Model comparison
Muse Spark 1.3 vs Qwen2.5-Coder-32B
Muse Spark 1.3 is the stronger model overall, scoring 54.8 to 33.4 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.
Last verified . 13 shared benchmarks.
Meta
Alibaba (Qwen)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 73.1 to 33.3.
- 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.
Side by side
| Muse Spark 1.3 | Qwen2.5-Coder-32B | |
|---|---|---|
| Provider | Meta | Alibaba (Qwen) |
| Noometry Index | 54.8 | 33.4 |
| Released | 2026-09-02 | 2024-09-18 |
| Weights | Proprietary | Open |
| Context window | 1.05M | 33K |
| Max output | 131K | 29K |
| Input $ / M tokens | $1.25 | $0.66 |
| Output $ / M tokens | $4.25 | $1 |
| Results tracked | 37 | 31 |
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Category by category
Coding Muse Spark 1.3 leads
Muse Spark 1.3: 56.6 (#21), Qwen2.5-Coder-32B: 22.6 (#333)
| Benchmark | Muse Spark 1.3 | Qwen2.5-Coder-32B |
|---|---|---|
| LMArena Coding | 1514 | 1276 |
| SWE-bench Verified (bash only) | — | 9% |
| Aider Polyglot | — | 16.4% |
| CursorBench | 41.6% | — |
| LMArena WebDev | 1657 | — |
| SciCode | 59.7% | — |
| BigCodeBench Instruct | — | 49% |
| LiveBench Coding | — | 56.9% |
| BigCodeBench Complete | — | 58% |
| HumanEval+ | — | 87.2% |
| MBPP+ | — | 77% |
Agentic & Tool Use Not comparable
Muse Spark 1.3: 38.6 (#30), 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 leads
Muse Spark 1.3: 54.0 (#27), Qwen2.5-Coder-32B: 21.2 (#225)
| Benchmark | Muse Spark 1.3 | Qwen2.5-Coder-32B |
|---|---|---|
| LMArena Hard Prompts | 1503 | 1251 |
| Epoch Capabilities Index | 156.75 | 119.49 |
| NYT Connections (extended) | 85.1% | — |
| CritPt | 26% | — |
| 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 leads
Muse Spark 1.3: 73.1 (#21), Qwen2.5-Coder-32B: 33.3 (#204)
| Benchmark | Muse Spark 1.3 | Qwen2.5-Coder-32B |
|---|---|---|
| LMArena Math | 1494 | 1251 |
| FrontierMath (Tiers 1-3) | 74.4% | — |
| FrontierMath Tier 4 | 46.3% | — |
| OTIS Mock AIME 2024-2025 | 99.2% | — |
| ProofBench | 58% | — |
| LiveBench Math | — | 46.6% |
| GSM8K | — | 93% |
Knowledge Muse Spark 1.3 leads
Muse Spark 1.3: 42.6 (#95), Qwen2.5-Coder-32B: 33.4 (#203)
| Benchmark | Muse Spark 1.3 | Qwen2.5-Coder-32B |
|---|---|---|
| LMArena Expert | 1516 | 1221 |
| ARC (AI2) Challenge | — | 70.5% |
| MMLU | — | 79.1% |
Multimodal Not comparable
Muse Spark 1.3: 43.7 (#22), Qwen2.5-Coder-32B: —
| Benchmark | Muse Spark 1.3 | Qwen2.5-Coder-32B |
|---|---|---|
| LMArena Vision | 1309 | — |
| LMArena Document | 1471 | — |
Multilingual Muse Spark 1.3 leads
Muse Spark 1.3: 57.4 (#8), Qwen2.5-Coder-32B: 37.8 (#235)
| Benchmark | Muse Spark 1.3 | Qwen2.5-Coder-32B |
|---|---|---|
| LMArena Non-English | 1481 | 1205 |
| LMArena Chinese | 1529 | 1222 |
| LMArena Russian | 1490 | 1228 |
| LMArena French | 1524 | — |
| LMArena German | 1515 | — |
| LMArena Japanese | 1474 | — |
| LMArena Korean | 1501 | — |
| LMArena Spanish | 1490 | — |
Instruction Following Muse Spark 1.3 leads
Muse Spark 1.3: 77.5 (#22), Qwen2.5-Coder-32B: 61.4 (#245)
| Benchmark | Muse Spark 1.3 | Qwen2.5-Coder-32B |
|---|---|---|
| LMArena Instruction Following | 1477 | 1223 |
| LiveBench Instruction Following | — | 58.7% |
Long Context Muse Spark 1.3 leads
Muse Spark 1.3: 45.6 (#32), Qwen2.5-Coder-32B: 38.0 (#208)
| Benchmark | Muse Spark 1.3 | Qwen2.5-Coder-32B |
|---|---|---|
| LMArena Longer Query | 1488 | 1251 |
Writing & Preference Muse Spark 1.3 leads
Muse Spark 1.3: 73.6 (#9), Qwen2.5-Coder-32B: 41.6 (#240)
| Benchmark | Muse Spark 1.3 | Qwen2.5-Coder-32B |
|---|---|---|
| LMArena Text | 1490 | 1230 |
| LMArena Creative Writing | 1455 | 1174 |
| LMArena Multi-Turn | 1482 | 1222 |
| EQ-Bench Creative Writing | 1906 | — |
| LiveBench Language | — | 23.3% |
Frequently asked questions
Is Muse Spark 1.3 better than Qwen2.5-Coder-32B?
Muse Spark 1.3 is the stronger model overall, scoring 54.8 to 33.4 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: 56.6 versus 22.6 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 37 scored results on Noometry and Qwen2.5-Coder-32B has 31.