# Gemini 3.5 Flash vs GPT-5-Codex

> Gemini 3.5 Flash is the stronger model overall, scoring 54.1 to 37.3 on the Noometry Index.

- Canonical page: https://noometry.com/compare/gemini-3-5-flash-vs-gpt-5-codex
- Last updated: 2026-10-10
- Shared benchmarks: 1

## Summary

- They share 1 benchmark with published results for both. Gemini 3.5 Flash scores higher in 2 categories and GPT-5-Codex in 1 category; 3 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where Gemini 3.5 Flash leads 62.7 to 30.0.
- The biggest single-benchmark swing is WeirdML: 62.6% for Gemini 3.5 Flash and 54.5% for GPT-5-Codex.
- Both cost about the same: $1.50 input and $9 output per million tokens.
- Gemini 3.5 Flash accepts more context: 1.05M tokens versus 400K.

## Snapshot

| | Gemini 3.5 Flash | GPT-5-Codex |
|---|---|---|
| Provider | Google | OpenAI |
| Noometry Index | 54.1 | 37.3 |
| Rank | 29 | 190 |
| Context | 1.05M | 400K |
| Input $/M | $1.50 | $1.25 |
| Output $/M | $9 | $10 |
| Weights | Proprietary | Proprietary |

## Coding

- Gemini 3.5 Flash: 49.1 (#46)
- GPT-5-Codex: 41.9 (#100)

| Benchmark | Gemini 3.5 Flash | GPT-5-Codex |
|---|---|---|
| WeirdML | 62.6% | 54.5% |
| SWE-bench Verified | 79.3% | — |
| DeepSWE | 37.4% | — |
| LMArena WebDev | 1499 | — |
| SciCode | 53.1% | — |
| LMArena Coding | 1492 | — |
| ALE-Bench | 911.02 | — |

## Agentic & Tool Use

- Gemini 3.5 Flash: 24.8 (#107)
- GPT-5-Codex: 30.8 (#66)

| Benchmark | Gemini 3.5 Flash | GPT-5-Codex |
|---|---|---|
| Terminal-Bench | — | 44.3% |
| APEX-Agents | 27.5% | — |
| GBAEval | 6.7% | — |
| GDP.pdf | 14% | — |
| Vending-Bench 2 | 5,396 | — |

## Reasoning

- Gemini 3.5 Flash: 62.7 (#16)
- GPT-5-Codex: 30.0 (#80)

| Benchmark | Gemini 3.5 Flash | GPT-5-Codex |
|---|---|---|
| ARC-AGI-2 | 72.1% | — |
| SimpleBench | 76.7% | — |
| Kagi LLM Benchmark | — | 70.3% |
| NYT Connections (extended) | 92.6% | — |
| ARC-AGI-1 | 92.5% | — |
| CritPt | 13.1% | — |
| Chess Puzzles | 50% | — |
| EnigmaEval | 25.4% | — |
| EBR-Bench | 4.8% | — |
| LMArena Hard Prompts | 1488 | — |
| Mystery Game Puzzles | 32% | — |
| DTBench | 94.7% | — |
| LMCA | 47.1% | — |
| Surface Evolver Bench | 58.1% | — |
| Epoch Capabilities Index | 154.55 | — |
| ForecastBench | 59 | — |

## Math

- Gemini 3.5 Flash: 60.5 (#30)
- GPT-5-Codex: —

| Benchmark | Gemini 3.5 Flash | GPT-5-Codex |
|---|---|---|
| FrontierMath (Tiers 1-3) | 62.8% | — |
| FrontierMath Tier 4 | 26.8% | — |
| MathArena Final-Answer Competitions | 76.3% | — |
| OTIS Mock AIME 2024-2025 | 95.6% | — |
| ProofBench | 31% | — |
| LMArena Math | 1502 | — |
| FrontierMath (Feb 2025 set) | 39% | — |
| FrontierMath Tier 4 (v1) | 14.6% | — |

## Knowledge

- Gemini 3.5 Flash: 66.3 (#10)
- GPT-5-Codex: —

| Benchmark | Gemini 3.5 Flash | GPT-5-Codex |
|---|---|---|
| GPQA Diamond | 92.8% | — |
| SimpleQA Verified | 66.2% | — |
| LMArena Expert | 1493 | — |

## Multimodal

- Gemini 3.5 Flash: 45.7 (#13)
- GPT-5-Codex: —

| Benchmark | Gemini 3.5 Flash | GPT-5-Codex |
|---|---|---|
| LMArena Vision | 1311 | — |
| Blueprint-Bench 2 | 33.6% | — |
| LMArena Document | 1463 | — |

## Multilingual

- Gemini 3.5 Flash: 57.1 (#12)
- GPT-5-Codex: —

| Benchmark | Gemini 3.5 Flash | GPT-5-Codex |
|---|---|---|
| LMArena Non-English | 1475 | — |
| LMArena Chinese | 1525 | — |
| LMArena French | 1490 | — |
| LMArena German | 1500 | — |
| LMArena Japanese | 1481 | — |
| LMArena Korean | 1453 | — |
| LMArena Russian | 1491 | — |
| LMArena Spanish | 1478 | — |

## Instruction Following

- Gemini 3.5 Flash: 77.2 (#29)
- GPT-5-Codex: —

| Benchmark | Gemini 3.5 Flash | GPT-5-Codex |
|---|---|---|
| LMArena Instruction Following | 1466 | — |

## Long Context

- Gemini 3.5 Flash: 45.3 (#39)
- GPT-5-Codex: —

| Benchmark | Gemini 3.5 Flash | GPT-5-Codex |
|---|---|---|
| LMArena Longer Query | 1481 | — |

## Writing & Preference

- Gemini 3.5 Flash: 65.5 (#46)
- GPT-5-Codex: —

| Benchmark | Gemini 3.5 Flash | GPT-5-Codex |
|---|---|---|
| LMArena Text | 1481 | — |
| LMArena Creative Writing | 1467 | — |
| EQ-Bench 4 | 1087 | — |
| LMArena Multi-Turn | 1482 | — |

## FAQ

### Is Gemini 3.5 Flash better than GPT-5-Codex?

Gemini 3.5 Flash is the stronger model overall, scoring 54.1 to 37.3 on the Noometry Index.

### Which is cheaper, Gemini 3.5 Flash or GPT-5-Codex?

Gemini 3.5 Flash is cheaper. It lists at $1.50 per million input tokens and $9 per million output tokens; GPT-5-Codex lists at $1.25 and $10.

### Is Gemini 3.5 Flash or GPT-5-Codex better for coding?

Gemini 3.5 Flash scores higher on coding benchmarks: 49.1 versus 41.9 in the Noometry coding category.

### Which has the bigger context window?

Gemini 3.5 Flash does, with 1.05M tokens against 400K.

### How many benchmarks do Gemini 3.5 Flash and GPT-5-Codex share?

1 benchmark has published results for both models. Gemini 3.5 Flash has 54 scored results on Noometry and GPT-5-Codex has 3.