# Gemini 3.1 Flash Lite vs GPT-5.6 Sol

> GPT-5.6 Sol is the stronger model overall, scoring 64.4 to 40.4 on the Noometry Index. Gemini 3.1 Flash Lite costs 14× less per token, which makes it the better buy when GPT-5.6 Sol's lead doesn't matter for your workload.

- Canonical page: https://noometry.com/compare/gemini-3-1-flash-lite-vs-gpt-5-6-sol
- Last updated: 2026-10-10
- Shared benchmarks: 34

## Summary

- They share 34 benchmarks with published results for both. Gemini 3.1 Flash Lite scores higher in 0 categories and GPT-5.6 Sol in 10 categories; 10 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where GPT-5.6 Sol leads 74.7 to 22.3.
- The biggest single-benchmark swing is NYT Connections (extended): 8.2% for Gemini 3.1 Flash Lite and 93.8% for GPT-5.6 Sol.
- Gemini 3.1 Flash Lite is cheaper at $0.25 / $1.50 per million input/output tokens, against $4 / $20 for GPT-5.6 Sol.
- GPT-5.6 Sol accepts more context: 1.05M tokens versus 1.05M.

## Snapshot

| | Gemini 3.1 Flash Lite | GPT-5.6 Sol |
|---|---|---|
| Provider | Google | OpenAI |
| Noometry Index | 40.4 | 64.4 |
| Rank | 141 | 6 |
| Context | 1.05M | 1.05M |
| Input $/M | $0.25 | $4 |
| Output $/M | $1.50 | $20 |
| Weights | Proprietary | Proprietary |

## Coding

- Gemini 3.1 Flash Lite: 37.5 (#179)
- GPT-5.6 Sol: 61.1 (#7)

| Benchmark | Gemini 3.1 Flash Lite | GPT-5.6 Sol |
|---|---|---|
| LMArena WebDev | 1256 | 1619 |
| SciCode | 41.9% | 57.1% |
| WeirdML | 52.2% | 89.4% |
| LMArena Coding | 1400 | 1493 |
| ALE-Bench | 797.73 | 2,177 |
| DeepSWE | — | 72.7% |
| FrontierCode | — | 47.5% |
| CursorBench | — | 41.7% |
| FrontierSWE | — | 32.2% |
| MirrorCode | — | 20% |

## Agentic & Tool Use

- Gemini 3.1 Flash Lite: 29.9 (#72)
- GPT-5.6 Sol: 50.2 (#7)

| Benchmark | Gemini 3.1 Flash Lite | GPT-5.6 Sol |
|---|---|---|
| APEX-Agents | — | 51.4% |
| OSWorld 2.0 | — | 27.3% |
| τ²-bench Banking | — | 46.9% |
| DeepResearch Bench | 37.3% | — |
| PostTrainBench | — | 36.2% |
| BALROG | — | 60% |
| GBAEval | — | 52.6% |
| GDP.pdf | — | 30.7% |
| LMArena Search | — | 1257 |
| Vending-Bench 2 | — | 9,619 |

## Reasoning

- Gemini 3.1 Flash Lite: 22.3 (#181)
- GPT-5.6 Sol: 74.7 (#6)

| Benchmark | Gemini 3.1 Flash Lite | GPT-5.6 Sol |
|---|---|---|
| Kagi LLM Benchmark | 67.2% | 67% |
| NYT Connections (extended) | 8.2% | 93.8% |
| CritPt | 1.1% | 32.3% |
| Chess Puzzles | 25% | 64% |
| EnigmaEval | 3% | 37.1% |
| LMArena Hard Prompts | 1407 | 1481 |
| DTBench | 76.8% | 96% |
| LMCA | 35% | 59.2% |
| Epoch Capabilities Index | 144.45 | 161.99 |
| ARC-AGI-2 | — | 92.5% |
| SimpleBench | — | 71.7% |
| ARC-AGI-1 | — | 97.5% |
| Thematic Generalization | 63.3% | — |
| EBR-Bench | — | 44.8% |
| Mystery Game Puzzles | — | 58% |
| Surface Evolver Bench | — | 93.1% |
| Bench to the Future 3 | — | 0.14 |
| ForecastBench | 54.4 | — |

