Model comparison
GPT-4o mini vs Muse Spark 1.2
Muse Spark 1.2 is the stronger model overall, scoring 50.3 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 1.2's lead doesn't matter for your workload.
Last verified . 22 shared benchmarks.
MetaSummary
- They share 22 benchmarks with published results for both. GPT-4o mini scores higher in 0 categories and Muse Spark 1.2 in 10 categories; 10 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where Muse Spark 1.2 leads 51.3 to 8.7.
- The biggest single-benchmark swing is SimpleBench: 10.7% for GPT-4o mini and 74.5% for Muse Spark 1.2.
- GPT-4o mini is cheaper at $0.15 / $0.60 per million input/output tokens, against $1.25 / $4.25 for Muse Spark 1.2.
- Muse Spark 1.2 accepts more context: 1.05M tokens versus 128K.
Side by side
| GPT-4o mini | Muse Spark 1.2 | |
|---|---|---|
| Provider | OpenAI | Meta |
| Noometry Index | 25.5 | 50.3 |
| Released | 2024-07-18 | 2026-08-05 |
| 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 | 31 |
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Category by category
Coding Muse Spark 1.2 leads
GPT-4o mini: 22.0 (#335), Muse Spark 1.2: 49.2 (#51)
| Benchmark | GPT-4o mini | Muse Spark 1.2 |
|---|---|---|
| WeirdML | 11.8% | 60.3% |
| LMArena Coding | 1290 | 1495 |
| DeepSWE | — | 54.9% |
| Aider Polyglot | 3.6% | — |
| LMArena WebDev | — | 1533 |
| FrontierSWE | — | 12% |
| SciCode | — | 56.4% |
| BigCodeBench Instruct | 46.1% | — |
| LiveBench Coding | 43.1% | — |
| BigCodeBench Complete | 57.4% | — |
| HumanEval+ | 83.5% | — |
| MBPP+ | 72.2% | — |
Agentic & Tool Use Muse Spark 1.2 leads
GPT-4o mini: 27.5 (#101), Muse Spark 1.2: 29.4 (#87)
| Benchmark | GPT-4o mini | Muse Spark 1.2 |
|---|---|---|
| APEX-Agents | — | 36.4% |
| BALROG | 17.4% | — |
| GDP.pdf | — | 16% |
Reasoning Muse Spark 1.2 leads
GPT-4o mini: 8.7 (#347), Muse Spark 1.2: 51.3 (#34)
| Benchmark | GPT-4o mini | Muse Spark 1.2 |
|---|---|---|
| SimpleBench | 10.7% | 74.5% |
| LMArena Hard Prompts | 1267 | 1486 |
| DTBench | 54.4% | 94.7% |
| LMCA | 10.4% | 48.4% |
| Epoch Capabilities Index | 126.56 | 154.87 |
| ARC-AGI-2 | 0% | — |
| Kagi LLM Benchmark | 28.8% | — |
| NYT Connections (extended) | — | 79.2% |
| CritPt | — | 17.7% |
| Chess Puzzles | 0% | — |
| LiveBench Reasoning | 32.8% | — |
| Mystery Game Puzzles | 12% | — |
| LiveBench Data Analysis | 50% | — |
| LiveBench | 41.3% | — |
| PIQA | 88.7% | — |
Math Muse Spark 1.2 leads
GPT-4o mini: 10.4 (#314), Muse Spark 1.2: 46.4 (#70)
| Benchmark | GPT-4o mini | Muse Spark 1.2 |
|---|---|---|
| LMArena Math | 1267 | 1471 |
| FrontierMath (Tiers 1-3) | 0.7% | — |
| OTIS Mock AIME 2024-2025 | 6.9% | — |
| ProofBench | — | 43% |
| Omni-MATH | 28% | — |
| LiveBench Math | 36.3% | — |
| MATH Level 5 | 52.6% | — |
