Model comparison
GPT-4.1 mini vs Muse Spark 1.1
Muse Spark 1.1 is the stronger model overall, scoring 49.9 to 33.5 on the Noometry Index. GPT-4.1 mini costs 2.9× less per token, which makes it the better buy when Muse Spark 1.1's lead doesn't matter for your workload.
Last verified . 25 shared benchmarks.
MetaSummary
- They share 25 benchmarks with published results for both. GPT-4.1 mini scores higher in 0 categories and Muse Spark 1.1 in 10 categories; 9 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where Muse Spark 1.1 leads 45.9 to 10.9.
- The biggest single-benchmark swing is SimpleQA Verified: 12.7% for GPT-4.1 mini and 57.8% for Muse Spark 1.1.
- GPT-4.1 mini is cheaper at $0.40 / $1.60 per million input/output tokens, against $1.25 / $4.25 for Muse Spark 1.1.
- Muse Spark 1.1 accepts more context: 1.05M tokens versus 1.05M.
Side by side
| GPT-4.1 mini | Muse Spark 1.1 | |
|---|---|---|
| Provider | OpenAI | Meta |
| Noometry Index | 33.5 | 49.9 |
| Released | 2025-04-14 | 2026-04-08 |
| Weights | Proprietary | Proprietary |
| Context window | 1.05M | 1.05M |
| Max output | 33K | 131K |
| Input $ / M tokens | $0.40 | $1.25 |
| Output $ / M tokens | $1.60 | $4.25 |
| Results tracked | 47 | 36 |
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Category by category
Coding Muse Spark 1.1 leads
GPT-4.1 mini: 30.4 (#286), Muse Spark 1.1: 50.8 (#38)
| Benchmark | GPT-4.1 mini | Muse Spark 1.1 |
|---|---|---|
| SciCode | 40.4% | 58.8% |
| LMArena Coding | 1367 | 1497 |
| DeepSWE | — | 53.3% |
| SWE-bench Verified (bash only) | 23.9% | — |
| Aider Polyglot | 32.4% | — |
| LMArena WebDev | — | 1542 |
| WeirdML | 37.6% | — |
| BigCodeBench Instruct | 48.9% | — |
| CadEval | 16% | — |
Agentic & Tool Use Too close to call
GPT-4.1 mini: 33.0 (#52), Muse Spark 1.1: 33.9 (#45)
| Benchmark | GPT-4.1 mini | Muse Spark 1.1 |
|---|---|---|
| Berkeley Function Calling Leaderboard | 50.5% | — |
| τ²-bench Banking | — | 40.5% |
| GBAEval | — | 7.9% |
| GDP.pdf | — | 15% |
| Vending-Bench 2 | — | 6,520 |
Reasoning Muse Spark 1.1 leads
GPT-4.1 mini: 10.9 (#335), Muse Spark 1.1: 45.9 (#41)
| Benchmark | GPT-4.1 mini | Muse Spark 1.1 |
|---|---|---|
| CritPt | 0% | 15.1% |
| LMArena Hard Prompts | 1349 | 1486 |
| DTBench | 68.8% | 94.4% |
| LMCA | 21.1% | 49.9% |
| Epoch Capabilities Index | 135.01 | 154.32 |
| ARC-AGI-2 | 0% | — |
| Kagi LLM Benchmark | 48.6% | — |
| NYT Connections (extended) | — | 84.9% |
| ARC-AGI-1 | 3.5% | — |
| Chess Puzzles | 7% | — |
| Mystery Game Puzzles | 7% | — |
| Surface Evolver Bench | — | 52.5% |
Math Muse Spark 1.1 leads
GPT-4.1 mini: 23.1 (#264), Muse Spark 1.1: 44.0 (#67)
| Benchmark | GPT-4.1 mini | Muse Spark 1.1 |
|---|---|---|
| LMArena Math | 1343 | 1477 |
| FrontierMath (Tiers 1-3) | 6.7% | — |
| OTIS Mock AIME 2024-2025 | 44.7% | — |
