# Gemini 3.7 Flash vs GPT-5.3 Codex

> Gemini 3.7 Flash is the stronger model overall, scoring 59.8 to 45.8 on the Noometry Index.

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

## Summary

- They share 3 benchmarks with published results for both. Gemini 3.7 Flash scores higher in 1 category and GPT-5.3 Codex in 1 category; 2 gaps are clear of the uncertainty.
- The widest gap is in coding, where Gemini 3.7 Flash leads 56.2 to 48.6.
- Gemini 3.7 Flash is cheaper at $0.75 / $3.75 per million input/output tokens, against $1.75 / $14 for GPT-5.3 Codex.
- Gemini 3.7 Flash accepts more context: 1.05M tokens versus 400K.

## Snapshot

| | Gemini 3.7 Flash | GPT-5.3 Codex |
|---|---|---|
| Provider | Google | OpenAI |
| Noometry Index | 59.8 | 45.8 |
| Rank | 14 | 69 |
| Context | 1.05M | 400K |
| Input $/M | $0.75 | $1.75 |
| Output $/M | $3.75 | $14 |
| Weights | Proprietary | Proprietary |

## Coding

- Gemini 3.7 Flash: 56.2 (#22)
- GPT-5.3 Codex: 48.6 (#56)

| Benchmark | Gemini 3.7 Flash | GPT-5.3 Codex |
|---|---|---|
| LMArena WebDev | 1592 | 1409 |
| ALE-Bench | 904.3 | 1,655 |
| SWE-bench Verified | — | 74.8% |
| DeepSWE | 65.5% | — |
| FrontierCode | 43.6% | — |
| FrontierSWE | 20.3% | — |
| SciCode | 59.8% | — |
| WeirdML | — | 79.3% |
| LMArena Coding | 1497 | — |

## Agentic & Tool Use

- Gemini 3.7 Flash: 42.1 (#19)
- GPT-5.3 Codex: 48.0 (#9)

| Benchmark | Gemini 3.7 Flash | GPT-5.3 Codex |
|---|---|---|
| Terminal-Bench | — | 78.4% |
| APEX-Agents | 67.8% | — |
| Remote Labor Index | 5% | — |
| GDP.pdf | 23.8% | — |
| METR Time Horizons | — | 74.5% |
| Vending-Bench 2 | — | 5,940 |

## Reasoning

- Gemini 3.7 Flash: 70.0 (#15)
- GPT-5.3 Codex: —

| Benchmark | Gemini 3.7 Flash | GPT-5.3 Codex |
|---|---|---|
| Epoch Capabilities Index | 157.27 | 156.77 |
| ARC-AGI-2 | 84.6% | — |
| NYT Connections (extended) | 94% | — |
| ARC-AGI-1 | 95.5% | — |
| CritPt | 14.3% | — |
| Chess Puzzles | 47% | — |
| LMArena Hard Prompts | 1494 | — |
| Mystery Game Puzzles | 37% | — |
| DTBench | 96.8% | — |
| LMCA | 50.4% | — |

## Math

- Gemini 3.7 Flash: 69.6 (#23)
- GPT-5.3 Codex: —

| Benchmark | Gemini 3.7 Flash | GPT-5.3 Codex |
|---|---|---|
| FrontierMath (Tiers 1-3) | 71.6% | — |
| FrontierMath Tier 4 | 36.6% | — |
| OTIS Mock AIME 2024-2025 | 97.2% | — |
| ProofBench | 58% | — |
| LMArena Math | 1507 | — |

## Knowledge

- Gemini 3.7 Flash: 69.7 (#5)
- GPT-5.3 Codex: —

| Benchmark | Gemini 3.7 Flash | GPT-5.3 Codex |
|---|---|---|
| GPQA Diamond | 94.8% | — |
| SimpleQA Verified | 69.2% | — |
| LMArena Expert | 1508 | — |

## Multimodal

- Gemini 3.7 Flash: 37.3 (#73)
- GPT-5.3 Codex: —

| Benchmark | Gemini 3.7 Flash | GPT-5.3 Codex |
|---|---|---|
| LMArena Vision | 1316 | — |
| Furniture Assembly | 26.7% | — |

## Multilingual

- Gemini 3.7 Flash: 57.6 (#7)
- GPT-5.3 Codex: —

| Benchmark | Gemini 3.7 Flash | GPT-5.3 Codex |
|---|---|---|
| LMArena Non-English | 1484 | — |
| LMArena Chinese | 1548 | — |
| LMArena French | 1505 | — |
| LMArena German | 1498 | — |
| LMArena Japanese | 1512 | — |
| LMArena Korean | 1483 | — |
| LMArena Russian | 1516 | — |
| LMArena Spanish | 1503 | — |

## Instruction Following

- Gemini 3.7 Flash: 77.7 (#15)
- GPT-5.3 Codex: —

| Benchmark | Gemini 3.7 Flash | GPT-5.3 Codex |
|---|---|---|
| LMArena Instruction Following | 1483 | — |

## Long Context

- Gemini 3.7 Flash: 45.7 (#30)
- GPT-5.3 Codex: —

| Benchmark | Gemini 3.7 Flash | GPT-5.3 Codex |
|---|---|---|
| LMArena Longer Query | 1492 | — |

## Writing & Preference

- Gemini 3.7 Flash: 71.2 (#20)
- GPT-5.3 Codex: —

| Benchmark | Gemini 3.7 Flash | GPT-5.3 Codex |
|---|---|---|
| LMArena Text | 1486 | — |
| LMArena Creative Writing | 1490 | — |
| EQ-Bench Creative Writing | 1723 | — |
| LMArena Multi-Turn | 1489 | — |

## FAQ

### Is Gemini 3.7 Flash better than GPT-5.3 Codex?

Gemini 3.7 Flash is the stronger model overall, scoring 59.8 to 45.8 on the Noometry Index.

### Which is cheaper, Gemini 3.7 Flash or GPT-5.3 Codex?

Gemini 3.7 Flash is cheaper. It lists at $0.75 per million input tokens and $3.75 per million output tokens; GPT-5.3 Codex lists at $1.75 and $14.

### Is Gemini 3.7 Flash or GPT-5.3 Codex better for coding?

Gemini 3.7 Flash scores higher on coding benchmarks: 56.2 versus 48.6 in the Noometry coding category.

### Which has the bigger context window?

Gemini 3.7 Flash does, with 1.05M tokens against 400K.

### How many benchmarks do Gemini 3.7 Flash and GPT-5.3 Codex share?

3 benchmarks have published results for both models. Gemini 3.7 Flash has 44 scored results on Noometry and GPT-5.3 Codex has 8.