# gpt-oss-20b vs Muse Spark 1.1

> Muse Spark 1.1 is the stronger model overall, scoring 49.9 to 32.5 on the Noometry Index. gpt-oss-20b costs 56× less per token, which makes it the better buy when Muse Spark 1.1's lead doesn't matter for your workload.

- Canonical page: https://noometry.com/compare/gpt-oss-20b-vs-muse-spark-1-1
- Last updated: 2026-10-12
- Shared benchmarks: 22

## Summary

- They share 22 benchmarks with published results for both. gpt-oss-20b scores higher in 0 categories and Muse Spark 1.1 in 9 categories; 9 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where Muse Spark 1.1 leads 73.4 to 35.5.
- The biggest single-benchmark swing is LMCA: 14.5% for gpt-oss-20b and 49.9% for Muse Spark 1.1.
- gpt-oss-20b is cheaper at $0.018 / $0.09 per million input/output tokens, against $1.25 / $4.25 for Muse Spark 1.1.
- Muse Spark 1.1 accepts more context: 1.05M tokens versus 131K.
- gpt-oss-20b has downloadable open weights; the other is API-only.

## Snapshot

| | gpt-oss-20b | Muse Spark 1.1 |
|---|---|---|
| Provider | OpenAI | Meta |
| Noometry Index | 32.5 | 49.9 |
| Rank | 255 | 51 |
| Context | 131K | 1.05M |
| Input $/M | $0.018 | $1.25 |
| Output $/M | $0.09 | $4.25 |
| Weights | Open | Proprietary |

## Coding

- gpt-oss-20b: 37.6 (#192)
- Muse Spark 1.1: 51.3 (#40)

| Benchmark | gpt-oss-20b | Muse Spark 1.1 |
|---|---|---|
| SciCode | 34.4% | 58.8% |
| LMArena Coding | 1306 | 1498 |
| DeepSWE | — | 53.3% |
| LMArena WebDev | — | 1542 |
| WeirdML | 40.9% | — |
| ALE-Bench | 566.05 | — |

## Agentic & Tool Use

- gpt-oss-20b: 9.3 (#154)
- Muse Spark 1.1: 30.8 (#73)

| Benchmark | gpt-oss-20b | Muse Spark 1.1 |
|---|---|---|
| Terminal-Bench | 3.4% | — |
| APEX-Agents | — | 31.8% |
| τ²-bench Banking | — | 40.5% |
| GBAEval | — | 7.9% |
| GDP.pdf | — | 15% |
| Vending-Bench 2 | — | 6,520 |

## Reasoning

- gpt-oss-20b: 19.3 (#261)
- Muse Spark 1.1: 47.1 (#44)

| Benchmark | gpt-oss-20b | Muse Spark 1.1 |
|---|---|---|
| CritPt | 1.4% | 15.1% |
| LMArena Hard Prompts | 1274 | 1486 |
| DTBench | 68% | 94.4% |
| LMCA | 14.5% | 49.9% |
| Epoch Capabilities Index | 137.82 | 154.21 |
| Kagi LLM Benchmark | 53.2% | — |
| NYT Connections (extended) | — | 84.9% |
| Chess Puzzles | 4% | — |
| Surface Evolver Bench | — | 52.5% |

## Math

- gpt-oss-20b: 39.4 (#103)
- Muse Spark 1.1: 45.5 (#76)

| Benchmark | gpt-oss-20b | Muse Spark 1.1 |
|---|---|---|
| LMArena Math | 1317 | 1483 |
| OTIS Mock AIME 2024-2025 | 65.3% | — |
| ProofBench | — | 39% |
| Omni-MATH | 56.5% | — |

## Knowledge

- gpt-oss-20b: 34.6 (#195)
- Muse Spark 1.1: 53.1 (#59)

| Benchmark | gpt-oss-20b | Muse Spark 1.1 |
|---|---|---|
| LMArena Expert | 1258 | 1478 |
| GPQA Diamond | 60.8% | — |
| SimpleQA Verified | — | 57.8% |
| MMLU-Pro | 74% | — |
| GPQA (HELM) | 59.4% | — |

## Multimodal

- gpt-oss-20b: —
- Muse Spark 1.1: 42.6 (#29)

| Benchmark | gpt-oss-20b | Muse Spark 1.1 |
|---|---|---|
| LMArena Vision | — | 1293 |
| LMArena Document | — | 1465 |

## Multilingual

- gpt-oss-20b: 42.2 (#197)
- Muse Spark 1.1: 56.7 (#17)

| Benchmark | gpt-oss-20b | Muse Spark 1.1 |
|---|---|---|
| LMArena Non-English | 1268 | 1472 |
| LMArena Chinese | 1314 | 1518 |
| LMArena German | 1255 | 1466 |
| LMArena Japanese | 1244 | 1451 |
| LMArena Korean | 1236 | 1458 |
| LMArena Russian | 1278 | 1483 |
| LMArena Spanish | 1267 | 1464 |
| LMArena French | — | 1494 |

## Instruction Following

- gpt-oss-20b: 61.8 (#240)
- Muse Spark 1.1: 76.5 (#39)

| Benchmark | gpt-oss-20b | Muse Spark 1.1 |
|---|---|---|
| LMArena Instruction Following | 1236 | 1457 |
| IFEval | 73.2% | — |

## Long Context

- gpt-oss-20b: 37.9 (#209)
- Muse Spark 1.1: 44.8 (#58)

| Benchmark | gpt-oss-20b | Muse Spark 1.1 |
|---|---|---|
| LMArena Longer Query | 1250 | 1462 |

## Writing & Preference

- gpt-oss-20b: 35.5 (#265)
- Muse Spark 1.1: 73.4 (#11)

| Benchmark | gpt-oss-20b | Muse Spark 1.1 |
|---|---|---|
| LMArena Text | 1287 | 1479 |
| LMArena Creative Writing | 1201 | 1437 |
| EQ-Bench Creative Writing | 666 | 1927 |
| LMArena Multi-Turn | 1268 | 1485 |
| WildBench | 73.7% | — |
| EQ-Bench 4 | — | 1260 |

## FAQ

### Is gpt-oss-20b better than Muse Spark 1.1?

Muse Spark 1.1 is the stronger model overall, scoring 49.9 to 32.5 on the Noometry Index. gpt-oss-20b costs 56× less per token, which makes it the better buy when Muse Spark 1.1's lead doesn't matter for your workload.

### Which is cheaper, gpt-oss-20b or Muse Spark 1.1?

gpt-oss-20b is cheaper. It lists at $0.018 per million input tokens and $0.09 per million output tokens; Muse Spark 1.1 lists at $1.25 and $4.25.

### Is gpt-oss-20b or Muse Spark 1.1 better for coding?

Muse Spark 1.1 scores higher on coding benchmarks: 51.3 versus 37.6 in the Noometry coding category.

### Which has the bigger context window?

Muse Spark 1.1 does, with 1.05M tokens against 131K.

### How many benchmarks do gpt-oss-20b and Muse Spark 1.1 share?

22 benchmarks have published results for both models. gpt-oss-20b has 34 scored results on Noometry and Muse Spark 1.1 has 37.