# Muse Spark 1.3 vs Qwen2.5 72B Instruct

> Muse Spark 1.3 is the stronger model overall, scoring 54.8 to 31.9 on the Noometry Index.

- Canonical page: https://noometry.com/compare/muse-spark-1-3-vs-qwen2-5-72b-instruct
- Last updated: 2026-10-10
- Shared benchmarks: 21

## Summary

- They share 21 benchmarks with published results for both. Muse Spark 1.3 scores higher in 9 categories and Qwen2.5 72B Instruct in 0 categories; 9 gaps are clear of the uncertainty.
- The widest gap is in math, where Muse Spark 1.3 leads 73.1 to 19.3.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 99.2% for Muse Spark 1.3 and 8.1% for Qwen2.5 72B Instruct.
- Muse Spark 1.3 is cheaper at $1.25 / $4.25 per million input/output tokens, against $1.40 / $5.60 for Qwen2.5 72B Instruct.
- Muse Spark 1.3 accepts more context: 1.05M tokens versus 131K.
- Qwen2.5 72B Instruct has downloadable open weights; the other is API-only.

## Snapshot

| | Muse Spark 1.3 | Qwen2.5 72B Instruct |
|---|---|---|
| Provider | Meta | Alibaba (Qwen) |
| Noometry Index | 54.8 | 31.9 |
| Rank | 27 | 267 |
| Context | 1.05M | 131K |
| Input $/M | $1.25 | $1.40 |
| Output $/M | $4.25 | $5.60 |
| Weights | Proprietary | Open |

## Coding

- Muse Spark 1.3: 56.6 (#21)
- Qwen2.5 72B Instruct: 33.2 (#260)

| Benchmark | Muse Spark 1.3 | Qwen2.5 72B Instruct |
|---|---|---|
| LMArena Coding | 1514 | 1292 |
| CursorBench | 41.6% | — |
| LMArena WebDev | 1657 | — |
| SciCode | 59.7% | — |
| WeirdML | — | 16% |
| BigCodeBench Instruct | — | 45.8% |
| BigCodeBench Complete | — | 55.9% |

## Agentic & Tool Use

- Muse Spark 1.3: 38.6 (#30)
- Qwen2.5 72B Instruct: 22.1 (#133)

| Benchmark | Muse Spark 1.3 | Qwen2.5 72B Instruct |
|---|---|---|
| APEX-Agents | 57.8% | — |
| TheAgentCompany | — | 5.7% |
| BALROG | — | 16.2% |
| GDP.pdf | 27.6% | — |
| METR Time Horizons | — | 35.8% |

## Reasoning

- Muse Spark 1.3: 54.0 (#27)
- Qwen2.5 72B Instruct: 22.3 (#199)

| Benchmark | Muse Spark 1.3 | Qwen2.5 72B Instruct |
|---|---|---|
| LMArena Hard Prompts | 1503 | 1271 |
| DTBench | 96.5% | 62.9% |
| LMCA | 53.9% | 13.4% |
| Epoch Capabilities Index | 156.75 | 129 |
| NYT Connections (extended) | 85.1% | — |
| CritPt | 26% | — |
| Chess Puzzles | 38% | — |
| Mystery Game Puzzles | 25% | — |
| Bench to the Future 3 | 0.14 | — |
| BIG-Bench Hard | — | 79.8% |
| ForecastBench | — | 57.5 |
| HellaSwag | — | 84.8% |
| PIQA | — | 82.6% |
| WinoGrande | — | 82.3% |

## Math

- Muse Spark 1.3: 73.1 (#21)
- Qwen2.5 72B Instruct: 19.3 (#287)

| Benchmark | Muse Spark 1.3 | Qwen2.5 72B Instruct |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 99.2% | 8.1% |
| LMArena Math | 1494 | 1283 |
| FrontierMath (Tiers 1-3) | 74.4% | — |
| FrontierMath Tier 4 | 46.3% | — |
| ProofBench | 58% | — |
| Omni-MATH | — | 33% |
| MATH Level 5 | — | 63.2% |

