# Gemini 3.7 Flash vs GPT-5.6 Terra

> Gemini 3.7 Flash and GPT-5.6 Terra score almost the same on the Noometry Index (59.8 vs 59.2), so choose on price, context window or the category you care about most.

- Canonical page: https://noometry.com/compare/gemini-3-7-flash-vs-gpt-5-6-terra
- Last updated: 2026-10-10
- Shared benchmarks: 42

## Summary

- They share 42 benchmarks with published results for both. Gemini 3.7 Flash scores higher in 7 categories and GPT-5.6 Terra in 3 categories; 9 gaps are clear of the uncertainty.
- The widest gap is in math, where GPT-5.6 Terra leads 81.6 to 69.6.
- The biggest single-benchmark swing is FrontierMath Tier 4: 36.6% for Gemini 3.7 Flash and 70.7% for GPT-5.6 Terra.
- Gemini 3.7 Flash is cheaper at $0.75 / $3.75 per million input/output tokens, against $2 / $12 for GPT-5.6 Terra.
- GPT-5.6 Terra accepts more context: 1.05M tokens versus 1.05M.

## Snapshot

| | Gemini 3.7 Flash | GPT-5.6 Terra |
|---|---|---|
| Provider | Google | OpenAI |
| Noometry Index | 59.8 | 59.2 |
| Rank | 14 | 17 |
| Context | 1.05M | 1.05M |
| Input $/M | $0.75 | $2 |
| Output $/M | $3.75 | $12 |
| Weights | Proprietary | Proprietary |

## Coding

- Gemini 3.7 Flash: 56.2 (#22)
- GPT-5.6 Terra: 57.7 (#19)

| Benchmark | Gemini 3.7 Flash | GPT-5.6 Terra |
|---|---|---|
| DeepSWE | 65.5% | 69.6% |
| FrontierCode | 43.6% | 41.3% |
| LMArena WebDev | 1592 | 1522 |
| SciCode | 59.8% | 55% |
| LMArena Coding | 1497 | 1484 |
| ALE-Bench | 904.3 | 1,951 |
| CursorBench | — | 41.3% |
| FrontierSWE | 20.3% | — |
| WeirdML | — | 78.3% |

## Agentic & Tool Use

- Gemini 3.7 Flash: 42.1 (#19)
- GPT-5.6 Terra: 40.1 (#25)

| Benchmark | Gemini 3.7 Flash | GPT-5.6 Terra |
|---|---|---|
| APEX-Agents | 67.8% | 58.2% |
| GDP.pdf | 23.8% | 24.7% |
| Remote Labor Index | 5% | — |
| BALROG | — | 53.2% |
| Vending-Bench 2 | — | 7,343 |

## Reasoning

- Gemini 3.7 Flash: 70.0 (#15)
- GPT-5.6 Terra: 60.7 (#21)

| Benchmark | Gemini 3.7 Flash | GPT-5.6 Terra |
|---|---|---|
| ARC-AGI-2 | 84.6% | 83.9% |
| NYT Connections (extended) | 94% | 78.4% |
| ARC-AGI-1 | 95.5% | 96.5% |
| CritPt | 14.3% | 30% |
| Chess Puzzles | 47% | 54% |
| LMArena Hard Prompts | 1494 | 1468 |
| Mystery Game Puzzles | 37% | 35% |
| DTBench | 96.8% | 93.3% |
| LMCA | 50.4% | 55% |
| Epoch Capabilities Index | 157.27 | 159.62 |
| SimpleBench | — | 48.9% |
| Kagi LLM Benchmark | — | 51.3% |
| Surface Evolver Bench | — | 83.8% |

## Math

- Gemini 3.7 Flash: 69.6 (#23)
- GPT-5.6 Terra: 81.6 (#12)

| Benchmark | Gemini 3.7 Flash | GPT-5.6 Terra |
|---|---|---|
| FrontierMath (Tiers 1-3) | 71.6% | 86% |
| FrontierMath Tier 4 | 36.6% | 70.7% |
| OTIS Mock AIME 2024-2025 | 97.2% | 99.7% |
| ProofBench | 58% | 74% |
| LMArena Math | 1507 | 1466 |

