Model comparison
GPT-4.1 mini vs Muse Spark 1.3
Muse Spark 1.3 is the stronger model overall, scoring 54.8 to 33.6 on the Noometry Index. GPT-4.1 mini costs 2.9× less per token, which makes it the better buy when Muse Spark 1.3's lead doesn't matter for your workload.
Last verified . 28 shared benchmarks.
MetaSummary
- They share 28 benchmarks with published results for both. GPT-4.1 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 24.1.
- The biggest single-benchmark swing is FrontierMath (Tiers 1-3): 6.7% for GPT-4.1 mini and 74.4% for Muse Spark 1.3.
- GPT-4.1 mini is cheaper at $0.40 / $1.60 per million input/output tokens, against $1.25 / $4.25 for Muse Spark 1.3.
- Muse Spark 1.3 accepts more context: 1.05M tokens versus 1.05M.
Side by side
| GPT-4.1 mini | Muse Spark 1.3 | |
|---|---|---|
| Provider | OpenAI | Meta |
| Noometry Index | 33.6 | 54.8 |
| Released | 2025-04-14 | 2026-09-02 |
| 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 | 37 |
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Category by category
Coding Muse Spark 1.3 leads
GPT-4.1 mini: 30.6 (#293), Muse Spark 1.3: 56.6 (#21)
| Benchmark | GPT-4.1 mini | Muse Spark 1.3 |
|---|---|---|
| SciCode | 40.4% | 59.7% |
| LMArena Coding | 1367 | 1514 |
| SWE-bench Verified (bash only) | 23.9% | — |
| Aider Polyglot | 32.4% | — |
| CursorBench | — | 41.6% |
| LMArena WebDev | — | 1657 |
| WeirdML | 37.6% | — |
| BigCodeBench Instruct | 48.9% | — |
| CadEval | 16% | — |
Agentic & Tool Use Muse Spark 1.3 leads
GPT-4.1 mini: 33.3 (#55), Muse Spark 1.3: 38.6 (#30)
| Benchmark | GPT-4.1 mini | Muse Spark 1.3 |
|---|---|---|
| APEX-Agents | — | 57.8% |
| Berkeley Function Calling Leaderboard | 50.5% | — |
| GDP.pdf | — | 27.6% |
Reasoning Muse Spark 1.3 leads
GPT-4.1 mini: 10.8 (#340), Muse Spark 1.3: 54.0 (#27)
| Benchmark | GPT-4.1 mini | Muse Spark 1.3 |
|---|---|---|
| CritPt | 0% | 26% |
| Chess Puzzles | 7% | 38% |
| LMArena Hard Prompts | 1349 | 1503 |
| Mystery Game Puzzles | 7% | 25% |
| DTBench | 68.8% | 96.5% |
| LMCA | 21.1% | 53.9% |
| Epoch Capabilities Index | 135.01 | 156.75 |
| ARC-AGI-2 | 0% | — |
| Kagi LLM Benchmark | 48.6% | — |
| NYT Connections (extended) | — | 85.1% |
| ARC-AGI-1 | 3.5% | — |
| Bench to the Future 3 | — | 0.14 |
Math Muse Spark 1.3 leads
GPT-4.1 mini: 24.1 (#270), Muse Spark 1.3: 73.1 (#21)
| Benchmark | GPT-4.1 mini | Muse Spark 1.3 |
|---|---|---|
| FrontierMath (Tiers 1-3) | 6.7% | 74.4% |
| OTIS Mock AIME 2024-2025 | 44.7% | 99.2% |
| LMArena Math | 1343 | 1494 |
| FrontierMath Tier 4 | — | 46.3% |
| ProofBench | — | 58% |
| Omni-MATH | 49.1% | — |
| MATH Level 5 | 87.3% | — |
| FrontierMath (Feb 2025 set) | 4.5% | — |
Knowledge Muse Spark 1.3 leads
GPT-4.1 mini: 34.7 (#194), Muse Spark 1.3: 42.6 (#95)
| Benchmark | GPT-4.1 mini | Muse Spark 1.3 |
|---|---|---|
| LMArena Expert | 1338 | 1516 |
| GPQA Diamond | 65.8% | — |
| SimpleQA Verified | 12.7% | — |
| MMLU-Pro | 78.3% | — |
| GPQA (HELM) | 61.4% | — |
Multimodal Muse Spark 1.3 leads
GPT-4.1 mini: 35.8 (#82), Muse Spark 1.3: 43.7 (#22)
| Benchmark | GPT-4.1 mini | Muse Spark 1.3 |
|---|---|---|
| LMArena Vision | 1181 | 1309 |
| LMArena Document | — | 1471 |
Multilingual Muse Spark 1.3 leads
GPT-4.1 mini: 45.7 (#166), Muse Spark 1.3: 57.4 (#8)
| Benchmark | GPT-4.1 mini | Muse Spark 1.3 |
|---|---|---|
| LMArena Non-English | 1318 | 1481 |
| LMArena Chinese | 1329 | 1529 |
| LMArena French | 1358 | 1524 |
| LMArena German | 1351 | 1515 |
| LMArena Japanese | 1290 | 1474 |
| LMArena Korean | 1298 | 1501 |
| LMArena Russian | 1324 | 1490 |
| LMArena Spanish | 1319 | 1490 |
Instruction Following Muse Spark 1.3 leads
GPT-4.1 mini: 73.7 (#118), Muse Spark 1.3: 77.5 (#22)
| Benchmark | GPT-4.1 mini | Muse Spark 1.3 |
|---|---|---|
| LMArena Instruction Following | 1333 | 1477 |
| IFEval | 90.4% | — |
Long Context Muse Spark 1.3 leads
GPT-4.1 mini: 31.8 (#275), Muse Spark 1.3: 45.6 (#32)
| Benchmark | GPT-4.1 mini | Muse Spark 1.3 |
|---|---|---|
| LMArena Longer Query | 1344 | 1488 |
| Fiction.LiveBench | 44.4% | — |
Writing & Preference Muse Spark 1.3 leads
GPT-4.1 mini: 48.6 (#199), Muse Spark 1.3: 73.6 (#9)
| Benchmark | GPT-4.1 mini | Muse Spark 1.3 |
|---|---|---|
| LMArena Text | 1340 | 1490 |
| LMArena Creative Writing | 1300 | 1455 |
| EQ-Bench Creative Writing | 1147 | 1906 |
| LMArena Multi-Turn | 1354 | 1482 |
| WildBench | 83.8% | — |
Frequently asked questions
Is GPT-4.1 mini better than Muse Spark 1.3?
Muse Spark 1.3 is the stronger model overall, scoring 54.8 to 33.6 on the Noometry Index. GPT-4.1 mini costs 2.9× 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-4.1 mini or Muse Spark 1.3?
GPT-4.1 mini is cheaper. It lists at $0.40 per million input tokens and $1.60 per million output tokens; Muse Spark 1.3 lists at $1.25 and $4.25.
Is GPT-4.1 mini or Muse Spark 1.3 better for coding?
Muse Spark 1.3 scores higher on coding benchmarks: 56.6 versus 30.6 in the Noometry coding category.
Which has the bigger context window?
Muse Spark 1.3 does, with 1.05M tokens against 1.05M.
How many benchmarks do GPT-4.1 mini and Muse Spark 1.3 share?
28 benchmarks have published results for both models. GPT-4.1 mini has 47 scored results on Noometry and Muse Spark 1.3 has 37.