Model comparison
GPT-4o mini vs Muse Spark 1.3
Muse Spark 1.3 is the stronger model overall, scoring 54.4 to 25.4 on the Noometry Index. GPT-4o mini costs 7.6× less per token, which makes it the better buy when Muse Spark 1.3's lead doesn't matter for your workload.
Last verified . 24 shared benchmarks.
MetaSummary
- They share 24 benchmarks with published results for both. GPT-4o mini scores higher in 0 categories and Muse Spark 1.3 in 10 categories; 10 gaps are clear of the uncertainty.
- The widest gap is in math, where Muse Spark 1.3 leads 72.4 to 9.9.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 6.9% for GPT-4o mini and 99.2% for Muse Spark 1.3.
- GPT-4o mini is cheaper at $0.15 / $0.60 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 128K.
Side by side
| GPT-4o mini | Muse Spark 1.3 | |
|---|---|---|
| Provider | OpenAI | Meta |
| Noometry Index | 25.4 | 54.4 |
| Released | 2024-07-18 | 2026-09-02 |
| Weights | Proprietary | Proprietary |
| Context window | 128K | 1.05M |
| Max output | 16K | 131K |
| Input $ / M tokens | $0.15 | $1.25 |
| Output $ / M tokens | $0.60 | $4.25 |
| Results tracked | 60 | 34 |
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Category by category
Coding Muse Spark 1.3 leads
GPT-4o mini: 21.6 (#330), Muse Spark 1.3: 56.1 (#18)
| Benchmark | GPT-4o mini | Muse Spark 1.3 |
|---|---|---|
| LMArena Coding | 1290 | 1516 |
| Aider Polyglot | 3.6% | — |
| CursorBench | — | 41.6% |
| LMArena WebDev | — | 1655 |
| SciCode | — | 59.7% |
| WeirdML | 11.8% | — |
| BigCodeBench Instruct | 46.1% | — |
| LiveBench Coding | 43.1% | — |
| BigCodeBench Complete | 57.4% | — |
| HumanEval+ | 83.5% | — |
| MBPP+ | 72.2% | — |
Agentic & Tool Use Muse Spark 1.3 leads
GPT-4o mini: 27.2 (#95), Muse Spark 1.3: 38.6 (#28)
| Benchmark | GPT-4o mini | Muse Spark 1.3 |
|---|---|---|
| APEX-Agents | — | 57.8% |
| BALROG | 17.4% | — |
| GDP.pdf | — | 27.6% |
Reasoning Muse Spark 1.3 leads
GPT-4o mini: 8.7 (#343), Muse Spark 1.3: 52.9 (#27)
| Benchmark | GPT-4o mini | Muse Spark 1.3 |
|---|---|---|
| Chess Puzzles | 0% | 38% |
| LMArena Hard Prompts | 1267 | 1503 |
| Mystery Game Puzzles | 12% | 25% |
| DTBench | 54.4% | 96.5% |
| LMCA | 10.4% | 53.9% |
| Epoch Capabilities Index | 126.56 | 156.89 |
| ARC-AGI-2 | 0% | — |
| SimpleBench | 10.7% | — |
| Kagi LLM Benchmark | 28.8% | — |
| NYT Connections (extended) | — | 85.1% |
| CritPt | — | 24.9% |
| LiveBench Reasoning | 32.8% | — |
| LiveBench Data Analysis | 50% | — |
| Bench to the Future 3 | — | 0.14 |
| LiveBench | 41.3% | — |
| PIQA | 88.7% | — |
Math Muse Spark 1.3 leads
GPT-4o mini: 9.9 (#307), Muse Spark 1.3: 72.4 (#16)
| Benchmark | GPT-4o mini | Muse Spark 1.3 |
|---|---|---|
| FrontierMath (Tiers 1-3) | 0.7% | 74.4% |
| OTIS Mock AIME 2024-2025 | 6.9% | 99.2% |
| LMArena Math | 1267 | 1497 |
| FrontierMath Tier 4 | — | 46.3% |
