# Muse Spark 1.3 vs Qwen2.5-Coder-32B

> Muse Spark 1.3 is the stronger model overall, scoring 54.4 to 32.9 on the Noometry Index. Qwen2.5-Coder-32B costs 2.7× less per token, which makes it the better buy when Muse Spark 1.3's lead doesn't matter for your workload.

- Canonical page: https://noometry.com/compare/muse-spark-1-3-vs-qwen2-5-coder-32b
- Last updated: 2026-10-10
- Shared benchmarks: 13

## Summary

- They share 13 benchmarks with published results for both. Muse Spark 1.3 scores higher in 8 categories and Qwen2.5-Coder-32B in 0 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in math, where Muse Spark 1.3 leads 72.4 to 30.8.
- Qwen2.5-Coder-32B is cheaper at $0.66 / $1 per million input/output tokens, against $1.25 / $4.25 for Muse Spark 1.3.
- Muse Spark 1.3 accepts more context: 1.05M tokens versus 33K.
- Qwen2.5-Coder-32B has downloadable open weights; the other is API-only.

## Snapshot

| | Muse Spark 1.3 | Qwen2.5-Coder-32B |
|---|---|---|
| Provider | Meta | Alibaba (Qwen) |
| Noometry Index | 54.4 | 32.9 |
| Rank | 27 | 239 |
| Context | 1.05M | 33K |
| Input $/M | $1.25 | $0.66 |
| Output $/M | $4.25 | $1 |
| Weights | Proprietary | Open |

## Coding

- Muse Spark 1.3: 56.1 (#18)
- Qwen2.5-Coder-32B: 22.4 (#328)

| Benchmark | Muse Spark 1.3 | Qwen2.5-Coder-32B |
|---|---|---|
| LMArena Coding | 1516 | 1276 |
| SWE-bench Verified (bash only) | — | 9% |
| Aider Polyglot | — | 16.4% |
| CursorBench | 41.6% | — |
| LMArena WebDev | 1655 | — |
| SciCode | 59.7% | — |
| BigCodeBench Instruct | — | 49% |
| LiveBench Coding | — | 56.9% |
| BigCodeBench Complete | — | 58% |
| HumanEval+ | — | 87.2% |
| MBPP+ | — | 77% |

## Agentic & Tool Use

- Muse Spark 1.3: 38.6 (#28)
- Qwen2.5-Coder-32B: —

| Benchmark | Muse Spark 1.3 | Qwen2.5-Coder-32B |
|---|---|---|
| APEX-Agents | 57.8% | — |
| GDP.pdf | 27.6% | — |

## Reasoning

- Muse Spark 1.3: 52.9 (#27)
- Qwen2.5-Coder-32B: 20.4 (#220)

| Benchmark | Muse Spark 1.3 | Qwen2.5-Coder-32B |
|---|---|---|
| LMArena Hard Prompts | 1503 | 1251 |
| Epoch Capabilities Index | 156.89 | 119.41 |
| NYT Connections (extended) | 85.1% | — |
| CritPt | 24.9% | — |
| Chess Puzzles | 38% | — |
| LiveBench Reasoning | — | 42.1% |
| Mystery Game Puzzles | 25% | — |
| DTBench | 96.5% | — |
| LiveBench Data Analysis | — | 49.9% |
| LMCA | 53.9% | — |
| Bench to the Future 3 | 0.14 | — |
| HellaSwag | — | 83% |
| LiveBench | — | 46.2% |
| WinoGrande | — | 80.8% |

## Math

- Muse Spark 1.3: 72.4 (#16)
- Qwen2.5-Coder-32B: 30.8 (#203)

| Benchmark | Muse Spark 1.3 | Qwen2.5-Coder-32B |
|---|---|---|
| LMArena Math | 1497 | 1251 |
| FrontierMath (Tiers 1-3) | 74.4% | — |
| FrontierMath Tier 4 | 46.3% | — |
| OTIS Mock AIME 2024-2025 | 99.2% | — |
| LiveBench Math | — | 46.6% |
| GSM8K | — | 93% |

## Knowledge

- Muse Spark 1.3: 42.0 (#92)
- Qwen2.5-Coder-32B: 32.9 (#200)

| Benchmark | Muse Spark 1.3 | Qwen2.5-Coder-32B |
|---|---|---|
| LMArena Expert | 1516 | 1221 |
| ARC (AI2) Challenge | — | 70.5% |
| MMLU | — | 79.1% |

## Multimodal

- Muse Spark 1.3: 43.0 (#21)
- Qwen2.5-Coder-32B: —

| Benchmark | Muse Spark 1.3 | Qwen2.5-Coder-32B |
|---|---|---|
| LMArena Vision | 1310 | — |
| LMArena Document | 1471 | — |

## Multilingual

- Muse Spark 1.3: 57.8 (#6)
- Qwen2.5-Coder-32B: 38.0 (#230)

| Benchmark | Muse Spark 1.3 | Qwen2.5-Coder-32B |
|---|---|---|
| LMArena Non-English | 1485 | 1205 |
| LMArena Chinese | 1527 | 1222 |
| LMArena Russian | 1491 | 1228 |
| LMArena French | 1534 | — |
| LMArena Korean | 1513 | — |
| LMArena Spanish | 1485 | — |

## Instruction Following

- Muse Spark 1.3: 77.8 (#14)
- Qwen2.5-Coder-32B: 61.6 (#240)

| Benchmark | Muse Spark 1.3 | Qwen2.5-Coder-32B |
|---|---|---|
| LMArena Instruction Following | 1481 | 1223 |
| LiveBench Instruction Following | — | 58.7% |

## Long Context

- Muse Spark 1.3: 45.7 (#29)
- Qwen2.5-Coder-32B: 37.9 (#204)

| Benchmark | Muse Spark 1.3 | Qwen2.5-Coder-32B |
|---|---|---|
| LMArena Longer Query | 1491 | 1251 |

## Writing & Preference

- Muse Spark 1.3: 73.7 (#10)
- Qwen2.5-Coder-32B: 41.8 (#235)

| Benchmark | Muse Spark 1.3 | Qwen2.5-Coder-32B |
|---|---|---|
| LMArena Text | 1490 | 1230 |
| LMArena Creative Writing | 1450 | 1174 |
| LMArena Multi-Turn | 1486 | 1222 |
| EQ-Bench Creative Writing | 1906 | — |
| LiveBench Language | — | 23.3% |

## FAQ

### Is Muse Spark 1.3 better than Qwen2.5-Coder-32B?

Muse Spark 1.3 is the stronger model overall, scoring 54.4 to 32.9 on the Noometry Index. Qwen2.5-Coder-32B costs 2.7× less per token, which makes it the better buy when Muse Spark 1.3's lead doesn't matter for your workload.

### Which is cheaper, Muse Spark 1.3 or Qwen2.5-Coder-32B?

Qwen2.5-Coder-32B is cheaper. It lists at $0.66 per million input tokens and $1 per million output tokens; Muse Spark 1.3 lists at $1.25 and $4.25.

### Is Muse Spark 1.3 or Qwen2.5-Coder-32B better for coding?

Muse Spark 1.3 scores higher on coding benchmarks: 56.1 versus 22.4 in the Noometry coding category.

### Which has the bigger context window?

Muse Spark 1.3 does, with 1.05M tokens against 33K.

### How many benchmarks do Muse Spark 1.3 and Qwen2.5-Coder-32B share?

13 benchmarks have published results for both models. Muse Spark 1.3 has 34 scored results on Noometry and Qwen2.5-Coder-32B has 31.