Model comparison
Muse Spark 1.2 vs o4-mini
Muse Spark 1.2 is the stronger model overall, scoring 50.3 to 41.6 on the Noometry Index.
Last verified . 22 shared benchmarks.
MetaSummary
- They share 22 benchmarks with published results for both. Muse Spark 1.2 scores higher in 8 categories and o4-mini in 2 categories; 9 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where Muse Spark 1.2 leads 51.3 to 24.6.
- The biggest single-benchmark swing is SimpleQA Verified: 60.3% for Muse Spark 1.2 and 19.6% for o4-mini.
- Both cost about the same: $1.25 input and $4.25 output per million tokens.
- Muse Spark 1.2 accepts more context: 1.05M tokens versus 200K.
Side by side
| Muse Spark 1.2 | o4-mini | |
|---|---|---|
| Provider | Meta | OpenAI |
| Noometry Index | 50.3 | 41.6 |
| Released | 2026-08-05 | 2025-04-16 |
| Weights | Proprietary | Proprietary |
| Context window | 1.05M | 200K |
| Max output | 131K | 100K |
| Input $ / M tokens | $1.25 | $1.10 |
| Output $ / M tokens | $4.25 | $4.40 |
| Results tracked | 31 | 60 |
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Category by category
Coding Muse Spark 1.2 leads
Muse Spark 1.2: 49.2 (#51), o4-mini: 40.9 (#127)
| Benchmark | Muse Spark 1.2 | o4-mini |
|---|---|---|
| WeirdML | 60.3% | 52.6% |
| LMArena Coding | 1495 | 1368 |
| DeepSWE | 54.9% | — |
| SWE-bench Verified (bash only) | — | 45% |
| Aider Polyglot | — | 72% |
| LMArena WebDev | 1533 | — |
| FrontierSWE | 12% | — |
| SciCode | 56.4% | — |
| GSO | — | 3.6% |
| CadEval | — | 62% |
| ALE-Bench | — | 826.17 |
| AlgoTune | — | 1.72 |
Agentic & Tool Use o4-mini leads
Muse Spark 1.2: 29.4 (#87), o4-mini: 32.6 (#61)
| Benchmark | Muse Spark 1.2 | o4-mini |
|---|---|---|
| APEX-Agents | 36.4% | — |
| Berkeley Function Calling Leaderboard | — | 53.2% |
| GDPval | — | 25.3% |
| GDP.pdf | 16% | — |
| METR Time Horizons | — | 63.9% |
Reasoning Muse Spark 1.2 leads
Muse Spark 1.2: 51.3 (#34), o4-mini: 24.6 (#162)
| Benchmark | Muse Spark 1.2 | o4-mini |
|---|---|---|
| SimpleBench | 74.5% | 38.7% |
| CritPt | 17.7% | 0.6% |
| LMArena Hard Prompts | 1486 | 1351 |
| DTBench | 94.7% | 77.6% |
| LMCA | 48.4% | 26.5% |
| Epoch Capabilities Index | 154.87 | 145.64 |
| ARC-AGI-2 | — | 6.1% |
| Kagi LLM Benchmark | — | 67.6% |
| NYT Connections (extended) | 79.2% | — |
| ARC-AGI-1 | — | 58.7% |
| Chess Puzzles | — | 26% |
| EnigmaEval | — | 9.2% |
| Mystery Game Puzzles | — | 5% |
| ForecastBench | — | 61.8 |
Math Muse Spark 1.2 leads
Muse Spark 1.2: 46.4 (#70), o4-mini: 40.8 (#89)
| Benchmark | Muse Spark 1.2 | o4-mini |
|---|---|---|
| LMArena Math | 1471 | 1389 |
| FrontierMath (Tiers 1-3) | — | 36.1% |
| FrontierMath Tier 4 | — | 4.9% |
| OTIS Mock AIME 2024-2025 | — | 81.7% |
