# Gemini 3.1 Flash Lite vs GPT-5.2

> GPT-5.2 is the stronger model overall, scoring 54.1 to 40.4 on the Noometry Index. Gemini 3.1 Flash Lite costs 8.6× less per token, which makes it the better buy when GPT-5.2's lead doesn't matter for your workload.

- Canonical page: https://noometry.com/compare/gemini-3-1-flash-lite-vs-gpt-5-2
- Last updated: 2026-10-10
- Shared benchmarks: 35

## Summary

- They share 35 benchmarks with published results for both. Gemini 3.1 Flash Lite scores higher in 0 categories and GPT-5.2 in 10 categories; 10 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where GPT-5.2 leads 50.1 to 22.3.
- The biggest single-benchmark swing is NYT Connections (extended): 8.2% for Gemini 3.1 Flash Lite and 83.6% for GPT-5.2.
- Gemini 3.1 Flash Lite is cheaper at $0.25 / $1.50 per million input/output tokens, against $1.75 / $14 for GPT-5.2.
- Gemini 3.1 Flash Lite accepts more context: 1.05M tokens versus 400K.

## Snapshot

| | Gemini 3.1 Flash Lite | GPT-5.2 |
|---|---|---|
| Provider | Google | OpenAI |
| Noometry Index | 40.4 | 54.1 |
| Rank | 141 | 31 |
| Context | 1.05M | 400K |
| Input $/M | $0.25 | $1.75 |
| Output $/M | $1.50 | $14 |
| Weights | Proprietary | Proprietary |

## Coding

- Gemini 3.1 Flash Lite: 37.5 (#179)
- GPT-5.2: 52.2 (#32)

| Benchmark | Gemini 3.1 Flash Lite | GPT-5.2 |
|---|---|---|
| LMArena WebDev | 1256 | 1415 |
| WeirdML | 52.2% | 72.2% |
| LMArena Coding | 1400 | 1447 |
| ALE-Bench | 797.73 | 1,294 |
| SWE-bench Verified | — | 73.8% |
| SWE-bench Verified (bash only) | — | 72.8% |
| SWE-bench Multilingual | — | 66.7% |
| SciCode | 41.9% | — |
| GSO | — | 27.4% |
| AlgoTune | — | 2.05 |

## Agentic & Tool Use

- Gemini 3.1 Flash Lite: 29.9 (#72)
- GPT-5.2: 40.0 (#24)

| Benchmark | Gemini 3.1 Flash Lite | GPT-5.2 |
|---|---|---|
| DeepResearch Bench | 37.3% | 41.1% |
| Terminal-Bench | — | 64.9% |
| Berkeley Function Calling Leaderboard | — | 55.9% |
| GDPval | — | 49.7% |
| Remote Labor Index | — | 2.5% |
| τ²-bench Airline | — | 83% |
| τ²-bench Banking | — | 32.2% |
| τ²-bench Retail | — | 81.6% |
| τ²-bench Telecom | — | 89.7% |
| LMArena Search | — | 1207 |
| METR Time Horizons | — | 75.3% |
| Vending-Bench 2 | — | 3,591 |

## Reasoning

- Gemini 3.1 Flash Lite: 22.3 (#181)
- GPT-5.2: 50.1 (#33)

| Benchmark | Gemini 3.1 Flash Lite | GPT-5.2 |
|---|---|---|
| Kagi LLM Benchmark | 67.2% | 73.3% |
| NYT Connections (extended) | 8.2% | 83.6% |
| Chess Puzzles | 25% | 49% |
| EnigmaEval | 3% | 10.4% |
| LMArena Hard Prompts | 1407 | 1445 |
| DTBench | 76.8% | 90.9% |
| LMCA | 35% | 43.9% |
| Epoch Capabilities Index | 144.45 | 153.45 |
| ForecastBench | 54.4 | 60.1 |
| ARC-AGI-2 | — | 52.9% |
| SimpleBench | — | 45.8% |
| ARC-AGI-1 | — | 86.2% |
| CritPt | 1.1% | — |
| Thematic Generalization | 63.3% | — |
| EBR-Bench | — | 23% |
| Mystery Game Puzzles | — | 23% |