| Omni-MATH | 28% | — |
| LiveBench Math | 36.3% | — |
| MATH Level 5 | 52.6% | — |
| GSM8K | 91.3% | — |
Knowledge Muse Spark 1.3 leads
GPT-4o mini: 17.7 (#279), Muse Spark 1.3: 42.0 (#92)
| Benchmark | GPT-4o mini | Muse Spark 1.3 |
|---|---|---|
| LMArena Expert | 1235 | 1516 |
| GPQA Diamond | 37.7% | — |
| SimpleQA Verified | 8.3% | — |
| MMLU-Pro | 60.3% | — |
| Confabulations | 37.2% | — |
| GPQA (HELM) | 36.8% | — |
| BoolQ | 88.7% | — |
| MMLU | 81.8% | — |
Multimodal Muse Spark 1.3 leads
GPT-4o mini: 25.3 (#117), Muse Spark 1.3: 43.0 (#21)
| Benchmark | GPT-4o mini | Muse Spark 1.3 |
|---|---|---|
| LMArena Vision | 1066 | 1310 |
| Video-MME | 64.8% | — |
| GeoBench | 64% | — |
| VPCT | 34% | — |
| LMArena Document | — | 1471 |
Multilingual Muse Spark 1.3 leads
GPT-4o mini: 42.2 (#194), Muse Spark 1.3: 57.8 (#6)
| Benchmark | GPT-4o mini | Muse Spark 1.3 |
|---|---|---|
| LMArena Non-English | 1266 | 1485 |
| LMArena Chinese | 1264 | 1527 |
| LMArena French | 1296 | 1534 |
| LMArena Korean | 1195 | 1513 |
| LMArena Russian | 1275 | 1491 |
| LMArena Spanish | 1276 | 1485 |
| LMArena German | 1272 | — |
| LMArena Japanese | 1216 | — |
Instruction Following Muse Spark 1.3 leads
GPT-4o mini: 62.1 (#234), Muse Spark 1.3: 77.8 (#14)
| Benchmark | GPT-4o mini | Muse Spark 1.3 |
|---|---|---|
| LMArena Instruction Following | 1259 | 1481 |
| LiveBench Instruction Following | 56.8% | — |
| IFEval | 78.2% | — |
Long Context Muse Spark 1.3 leads
GPT-4o mini: 39.1 (#181), Muse Spark 1.3: 45.7 (#29)
| Benchmark | GPT-4o mini | Muse Spark 1.3 |
|---|---|---|
| LMArena Longer Query | 1289 | 1491 |
Writing & Preference Muse Spark 1.3 leads
GPT-4o mini: 39.7 (#243), Muse Spark 1.3: 73.7 (#10)
| Benchmark | GPT-4o mini | Muse Spark 1.3 |
|---|---|---|
| LMArena Text | 1286 | 1490 |
| LMArena Creative Writing | 1268 | 1450 |
| EQ-Bench Creative Writing | 873 | 1906 |
| LMArena Multi-Turn | 1285 | 1486 |
| Short-Story Creative Writing | 67.2% | — |
| WildBench | 79.1% | — |
| LiveBench Language | 28.6% | — |
Frequently asked questions
Is GPT-4o mini better than Muse Spark 1.3?
Muse Spark 1.3 is the stronger model overall, scoring 54.4 to 25.4 on the Noometry Index. GPT-4o mini costs 7.6× 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, GPT-4o mini or Muse Spark 1.3?
GPT-4o mini is cheaper. It lists at $0.15 per million input tokens and $0.60 per million output tokens; Muse Spark 1.3 lists at $1.25 and $4.25.
Is GPT-4o mini or Muse Spark 1.3 better for coding?
Muse Spark 1.3 scores higher on coding benchmarks: 56.1 versus 21.6 in the Noometry coding category.
Which has the bigger context window?
Muse Spark 1.3 does, with 1.05M tokens against 128K.
How many benchmarks do GPT-4o mini and Muse Spark 1.3 share?
24 benchmarks have published results for both models. GPT-4o mini has 60 scored results on Noometry and Muse Spark 1.3 has 34.