 1497 | 1487 |
| ALE-Bench | 904.3 | 2,951 |
| GSO | — | 79.4% |
| WeirdML | — | 93.6% |
| MirrorCode | — | 46.7% |

## Agentic & Tool Use

- Gemini 3.7 Flash: 42.1 (#19)
- GPT-6 Astra: 52.9 (#3)

| Benchmark | Gemini 3.7 Flash | GPT-6 Astra |
|---|---|---|
| APEX-Agents | 67.8% | 64.7% |
| Remote Labor Index | 5% | 20.8% |
| GDP.pdf | 23.8% | 34.2% |
| BALROG | — | 68.3% |
| Vending-Bench 2 | — | 15,515 |

## Reasoning

- Gemini 3.7 Flash: 70.0 (#15)
- GPT-6 Astra: 85.1 (#1)

| Benchmark | Gemini 3.7 Flash | GPT-6 Astra |
|---|---|---|
| ARC-AGI-2 | 84.6% | 95% |
| NYT Connections (extended) | 94% | 98.1% |
| ARC-AGI-1 | 95.5% | 98.5% |
| CritPt | 14.3% | 31.7% |
| Chess Puzzles | 47% | 72% |
| LMArena Hard Prompts | 1494 | 1462 |
| Mystery Game Puzzles | 37% | 84% |
| DTBench | 96.8% | 97.3% |
| LMCA | 50.4% | 64.4% |
| Epoch Capabilities Index | 157.27 | 166.45 |
| EBR-Bench | — | 76.2% |
| Bench to the Future 3 | — | 0.14 |

## Math

- Gemini 3.7 Flash: 69.6 (#23)
- GPT-6 Astra: 93.5 (#2)

| Benchmark | Gemini 3.7 Flash | GPT-6 Astra |
|---|---|---|
| FrontierMath (Tiers 1-3) | 71.6% | 93.7% |
| FrontierMath Tier 4 | 36.6% | 97.6% |
| OTIS Mock AIME 2024-2025 | 97.2% | 100% |
| ProofBench | 58% | 99% |
| LMArena Math | 1507 | 1465 |
| FrontierMath Erdős | — | 2.9% |

## Knowledge

- Gemini 3.7 Flash: 69.7 (#5)
- GPT-6 Astra: 75.3 (#1)

| Benchmark | Gemini 3.7 Flash | GPT-6 Astra |
|---|---|---|
| GPQA Diamond | 94.8% | 95.8% |
| SimpleQA Verified | 69.2% | 75.6% |
| LMArena Expert | 1508 | 1483 |
| Humanity's Last Exam | — | 54.8% |
| Vectara Hallucination Rate | — | 8.7% |

## Multimodal

- Gemini 3.7 Flash: 37.3 (#73)
- GPT-6 Astra: 55.0 (#3)

| Benchmark | Gemini 3.7 Flash | GPT-6 Astra |
|---|---|---|
| LMArena Vision | 1316 | 1281 |
| Furniture Assembly | 26.7% | 80% |
| Blueprint-Bench 2 | — | 49.7% |
| LMArena Document | — | 1468 |

## Multilingual

- Gemini 3.7 Flash: 57.6 (#7)
- GPT-6 Astra: 53.7 (#61)

| Benchmark | Gemini 3.7 Flash | GPT-6 Astra |
|---|---|---|
| LMArena Non-English | 1484 | 1430 |
| LMArena Chinese | 1548 | 1484 |
| LMArena French | 1505 | 1456 |
| LMArena German | 1498 | 1440 |
| LMArena Japanese | 1512 | 1379 |
| LMArena Korean | 1483 | 1426 |
| LMArena Russian | 1516 | 1436 |
| LMArena Spanish | 1503 | 1407 |

## Instruction Following

- Gemini 3.7 Flash: 77.7 (#15)
- GPT-6 Astra: 76.3 (#44)

| Benchmark | Gemini 3.7 Flash | GPT-6 Astra |
|---|---|---|
| LMArena Instruction Following | 1483 | 1450 |

## Long Context

- Gemini 3.7 Flash: 45.7 (#30)
- GPT-6 Astra: 44.5 (#62)

| Benchmark | Gemini 3.7 Flash | GPT-6 Astra |
|---|---|---|
| LMArena Longer Query | 1492 | 1456 |

## Writing & Preference

- Gemini 3.7 Flash: 71.2 (#20)
- GPT-6 Astra: 75.3 (#7)

| Benchmark | Gemini 3.7 Flash | GPT-6 Astra |
|---|---|---|
| LMArena Text | 1486 | 1441 |
| LMArena Creative Writing | 1490 | 1418 |
| EQ-Bench Creative Writing | 1723 | 2173 |
| LMArena Multi-Turn | 1489 | 1448 |

## FAQ

### Is Gemini 3.7 Flash better than GPT-6 Astra?

GPT-6 Astra is the stronger model overall, scoring 70.8 to 59.8 on the Noometry Index. Gemini 3.7 Flash costs 13× less per token, which makes it the better buy when GPT-6 Astra's lead doesn't matter for your workload.

### Which is cheaper, Gemini 3.7 Flash or GPT-6 Astra?

Gemini 3.7 Flash is cheaper. It lists at $0.75 per million input tokens and $3.75 per million output tokens; GPT-6 Astra lists at $10 and $50.

### Is Gemini 3.7 Flash or GPT-6 Astra better for coding?

GPT-6 Astra scores higher on coding benchmarks: 73.7 versus 56.2 in the Noometry coding category.

### Which has the bigger context window?

GPT-6 Astra does, with 1.05M tokens against 1.05M.

### How many benchmarks do Gemini 3.7 Flash and GPT-6 Astra share?

44 benchmarks have published results for both models. Gemini 3.7 Flash has 44 scored results on Noometry and GPT-6 Astra has 56.