## Knowledge

- Muse Spark 1.3: 42.6 (#95)
- Qwen2.5 72B Instruct: 27.0 (#253)

| Benchmark | Muse Spark 1.3 | Qwen2.5 72B Instruct |
|---|---|---|
| LMArena Expert | 1516 | 1245 |
| GPQA Diamond | — | 49.1% |
| MMLU-Pro | — | 63.1% |
| Confabulations | — | 19.1% |
| GPQA (HELM) | — | 42.6% |
| ARC (AI2) Challenge | — | 94.5% |
| MMLU | — | 85.3% |
| TriviaQA | — | 71.9% |

## Multimodal

- Muse Spark 1.3: 43.7 (#22)
- Qwen2.5 72B Instruct: —

| Benchmark | Muse Spark 1.3 | Qwen2.5 72B Instruct |
|---|---|---|
| LMArena Vision | 1309 | — |
| LMArena Document | 1471 | — |

## Multilingual

- Muse Spark 1.3: 57.4 (#8)
- Qwen2.5 72B Instruct: 41.0 (#213)

| Benchmark | Muse Spark 1.3 | Qwen2.5 72B Instruct |
|---|---|---|
| LMArena Non-English | 1481 | 1252 |
| LMArena Chinese | 1529 | 1272 |
| LMArena French | 1524 | 1280 |
| LMArena German | 1515 | 1234 |
| LMArena Japanese | 1474 | 1180 |
| LMArena Korean | 1501 | 1188 |
| LMArena Russian | 1490 | 1264 |
| LMArena Spanish | 1490 | 1256 |

## Instruction Following

- Muse Spark 1.3: 77.5 (#22)
- Qwen2.5 72B Instruct: 65.5 (#221)

| Benchmark | Muse Spark 1.3 | Qwen2.5 72B Instruct |
|---|---|---|
| LMArena Instruction Following | 1477 | 1254 |
| IFEval | — | 80.6% |

## Long Context

- Muse Spark 1.3: 45.6 (#32)
- Qwen2.5 72B Instruct: 38.9 (#188)

| Benchmark | Muse Spark 1.3 | Qwen2.5 72B Instruct |
|---|---|---|
| LMArena Longer Query | 1488 | 1282 |

## Writing & Preference

- Muse Spark 1.3: 73.6 (#9)
- Qwen2.5 72B Instruct: 46.7 (#215)

| Benchmark | Muse Spark 1.3 | Qwen2.5 72B Instruct |
|---|---|---|
| LMArena Text | 1490 | 1269 |
| LMArena Creative Writing | 1455 | 1221 |
| LMArena Multi-Turn | 1482 | 1272 |
| EQ-Bench Creative Writing | 1906 | — |
| WildBench | — | 80.2% |

## FAQ

### Is Muse Spark 1.3 better than Qwen2.5 72B Instruct?

Muse Spark 1.3 is the stronger model overall, scoring 54.8 to 31.9 on the Noometry Index.

### Which is cheaper, Muse Spark 1.3 or Qwen2.5 72B Instruct?

Muse Spark 1.3 is cheaper. It lists at $1.25 per million input tokens and $4.25 per million output tokens; Qwen2.5 72B Instruct lists at $1.40 and $5.60.

### Is Muse Spark 1.3 or Qwen2.5 72B Instruct better for coding?

Muse Spark 1.3 scores higher on coding benchmarks: 56.6 versus 33.2 in the Noometry coding category.

### Which has the bigger context window?

Muse Spark 1.3 does, with 1.05M tokens against 131K.

### How many benchmarks do Muse Spark 1.3 and Qwen2.5 72B Instruct share?

21 benchmarks have published results for both models. Muse Spark 1.3 has 37 scored results on Noometry and Qwen2.5 72B Instruct has 43.