## Math

- Gemini 3.1 Flash Lite: 39.5 (#82)
- GPT-5.2: 59.8 (#32)

| Benchmark | Gemini 3.1 Flash Lite | GPT-5.2 |
|---|---|---|
| FrontierMath (Tiers 1-3) | 27.7% | 67.4% |
| OTIS Mock AIME 2024-2025 | 80% | 96.1% |
| LMArena Math | 1427 | 1439 |
| FrontierMath Tier 4 | — | 31.7% |
| MathArena Final-Answer Competitions | — | 72% |
| ProofBench | — | 15% |
| FrontierMath (Feb 2025 set) | — | 40.7% |
| FrontierMath Tier 4 (v1) | — | 18.8% |

## Knowledge

- Gemini 3.1 Flash Lite: 41.7 (#95)
- GPT-5.2: 59.2 (#29)

| Benchmark | Gemini 3.1 Flash Lite | GPT-5.2 |
|---|---|---|
| GPQA Diamond | 81.8% | 91.4% |
| Humanity's Last Exam | 8.6% | 27.8% |
| Vectara Hallucination Rate | 8.2% | 8.4% |
| LMArena Expert | 1397 | 1445 |
| SimpleQA Verified | — | 37.1% |

## Multimodal

- Gemini 3.1 Flash Lite: 38.7 (#57)
- GPT-5.2: 50.9 (#7)

| Benchmark | Gemini 3.1 Flash Lite | GPT-5.2 |
|---|---|---|
| LMArena Vision | 1240 | 1268 |
| VPCT | — | 84% |
| Furniture Assembly | — | 38.3% |
| LMArena Document | — | 1405 |

## Multilingual

- Gemini 3.1 Flash Lite: 52.5 (#82)
- GPT-5.2: 53.6 (#63)

| Benchmark | Gemini 3.1 Flash Lite | GPT-5.2 |
|---|---|---|
| LMArena Non-English | 1410 | 1425 |
| LMArena Chinese | 1461 | 1460 |
| LMArena French | 1423 | 1456 |
| LMArena German | 1429 | 1448 |
| LMArena Japanese | 1411 | 1421 |
| LMArena Korean | 1393 | 1390 |
| LMArena Russian | 1420 | 1440 |
| LMArena Spanish | 1420 | 1433 |

## Instruction Following

- Gemini 3.1 Flash Lite: 72.9 (#126)
- GPT-5.2: 74.9 (#83)

| Benchmark | Gemini 3.1 Flash Lite | GPT-5.2 |
|---|---|---|
| LMArena Instruction Following | 1376 | 1417 |

## Long Context

- Gemini 3.1 Flash Lite: 42.5 (#117)
- GPT-5.2: 44.0 (#74)

| Benchmark | Gemini 3.1 Flash Lite | GPT-5.2 |
|---|---|---|
| LMArena Longer Query | 1394 | 1428 |
| CL-bench | — | 18.2% |

## Writing & Preference

- Gemini 3.1 Flash Lite: 61.0 (#90)
- GPT-5.2: 67.0 (#30)

| Benchmark | Gemini 3.1 Flash Lite | GPT-5.2 |
|---|---|---|
| LMArena Text | 1416 | 1439 |
| LMArena Creative Writing | 1401 | 1402 |
| LMArena Multi-Turn | 1417 | 1458 |
| EQ-Bench Creative Writing | — | 1703 |

## FAQ

### Is Gemini 3.1 Flash Lite better than GPT-5.2?

GPT-5.2 is the stronger model overall, scoring 54.1 to 40.4 on the Noometry Index. Gemini 3.1 Flash Lite costs 8.6× less per token, which makes it the better buy when GPT-5.2's lead doesn't matter for your workload.

### Which is cheaper, Gemini 3.1 Flash Lite or GPT-5.2?

Gemini 3.1 Flash Lite is cheaper. It lists at $0.25 per million input tokens and $1.50 per million output tokens; GPT-5.2 lists at $1.75 and $14.

### Is Gemini 3.1 Flash Lite or GPT-5.2 better for coding?

GPT-5.2 scores higher on coding benchmarks: 52.2 versus 37.5 in the Noometry coding category.

### Which has the bigger context window?

Gemini 3.1 Flash Lite does, with 1.05M tokens against 400K.

### How many benchmarks do Gemini 3.1 Flash Lite and GPT-5.2 share?

35 benchmarks have published results for both models. Gemini 3.1 Flash Lite has 38 scored results on Noometry and GPT-5.2 has 67.