| ProofBench | — | 39% |
| Omni-MATH | 49.1% | — |
| MATH Level 5 | 87.3% | — |
| FrontierMath (Feb 2025 set) | 4.5% | — |
Knowledge Muse Spark 1.1 leads
GPT-4.1 mini: 34.7 (#183), Muse Spark 1.1: 52.8 (#55)
| Benchmark | GPT-4.1 mini | Muse Spark 1.1 |
|---|---|---|
| SimpleQA Verified | 12.7% | 57.8% |
| LMArena Expert | 1338 | 1480 |
| GPQA Diamond | 65.8% | — |
| MMLU-Pro | 78.3% | — |
| GPQA (HELM) | 61.4% | — |
Multimodal Muse Spark 1.1 leads
GPT-4.1 mini: 35.2 (#77), Muse Spark 1.1: 41.9 (#28)
| Benchmark | GPT-4.1 mini | Muse Spark 1.1 |
|---|---|---|
| LMArena Vision | 1181 | 1292 |
| LMArena Document | — | 1465 |
Multilingual Muse Spark 1.1 leads
GPT-4.1 mini: 45.9 (#161), Muse Spark 1.1: 56.8 (#16)
| Benchmark | GPT-4.1 mini | Muse Spark 1.1 |
|---|---|---|
| LMArena Non-English | 1318 | 1471 |
| LMArena Chinese | 1329 | 1518 |
| LMArena French | 1357 | 1494 |
| LMArena German | 1349 | 1466 |
| LMArena Japanese | 1291 | 1445 |
| LMArena Korean | 1298 | 1459 |
| LMArena Russian | 1324 | 1482 |
| LMArena Spanish | 1319 | 1471 |
Instruction Following Muse Spark 1.1 leads
GPT-4.1 mini: 73.9 (#113), Muse Spark 1.1: 76.8 (#36)
| Benchmark | GPT-4.1 mini | Muse Spark 1.1 |
|---|---|---|
| LMArena Instruction Following | 1332 | 1457 |
| IFEval | 90.4% | — |
Long Context Muse Spark 1.1 leads
GPT-4.1 mini: 31.8 (#270), Muse Spark 1.1: 44.8 (#55)
| Benchmark | GPT-4.1 mini | Muse Spark 1.1 |
|---|---|---|
| LMArena Longer Query | 1344 | 1463 |
| Fiction.LiveBench | 44.4% | — |
Writing & Preference Muse Spark 1.1 leads
GPT-4.1 mini: 48.8 (#193), Muse Spark 1.1: 73.6 (#11)
| Benchmark | GPT-4.1 mini | Muse Spark 1.1 |
|---|---|---|
| LMArena Text | 1341 | 1479 |
| LMArena Creative Writing | 1300 | 1440 |
| EQ-Bench Creative Writing | 1147 | 1927 |
| LMArena Multi-Turn | 1354 | 1484 |
| WildBench | 83.8% | — |
| EQ-Bench 4 | — | 1260 |
Frequently asked questions
Is GPT-4.1 mini better than Muse Spark 1.1?
Muse Spark 1.1 is the stronger model overall, scoring 49.9 to 33.5 on the Noometry Index. GPT-4.1 mini costs 2.9× less per token, which makes it the better buy when Muse Spark 1.1's lead doesn't matter for your workload.
Which is cheaper, GPT-4.1 mini or Muse Spark 1.1?
GPT-4.1 mini is cheaper. It lists at $0.40 per million input tokens and $1.60 per million output tokens; Muse Spark 1.1 lists at $1.25 and $4.25.
Is GPT-4.1 mini or Muse Spark 1.1 better for coding?
Muse Spark 1.1 scores higher on coding benchmarks: 50.8 versus 30.4 in the Noometry coding category.
Which has the bigger context window?
Muse Spark 1.1 does, with 1.05M tokens against 1.05M.
How many benchmarks do GPT-4.1 mini and Muse Spark 1.1 share?
25 benchmarks have published results for both models. GPT-4.1 mini has 47 scored results on Noometry and Muse Spark 1.1 has 36.