## Math

- Gemini 3.1 Flash Lite: 39.5 (#82)
- GPT-5.6 Sol: 85.5 (#7)

| Benchmark | Gemini 3.1 Flash Lite | GPT-5.6 Sol |
|---|---|---|
| FrontierMath (Tiers 1-3) | 27.7% | 89.1% |
| OTIS Mock AIME 2024-2025 | 80% | 100% |
| LMArena Math | 1427 | 1472 |
| FrontierMath Tier 4 | — | 82.9% |
| ProofBench | — | 83% |
| FrontierMath Erdős | — | 0% |

## Knowledge

- Gemini 3.1 Flash Lite: 41.7 (#95)
- GPT-5.6 Sol: 64.3 (#16)

| Benchmark | Gemini 3.1 Flash Lite | GPT-5.6 Sol |
|---|---|---|
| GPQA Diamond | 81.8% | 93.5% |
| Vectara Hallucination Rate | 8.2% | 12.4% |
| LMArena Expert | 1397 | 1517 |
| Humanity's Last Exam | 8.6% | — |
| SimpleQA Verified | — | 69.7% |

## Multimodal

- Gemini 3.1 Flash Lite: 38.7 (#57)
- GPT-5.6 Sol: 48.9 (#8)

| Benchmark | Gemini 3.1 Flash Lite | GPT-5.6 Sol |
|---|---|---|
| LMArena Vision | 1240 | 1281 |
| Blueprint-Bench 2 | — | 33.6% |
| Furniture Assembly | — | 56.7% |
| LMArena Document | — | 1483 |

## Multilingual

- Gemini 3.1 Flash Lite: 52.5 (#82)
- GPT-5.6 Sol: 55.4 (#32)

| Benchmark | Gemini 3.1 Flash Lite | GPT-5.6 Sol |
|---|---|---|
| LMArena Non-English | 1410 | 1450 |
| LMArena Chinese | 1461 | 1523 |
| LMArena French | 1423 | 1475 |
| LMArena German | 1429 | 1476 |
| LMArena Japanese | 1411 | 1475 |
| LMArena Korean | 1393 | 1434 |
| LMArena Russian | 1420 | 1466 |
| LMArena Spanish | 1420 | 1449 |

## Instruction Following

- Gemini 3.1 Flash Lite: 72.9 (#126)
- GPT-5.6 Sol: 77.8 (#16)

| Benchmark | Gemini 3.1 Flash Lite | GPT-5.6 Sol |
|---|---|---|
| LMArena Instruction Following | 1376 | 1480 |

## Long Context

- Gemini 3.1 Flash Lite: 42.5 (#117)
- GPT-5.6 Sol: 45.3 (#42)

| Benchmark | Gemini 3.1 Flash Lite | GPT-5.6 Sol |
|---|---|---|
| LMArena Longer Query | 1394 | 1479 |

## Writing & Preference

- Gemini 3.1 Flash Lite: 61.0 (#90)
- GPT-5.6 Sol: 73.5 (#12)

| Benchmark | Gemini 3.1 Flash Lite | GPT-5.6 Sol |
|---|---|---|
| LMArena Text | 1416 | 1456 |
| LMArena Creative Writing | 1401 | 1450 |
| LMArena Multi-Turn | 1417 | 1456 |
| EQ-Bench Creative Writing | — | 1972 |
| EQ-Bench 4 | — | 1250 |

## FAQ

### Is Gemini 3.1 Flash Lite better than GPT-5.6 Sol?

GPT-5.6 Sol is the stronger model overall, scoring 64.4 to 40.4 on the Noometry Index. Gemini 3.1 Flash Lite costs 14× less per token, which makes it the better buy when GPT-5.6 Sol's lead doesn't matter for your workload.

### Which is cheaper, Gemini 3.1 Flash Lite or GPT-5.6 Sol?

Gemini 3.1 Flash Lite is cheaper. It lists at $0.25 per million input tokens and $1.50 per million output tokens; GPT-5.6 Sol lists at $4 and $20.

### Is Gemini 3.1 Flash Lite or GPT-5.6 Sol better for coding?

GPT-5.6 Sol scores higher on coding benchmarks: 61.1 versus 37.5 in the Noometry coding category.

### Which has the bigger context window?

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

### How many benchmarks do Gemini 3.1 Flash Lite and GPT-5.6 Sol share?

34 benchmarks have published results for both models. Gemini 3.1 Flash Lite has 38 scored results on Noometry and GPT-5.6 Sol has 64.