| ProofBench | 43% | — |
| Omni-MATH | — | 72% |
| MATH Level 5 | — | 97.8% |
| FrontierMath (Feb 2025 set) | — | 24.8% |
| FrontierMath Tier 4 (v1) | — | 6.3% |
Knowledge Muse Spark 1.2 leads
Muse Spark 1.2: 54.1 (#53), o4-mini: 43.6 (#91)
| Benchmark | Muse Spark 1.2 | o4-mini |
|---|---|---|
| SimpleQA Verified | 60.3% | 19.6% |
| LMArena Expert | 1480 | 1343 |
| GPQA Diamond | — | 79.6% |
| Humanity's Last Exam | — | 18.1% |
| MMLU-Pro | — | 82% |
| Confabulations | — | 15.8% |
| Vectara Hallucination Rate | — | 18.6% |
| GPQA (HELM) | — | 73.5% |
Multimodal Muse Spark 1.2 leads
Muse Spark 1.2: 43.4 (#25), o4-mini: 40.2 (#49)
| Benchmark | Muse Spark 1.2 | o4-mini |
|---|---|---|
| LMArena Vision | 1305 | 1194 |
| GeoBench | — | 64% |
| VPCT | — | 57.5% |
Multilingual Muse Spark 1.2 leads
Muse Spark 1.2: 57.1 (#11), o4-mini: 47.0 (#154)
| Benchmark | Muse Spark 1.2 | o4-mini |
|---|---|---|
| LMArena Non-English | 1478 | 1337 |
| LMArena Chinese | 1511 | 1354 |
| LMArena French | 1513 | 1364 |
| LMArena Russian | 1487 | 1334 |
| LMArena Spanish | 1498 | 1347 |
| LMArena German | — | 1336 |
| LMArena Japanese | — | 1308 |
| LMArena Korean | — | 1312 |
Instruction Following Muse Spark 1.2 leads
Muse Spark 1.2: 76.7 (#36), o4-mini: 75.2 (#68)
| Benchmark | Muse Spark 1.2 | o4-mini |
|---|---|---|
| LMArena Instruction Following | 1461 | 1321 |
| IFEval | — | 92.8% |
Long Context Too close to call
Muse Spark 1.2: 45.2 (#48), o4-mini: 45.5 (#33)
| Benchmark | Muse Spark 1.2 | o4-mini |
|---|---|---|
| LMArena Longer Query | 1475 | 1315 |
| Fiction.LiveBench | — | 77.8% |
Writing & Preference Muse Spark 1.2 leads
Muse Spark 1.2: 72.3 (#14), o4-mini: 54.0 (#152)
| Benchmark | Muse Spark 1.2 | o4-mini |
|---|---|---|
| LMArena Text | 1482 | 1353 |
| LMArena Creative Writing | 1449 | 1294 |
| LMArena Multi-Turn | 1494 | 1350 |
| Short-Story Creative Writing | — | 75% |
| EQ-Bench Creative Writing | 1840 | — |
| WildBench | — | 85.4% |
Frequently asked questions
Is Muse Spark 1.2 better than o4-mini?
Muse Spark 1.2 is the stronger model overall, scoring 50.3 to 41.6 on the Noometry Index.
Which is cheaper, Muse Spark 1.2 or o4-mini?
o4-mini is cheaper. It lists at $1.10 per million input tokens and $4.40 per million output tokens; Muse Spark 1.2 lists at $1.25 and $4.25.
Is Muse Spark 1.2 or o4-mini better for coding?
Muse Spark 1.2 scores higher on coding benchmarks: 49.2 versus 40.9 in the Noometry coding category.
Which has the bigger context window?
Muse Spark 1.2 does, with 1.05M tokens against 200K.
How many benchmarks do Muse Spark 1.2 and o4-mini share?
22 benchmarks have published results for both models. Muse Spark 1.2 has 31 scored results on Noometry and o4-mini has 60.