Model comparison
GPT-4o mini vs Muse Spark 1.3
Muse Spark 1.3 is the stronger model overall, scoring 54.8 to 25.5 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 . 26 shared benchmarks.
MetaSummary
- They share 26 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 73.1 to 10.4.
- 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 | 25.5 | 54.8 |
| 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 | 37 |
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Category by category
Coding Muse Spark 1.3 leads
GPT-4o mini: 22.0 (#335), Muse Spark 1.3: 56.6 (#21)
| Benchmark | GPT-4o mini | Muse Spark 1.3 |
|---|---|---|
| LMArena Coding | 1290 | 1514 |
| Aider Polyglot | 3.6% | — |
| CursorBench | — | 41.6% |
| LMArena WebDev | — | 1657 |
| 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: 27.5 (#101), Muse Spark 1.3: 38.6 (#30)
| 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 (#347), Muse Spark 1.3: 54.0 (#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 | 156.75 |
| ARC-AGI-2 | 0% | — |
| SimpleBench | 10.7% | — |
| Kagi LLM Benchmark | 28.8% | — |
| NYT Connections (extended) | — | 85.1% |
| CritPt | — | 26% |
| 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: 10.4 (#314), Muse Spark 1.3: 73.1 (#21)
| 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 | 1494 |
| FrontierMath Tier 4 | — | 46.3% |
| ProofBench | — | 58% |
| 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 (#284), Muse Spark 1.3: 42.6 (#95)
| 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: 25.9 (#122), Muse Spark 1.3: 43.7 (#22)
| Benchmark | GPT-4o mini | Muse Spark 1.3 |
|---|---|---|
| LMArena Vision | 1066 | 1309 |
| Video-MME | 64.8% | — |
| GeoBench | 64% | — |
| VPCT | 34% | — |
| LMArena Document | — | 1471 |
Multilingual Muse Spark 1.3 leads
GPT-4o mini: 42.0 (#199), Muse Spark 1.3: 57.4 (#8)
| Benchmark | GPT-4o mini | Muse Spark 1.3 |
|---|---|---|
| LMArena Non-English | 1266 | 1481 |
| LMArena Chinese | 1265 | 1529 |
| LMArena French | 1297 | 1524 |
| LMArena German | 1272 | 1515 |
| LMArena Japanese | 1216 | 1474 |
| LMArena Korean | 1195 | 1501 |
| LMArena Russian | 1275 | 1490 |
| LMArena Spanish | 1276 | 1490 |
Instruction Following Muse Spark 1.3 leads
GPT-4o mini: 61.9 (#239), Muse Spark 1.3: 77.5 (#22)
| Benchmark | GPT-4o mini | Muse Spark 1.3 |
|---|---|---|
| LMArena Instruction Following | 1258 | 1477 |
| LiveBench Instruction Following | 56.8% | — |
| IFEval | 78.2% | — |
Long Context Muse Spark 1.3 leads
GPT-4o mini: 39.1 (#186), Muse Spark 1.3: 45.6 (#32)
| Benchmark | GPT-4o mini | Muse Spark 1.3 |
|---|---|---|
| LMArena Longer Query | 1289 | 1488 |
Writing & Preference Muse Spark 1.3 leads
GPT-4o mini: 39.5 (#248), Muse Spark 1.3: 73.6 (#9)
| Benchmark | GPT-4o mini | Muse Spark 1.3 |
|---|---|---|
| LMArena Text | 1286 | 1490 |
| LMArena Creative Writing | 1268 | 1455 |
| EQ-Bench Creative Writing | 873 | 1906 |
| LMArena Multi-Turn | 1285 | 1482 |
| 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 54.8 to 25.5 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: 56.6 versus 22.0 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?
26 benchmarks have published results for both models. GPT-4o mini has 60 scored results on Noometry and Muse Spark 1.3 has 37.