## Knowledge

- Gemini 3.7 Flash: 69.7 (#5)
- GPT-5.6 Terra: 61.2 (#30)

| Benchmark | Gemini 3.7 Flash | GPT-5.6 Terra |
|---|---|---|
| GPQA Diamond | 94.8% | 93.3% |
| SimpleQA Verified | 69.2% | 43.2% |
| LMArena Expert | 1508 | 1492 |

## Multimodal

- Gemini 3.7 Flash: 37.3 (#73)
- GPT-5.6 Terra: 47.3 (#11)

| Benchmark | Gemini 3.7 Flash | GPT-5.6 Terra |
|---|---|---|
| LMArena Vision | 1316 | 1271 |
| Furniture Assembly | 26.7% | 54.2% |
| Blueprint-Bench 2 | — | 30.8% |
| LMArena Document | — | 1472 |

## Multilingual

- Gemini 3.7 Flash: 57.6 (#7)
- GPT-5.6 Terra: 54.4 (#44)

| Benchmark | Gemini 3.7 Flash | GPT-5.6 Terra |
|---|---|---|
| LMArena Non-English | 1484 | 1439 |
| LMArena Chinese | 1548 | 1513 |
| LMArena French | 1505 | 1471 |
| LMArena German | 1498 | 1460 |
| LMArena Japanese | 1512 | 1457 |
| LMArena Korean | 1483 | 1425 |
| LMArena Russian | 1516 | 1450 |
| LMArena Spanish | 1503 | 1448 |

## Instruction Following

- Gemini 3.7 Flash: 77.7 (#15)
- GPT-5.6 Terra: 76.4 (#40)

| Benchmark | Gemini 3.7 Flash | GPT-5.6 Terra |
|---|---|---|
| LMArena Instruction Following | 1483 | 1454 |

## Long Context

- Gemini 3.7 Flash: 45.7 (#30)
- GPT-5.6 Terra: 44.4 (#68)

| Benchmark | Gemini 3.7 Flash | GPT-5.6 Terra |
|---|---|---|
| LMArena Longer Query | 1492 | 1451 |

## Writing & Preference

- Gemini 3.7 Flash: 71.2 (#20)
- GPT-5.6 Terra: 70.2 (#23)

| Benchmark | Gemini 3.7 Flash | GPT-5.6 Terra |
|---|---|---|
| LMArena Text | 1486 | 1447 |
| LMArena Creative Writing | 1490 | 1410 |
| EQ-Bench Creative Writing | 1723 | 1855 |
| LMArena Multi-Turn | 1489 | 1449 |
| EQ-Bench 4 | — | 1234 |

## FAQ

### Is Gemini 3.7 Flash better than GPT-5.6 Terra?

Gemini 3.7 Flash and GPT-5.6 Terra score almost the same on the Noometry Index (59.8 vs 59.2), so choose on price, context window or the category you care about most.

### Which is cheaper, Gemini 3.7 Flash or GPT-5.6 Terra?

Gemini 3.7 Flash is cheaper. It lists at $0.75 per million input tokens and $3.75 per million output tokens; GPT-5.6 Terra lists at $2 and $12.

### Is Gemini 3.7 Flash or GPT-5.6 Terra better for coding?

GPT-5.6 Terra scores higher on coding benchmarks: 57.7 versus 56.2 in the Noometry coding category.

### Which has the bigger context window?

GPT-5.6 Terra does, with 1.05M tokens against 1.05M.

### How many benchmarks do Gemini 3.7 Flash and GPT-5.6 Terra share?

42 benchmarks have published results for both models. Gemini 3.7 Flash has 44 scored results on Noometry and GPT-5.6 Terra has 52.