| GSM8K | 91.3% | — |
Knowledge Muse Spark 1.2 leads
GPT-4o mini: 17.7 (#284), Muse Spark 1.2: 54.1 (#53)
| Benchmark | GPT-4o mini | Muse Spark 1.2 |
|---|---|---|
| SimpleQA Verified | 8.3% | 60.3% |
| LMArena Expert | 1235 | 1480 |
| GPQA Diamond | 37.7% | — |
| MMLU-Pro | 60.3% | — |
| Confabulations | 37.2% | — |
| GPQA (HELM) | 36.8% | — |
| BoolQ | 88.7% | — |
| MMLU | 81.8% | — |
Multimodal Muse Spark 1.2 leads
GPT-4o mini: 25.9 (#122), Muse Spark 1.2: 43.4 (#25)
| Benchmark | GPT-4o mini | Muse Spark 1.2 |
|---|---|---|
| LMArena Vision | 1066 | 1305 |
| Video-MME | 64.8% | — |
| GeoBench | 64% | — |
| VPCT | 34% | — |
Multilingual Muse Spark 1.2 leads
GPT-4o mini: 42.0 (#199), Muse Spark 1.2: 57.1 (#11)
| Benchmark | GPT-4o mini | Muse Spark 1.2 |
|---|---|---|
| LMArena Non-English | 1266 | 1478 |
| LMArena Chinese | 1265 | 1511 |
| LMArena French | 1297 | 1513 |
| LMArena Russian | 1275 | 1487 |
| LMArena Spanish | 1276 | 1498 |
| LMArena German | 1272 | — |
| LMArena Japanese | 1216 | — |
| LMArena Korean | 1195 | — |
Instruction Following Muse Spark 1.2 leads
GPT-4o mini: 61.9 (#239), Muse Spark 1.2: 76.7 (#36)
| Benchmark | GPT-4o mini | Muse Spark 1.2 |
|---|---|---|
| LMArena Instruction Following | 1258 | 1461 |
| LiveBench Instruction Following | 56.8% | — |
| IFEval | 78.2% | — |
Long Context Muse Spark 1.2 leads
GPT-4o mini: 39.1 (#186), Muse Spark 1.2: 45.2 (#48)
| Benchmark | GPT-4o mini | Muse Spark 1.2 |
|---|---|---|
| LMArena Longer Query | 1289 | 1475 |
Writing & Preference Muse Spark 1.2 leads
GPT-4o mini: 39.5 (#248), Muse Spark 1.2: 72.3 (#14)
| Benchmark | GPT-4o mini | Muse Spark 1.2 |
|---|---|---|
| LMArena Text | 1286 | 1482 |
| LMArena Creative Writing | 1268 | 1449 |
| EQ-Bench Creative Writing | 873 | 1840 |
| LMArena Multi-Turn | 1285 | 1494 |
| Short-Story Creative Writing | 67.2% | — |
| WildBench | 79.1% | — |
| LiveBench Language | 28.6% | — |
Frequently asked questions
Is GPT-4o mini better than Muse Spark 1.2?
Muse Spark 1.2 is the stronger model overall, scoring 50.3 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 1.2's lead doesn't matter for your workload.
Which is cheaper, GPT-4o mini or Muse Spark 1.2?
GPT-4o mini is cheaper. It lists at $0.15 per million input tokens and $0.60 per million output tokens; Muse Spark 1.2 lists at $1.25 and $4.25.
Is GPT-4o mini or Muse Spark 1.2 better for coding?
Muse Spark 1.2 scores higher on coding benchmarks: 49.2 versus 22.0 in the Noometry coding category.
Which has the bigger context window?
Muse Spark 1.2 does, with 1.05M tokens against 128K.
How many benchmarks do GPT-4o mini and Muse Spark 1.2 share?
22 benchmarks have published results for both models. GPT-4o mini has 60 scored results on Noometry and Muse Spark 1.2 has 31.