# Gemini 2.5 Flash-Lite vs gpt-oss-20b

> Gemini 2.5 Flash-Lite is the stronger model overall, scoring 36.4 to 32.1 on the Noometry Index. gpt-oss-20b costs 4.9× less per token, which makes it the better buy when Gemini 2.5 Flash-Lite's lead doesn't matter for your workload.

- Canonical page: https://noometry.com/compare/gemini-2-5-flash-lite-vs-gpt-oss-20b
- Last updated: 2026-10-10
- Shared benchmarks: 27

## Summary

- They share 27 benchmarks with published results for both. Gemini 2.5 Flash-Lite scores higher in 6 categories and gpt-oss-20b in 3 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where Gemini 2.5 Flash-Lite leads 57.0 to 35.8.
- The biggest single-benchmark swing is GPQA (HELM): 30.9% for Gemini 2.5 Flash-Lite and 59.4% for gpt-oss-20b.
- gpt-oss-20b is cheaper at $0.018 / $0.09 per million input/output tokens, against $0.10 / $0.40 for Gemini 2.5 Flash-Lite.
- Gemini 2.5 Flash-Lite accepts more context: 1.05M tokens versus 131K.
- gpt-oss-20b has downloadable open weights; the other is API-only.

## Snapshot

| | Gemini 2.5 Flash-Lite | gpt-oss-20b |
|---|---|---|
| Provider | Google | OpenAI |
| Noometry Index | 36.4 | 32.1 |
| Rank | 208 | 249 |
| Context | 1.05M | 131K |
| Input $/M | $0.10 | $0.018 |
| Output $/M | $0.40 | $0.09 |
| Weights | Proprietary | Open |

## Coding

- Gemini 2.5 Flash-Lite: 38.0 (#167)
- gpt-oss-20b: 37.1 (#185)

| Benchmark | Gemini 2.5 Flash-Lite | gpt-oss-20b |
|---|---|---|
| WeirdML | 35.2% | 40.9% |
| LMArena Coding | 1373 | 1307 |
| ALE-Bench | 325.9 | 566.05 |
| SciCode | — | 34.4% |

## Agentic & Tool Use

- Gemini 2.5 Flash-Lite: 27.8 (#89)
- gpt-oss-20b: 9.2 (#146)

| Benchmark | Gemini 2.5 Flash-Lite | gpt-oss-20b |
|---|---|---|
| Terminal-Bench | — | 3.4% |
| Berkeley Function Calling Leaderboard | 36.9% | — |

## Reasoning

- Gemini 2.5 Flash-Lite: 21.5 (#196)
- gpt-oss-20b: 18.8 (#251)

| Benchmark | Gemini 2.5 Flash-Lite | gpt-oss-20b |
|---|---|---|
| Kagi LLM Benchmark | 40.5% | 53.2% |
| LMArena Hard Prompts | 1377 | 1274 |
| DTBench | 62.8% | 68% |
| LMCA | 18.1% | 14.5% |
| Epoch Capabilities Index | 133.93 | 137.81 |
| CritPt | — | 1.4% |
| Chess Puzzles | — | 4% |

## Math

- Gemini 2.5 Flash-Lite: 35.5 (#144)
- gpt-oss-20b: 37.6 (#93)

| Benchmark | Gemini 2.5 Flash-Lite | gpt-oss-20b |
|---|---|---|
| Omni-MATH | 48% | 56.5% |
| LMArena Math | 1373 | 1317 |
| OTIS Mock AIME 2024-2025 | — | 65.3% |

## Knowledge

- Gemini 2.5 Flash-Lite: 32.1 (#206)
- gpt-oss-20b: 34.6 (#186)

| Benchmark | Gemini 2.5 Flash-Lite | gpt-oss-20b |
|---|---|---|
| MMLU-Pro | 53.7% | 74% |
| GPQA (HELM) | 30.9% | 59.4% |
| LMArena Expert | 1373 | 1258 |
| GPQA Diamond | — | 60.8% |
| Vectara Hallucination Rate | 3.3% | — |

## Multimodal

- Gemini 2.5 Flash-Lite: 28.6 (#109)
- gpt-oss-20b: —

| Benchmark | Gemini 2.5 Flash-Lite | gpt-oss-20b |
|---|---|---|
| LMArena Vision | 1198 | — |
| VPCT | 30% | — |

## Multilingual

- Gemini 2.5 Flash-Lite: 49.5 (#129)
- gpt-oss-20b: 42.4 (#192)

| Benchmark | Gemini 2.5 Flash-Lite | gpt-oss-20b |
|---|---|---|
| LMArena Non-English | 1369 | 1269 |
| LMArena Chinese | 1404 | 1311 |
| LMArena German | 1390 | 1249 |
| LMArena Japanese | 1359 | 1245 |
| LMArena Korean | 1358 | 1239 |
| LMArena Russian | 1373 | 1279 |
| LMArena Spanish | 1396 | 1267 |
| LMArena French | 1388 | — |

## Instruction Following

- Gemini 2.5 Flash-Lite: 70.2 (#163)
- gpt-oss-20b: 62.0 (#235)

| Benchmark | Gemini 2.5 Flash-Lite | gpt-oss-20b |
|---|---|---|
| IFEval | 81% | 73.2% |
| LMArena Instruction Following | 1366 | 1236 |

## Long Context

- Gemini 2.5 Flash-Lite: 33.3 (#257)
- gpt-oss-20b: 37.9 (#203)

| Benchmark | Gemini 2.5 Flash-Lite | gpt-oss-20b |
|---|---|---|
| LMArena Longer Query | 1373 | 1251 |
| Fiction.LiveBench | 47.2% | — |

## Writing & Preference

- Gemini 2.5 Flash-Lite: 57.0 (#130)
- gpt-oss-20b: 35.8 (#260)

| Benchmark | Gemini 2.5 Flash-Lite | gpt-oss-20b |
|---|---|---|
| LMArena Text | 1379 | 1288 |
| LMArena Creative Writing | 1366 | 1201 |
| WildBench | 81.8% | 73.7% |
| LMArena Multi-Turn | 1367 | 1268 |
| EQ-Bench Creative Writing | — | 666 |

## FAQ

### Is Gemini 2.5 Flash-Lite better than gpt-oss-20b?

Gemini 2.5 Flash-Lite is the stronger model overall, scoring 36.4 to 32.1 on the Noometry Index. gpt-oss-20b costs 4.9× less per token, which makes it the better buy when Gemini 2.5 Flash-Lite's lead doesn't matter for your workload.

### Which is cheaper, Gemini 2.5 Flash-Lite or gpt-oss-20b?

gpt-oss-20b is cheaper. It lists at $0.018 per million input tokens and $0.09 per million output tokens; Gemini 2.5 Flash-Lite lists at $0.10 and $0.40.

### Is Gemini 2.5 Flash-Lite or gpt-oss-20b better for coding?

They score almost the same on coding (38.0 vs 37.1); test both on your own repository before choosing.

### Which has the bigger context window?

Gemini 2.5 Flash-Lite does, with 1.05M tokens against 131K.

### How many benchmarks do Gemini 2.5 Flash-Lite and gpt-oss-20b share?

27 benchmarks have published results for both models. Gemini 2.5 Flash-Lite has 33 scored results on Noometry and gpt-oss-20b has 34.