# DeepSeek-R1 vs gpt-oss-20b

> DeepSeek-R1 is the stronger model overall, scoring 42.0 to 32.1 on the Noometry Index. gpt-oss-20b costs 25× less per token, which makes it the better buy when DeepSeek-R1's lead doesn't matter for your workload.

- Canonical page: https://noometry.com/compare/deepseek-r1-vs-gpt-oss-20b
- Last updated: 2026-10-10
- Shared benchmarks: 30

## Summary

- They share 30 benchmarks with published results for both. DeepSeek-R1 scores higher in 8 categories and gpt-oss-20b in 1 category; 8 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where DeepSeek-R1 leads 61.5 to 35.8.
- The biggest single-benchmark swing is Kagi LLM Benchmark: 69.4% for DeepSeek-R1 and 53.2% for gpt-oss-20b.
- gpt-oss-20b is cheaper at $0.018 / $0.09 per million input/output tokens, against $0.50 / $2.15 for DeepSeek-R1.
- DeepSeek-R1 accepts more context: 164K tokens versus 131K.
- gpt-oss-20b has downloadable open weights; the other is API-only.

## Snapshot

| | DeepSeek-R1 | gpt-oss-20b |
|---|---|---|
| Provider | DeepSeek | OpenAI |
| Noometry Index | 42.0 | 32.1 |
| Rank | 110 | 249 |
| Context | 164K | 131K |
| Input $/M | $0.50 | $0.018 |
| Output $/M | $2.15 | $0.09 |
| Weights | Proprietary | Open |

## Coding

- DeepSeek-R1: 45.9 (#63)
- gpt-oss-20b: 37.1 (#185)

| Benchmark | DeepSeek-R1 | gpt-oss-20b |
|---|---|---|
| SciCode | 35.7% | 34.4% |
| WeirdML | 41.6% | 40.9% |
| LMArena Coding | 1427 | 1307 |
| ALE-Bench | 804.12 | 566.05 |
| Aider Polyglot | 71.4% | — |
| LiveBench Coding | 66.7% | — |
| AlgoTune | 1.7 | — |

## Agentic & Tool Use

- DeepSeek-R1: 30.4 (#68)
- gpt-oss-20b: 9.2 (#146)

| Benchmark | DeepSeek-R1 | gpt-oss-20b |
|---|---|---|
| Terminal-Bench | — | 3.4% |
| DeepResearch Bench | 35.1% | — |
| BALROG | 34.9% | — |
| METR Time Horizons | 53.8% | — |

## Reasoning

- DeepSeek-R1: 18.7 (#253)
- gpt-oss-20b: 18.8 (#251)

| Benchmark | DeepSeek-R1 | gpt-oss-20b |
|---|---|---|
| Kagi LLM Benchmark | 69.4% | 53.2% |
| CritPt | 1.1% | 1.4% |
| LMArena Hard Prompts | 1415 | 1274 |
| Epoch Capabilities Index | 141.3 | 137.81 |
| ARC-AGI-2 | 1.3% | — |
| SimpleBench | 40.8% | — |
| ARC-AGI-1 | 21.2% | — |
| Chess Puzzles | — | 4% |
| LiveBench Reasoning | 83.2% | — |
| DTBench | — | 68% |
| LiveBench Data Analysis | 69.8% | — |
| LMCA | — | 14.5% |
| ForecastBench | 60 | — |
| LiveBench | 71.6% | — |

## Math

- DeepSeek-R1: 42.0 (#70)
- gpt-oss-20b: 37.6 (#93)

| Benchmark | DeepSeek-R1 | gpt-oss-20b |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 66.4% | 65.3% |
| Omni-MATH | 42.4% | 56.5% |
| LMArena Math | 1401 | 1317 |
| LiveBench Math | 80.7% | — |
| MATH Level 5 | 96.6% | — |

## Knowledge

- DeepSeek-R1: 44.3 (#81)
- gpt-oss-20b: 34.6 (#186)

| Benchmark | DeepSeek-R1 | gpt-oss-20b |
|---|---|---|
| GPQA Diamond | 76.3% | 60.8% |
| MMLU-Pro | 79.3% | 74% |
| GPQA (HELM) | 66.6% | 59.4% |
| LMArena Expert | 1394 | 1258 |
| Confabulations | 12.7% | — |
| Vectara Hallucination Rate | 11.3% | — |

## Multilingual

- DeepSeek-R1: 52.6 (#80)
- gpt-oss-20b: 42.4 (#192)

| Benchmark | DeepSeek-R1 | gpt-oss-20b |
|---|---|---|
| LMArena Non-English | 1412 | 1269 |
| LMArena Chinese | 1443 | 1311 |
| LMArena German | 1405 | 1249 |
| LMArena Japanese | 1394 | 1245 |
| LMArena Korean | 1359 | 1239 |
| LMArena Russian | 1423 | 1279 |
| LMArena Spanish | 1410 | 1267 |
| LMArena French | 1415 | — |

## Instruction Following

- DeepSeek-R1: 72.2 (#138)
- gpt-oss-20b: 62.0 (#235)

| Benchmark | DeepSeek-R1 | gpt-oss-20b |
|---|---|---|
| IFEval | 78.4% | 73.2% |
| LMArena Instruction Following | 1382 | 1236 |
| LiveBench Instruction Following | 80.5% | — |

## Long Context

- DeepSeek-R1: 45.4 (#36)
- gpt-oss-20b: 37.9 (#203)

| Benchmark | DeepSeek-R1 | gpt-oss-20b |
|---|---|---|
| LMArena Longer Query | 1391 | 1251 |
| Fiction.LiveBench | 75% | — |

## Writing & Preference

- DeepSeek-R1: 61.5 (#84)
- gpt-oss-20b: 35.8 (#260)

| Benchmark | DeepSeek-R1 | gpt-oss-20b |
|---|---|---|
| LMArena Text | 1428 | 1288 |
| LMArena Creative Writing | 1406 | 1201 |
| EQ-Bench Creative Writing | 1500 | 666 |
| WildBench | 82.8% | 73.7% |
| LMArena Multi-Turn | 1404 | 1268 |
| Short-Story Creative Writing | 83% | — |
| LiveBench Language | 48.5% | — |

## FAQ

### Is DeepSeek-R1 better than gpt-oss-20b?

DeepSeek-R1 is the stronger model overall, scoring 42.0 to 32.1 on the Noometry Index. gpt-oss-20b costs 25× less per token, which makes it the better buy when DeepSeek-R1's lead doesn't matter for your workload.

### Which is cheaper, DeepSeek-R1 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; DeepSeek-R1 lists at $0.50 and $2.15.

### Is DeepSeek-R1 or gpt-oss-20b better for coding?

DeepSeek-R1 scores higher on coding benchmarks: 45.9 versus 37.1 in the Noometry coding category.

### Which has the bigger context window?

DeepSeek-R1 does, with 164K tokens against 131K.

### How many benchmarks do DeepSeek-R1 and gpt-oss-20b share?

30 benchmarks have published results for both models. DeepSeek-R1 has 52 scored results on Noometry and gpt-oss-20b has 34.