# Gemini 2.5 Flash vs GPT-5.3 Chat

> GPT-5.3 Chat is the stronger model overall, scoring 42.1 to 39.0 on the Noometry Index. Gemini 2.5 Flash costs 5.7× less per token, which makes it the better buy when GPT-5.3 Chat's lead doesn't matter for your workload.

- Canonical page: https://noometry.com/compare/gemini-2-5-flash-vs-gpt-5-3-chat
- Last updated: 2026-10-10
- Shared benchmarks: 18

## Summary

- They share 18 benchmarks with published results for both. Gemini 2.5 Flash scores higher in 4 categories and GPT-5.3 Chat in 4 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where GPT-5.3 Chat leads 63.3 to 54.0.
- Gemini 2.5 Flash is cheaper at $0.30 / $2.50 per million input/output tokens, against $1.75 / $14 for GPT-5.3 Chat.
- Gemini 2.5 Flash accepts more context: 1.05M tokens versus 128K.

## Snapshot

| | Gemini 2.5 Flash | GPT-5.3 Chat |
|---|---|---|
| Provider | Google | OpenAI |
| Noometry Index | 39.0 | 42.1 |
| Rank | 162 | 109 |
| Context | 1.05M | 128K |
| Input $/M | $0.30 | $1.75 |
| Output $/M | $2.50 | $14 |
| Weights | Proprietary | Proprietary |

## Coding

- Gemini 2.5 Flash: 35.5 (#210)
- GPT-5.3 Chat: 40.8 (#124)

| Benchmark | Gemini 2.5 Flash | GPT-5.3 Chat |
|---|---|---|
| LMArena Coding | 1424 | 1408 |
| SWE-bench Verified (bash only) | 28.7% | — |
| Aider Polyglot | 55.1% | — |
| WeirdML | 41.9% | — |
| ALE-Bench | 661.88 | — |

## Agentic & Tool Use

- Gemini 2.5 Flash: 30.6 (#67)
- GPT-5.3 Chat: —

| Benchmark | Gemini 2.5 Flash | GPT-5.3 Chat |
|---|---|---|
| Terminal-Bench | 17.1% | — |
| Berkeley Function Calling Leaderboard | 56.2% | — |
| TheAgentCompany | 41.1% | — |
| BALROG | 33.5% | — |
| Vending-Bench 2 | 548.84 | — |

## Reasoning

- Gemini 2.5 Flash: 18.2 (#271)
- GPT-5.3 Chat: 27.3 (#105)

| Benchmark | Gemini 2.5 Flash | GPT-5.3 Chat |
|---|---|---|
| LMArena Hard Prompts | 1422 | 1399 |
| ARC-AGI-2 | 2.5% | — |
| SimpleBench | 41.2% | — |
| Kagi LLM Benchmark | 56.8% | — |
| ARC-AGI-1 | 33.3% | — |
| CritPt | 1.1% | — |
| EnigmaEval | 2.7% | — |
| DTBench | 76.5% | — |
| LMCA | 27.5% | — |
| Epoch Capabilities Index | 143.04 | — |
| ForecastBench | 60.6 | — |

## Math

- Gemini 2.5 Flash: 38.1 (#87)
- GPT-5.3 Chat: 35.4 (#146)

| Benchmark | Gemini 2.5 Flash | GPT-5.3 Chat |
|---|---|---|
| LMArena Math | 1415 | 1389 |
| OTIS Mock AIME 2024-2025 | 73.1% | — |
| Omni-MATH | 38.5% | — |
| FrontierMath (Feb 2025 set) | 4.8% | — |
| FrontierMath Tier 4 (v1) | 4.2% | — |

## Knowledge

- Gemini 2.5 Flash: 36.1 (#162)
- GPT-5.3 Chat: 38.2 (#137)

| Benchmark | Gemini 2.5 Flash | GPT-5.3 Chat |
|---|---|---|
| LMArena Expert | 1426 | 1397 |
| Humanity's Last Exam | 12.1% | — |
| MMLU-Pro | 63.9% | — |
| Confabulations | 16.8% | — |
| Vectara Hallucination Rate | 7.8% | — |
| GPQA (HELM) | 39% | — |

## Multimodal

- Gemini 2.5 Flash: 41.2 (#31)
- GPT-5.3 Chat: —

| Benchmark | Gemini 2.5 Flash | GPT-5.3 Chat |
|---|---|---|
| LMArena Vision | 1254 | — |
| GeoBench | 76% | — |
| VPCT | 46.2% | — |
| SpatialViz-Bench | 36.9% | — |

## Multilingual

- Gemini 2.5 Flash: 52.5 (#83)
- GPT-5.3 Chat: 50.5 (#119)

| Benchmark | Gemini 2.5 Flash | GPT-5.3 Chat |
|---|---|---|
| LMArena Non-English | 1410 | 1383 |
| LMArena Chinese | 1450 | 1433 |
| LMArena French | 1433 | 1398 |
| LMArena German | 1419 | 1384 |
| LMArena Japanese | 1403 | 1351 |
| LMArena Korean | 1385 | 1347 |
| LMArena Russian | 1415 | 1400 |
| LMArena Spanish | 1421 | 1371 |

## Instruction Following

- Gemini 2.5 Flash: 75.9 (#50)
- GPT-5.3 Chat: 73.0 (#124)

| Benchmark | Gemini 2.5 Flash | GPT-5.3 Chat |
|---|---|---|
| LMArena Instruction Following | 1405 | 1378 |
| IFEval | 89.8% | — |

## Long Context

- Gemini 2.5 Flash: 47.5 (#16)
- GPT-5.3 Chat: 42.6 (#115)

| Benchmark | Gemini 2.5 Flash | GPT-5.3 Chat |
|---|---|---|
| LMArena Longer Query | 1419 | 1396 |
| Fiction.LiveBench | 77.8% | — |

## Writing & Preference

- Gemini 2.5 Flash: 54.0 (#153)
- GPT-5.3 Chat: 63.3 (#65)

| Benchmark | Gemini 2.5 Flash | GPT-5.3 Chat |
|---|---|---|
| LMArena Text | 1417 | 1389 |
| LMArena Creative Writing | 1400 | 1356 |
| EQ-Bench Creative Writing | 1137 | 1690 |
| LMArena Multi-Turn | 1408 | 1413 |
| Short-Story Creative Writing | 76.5% | — |
| WildBench | 81.7% | — |

## FAQ

### Is Gemini 2.5 Flash better than GPT-5.3 Chat?

GPT-5.3 Chat is the stronger model overall, scoring 42.1 to 39.0 on the Noometry Index. Gemini 2.5 Flash costs 5.7× less per token, which makes it the better buy when GPT-5.3 Chat's lead doesn't matter for your workload.

### Which is cheaper, Gemini 2.5 Flash or GPT-5.3 Chat?

Gemini 2.5 Flash is cheaper. It lists at $0.30 per million input tokens and $2.50 per million output tokens; GPT-5.3 Chat lists at $1.75 and $14.

### Is Gemini 2.5 Flash or GPT-5.3 Chat better for coding?

GPT-5.3 Chat scores higher on coding benchmarks: 40.8 versus 35.5 in the Noometry coding category.

### Which has the bigger context window?

Gemini 2.5 Flash does, with 1.05M tokens against 128K.

### How many benchmarks do Gemini 2.5 Flash and GPT-5.3 Chat share?

18 benchmarks have published results for both models. Gemini 2.5 Flash has 54 scored results on Noometry and GPT-5.3 Chat has 18.