Model comparison
GPT-4.1 nano vs Muse Spark 1.3
Muse Spark 1.3 is the stronger model overall, scoring 54.8 to 27.9 on the Noometry Index. GPT-4.1 nano costs 11× less per token, which makes it the better buy when Muse Spark 1.3's lead doesn't matter for your workload.
Last verified . 22 shared benchmarks.
MetaSummary
- They share 22 benchmarks with published results for both. GPT-4.1 nano 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 26.9.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 28.9% for GPT-4.1 nano and 99.2% for Muse Spark 1.3.
- GPT-4.1 nano is cheaper at $0.10 / $0.40 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 nano | Muse Spark 1.3 | |
|---|---|---|
| Provider | OpenAI | Meta |
| Noometry Index | 27.9 | 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 | $0.10 | $1.25 |
| Output $ / M tokens | $0.40 | $4.25 |
| Results tracked | 38 | 37 |
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Category by category
Coding Muse Spark 1.3 leads
GPT-4.1 nano: 24.1 (#330), Muse Spark 1.3: 56.6 (#21)
| Benchmark | GPT-4.1 nano | Muse Spark 1.3 |
|---|---|---|
| SciCode | 25.9% | 59.7% |
| LMArena Coding | 1306 | 1514 |
| Aider Polyglot | 8.9% | — |
| CursorBench | — | 41.6% |
| LMArena WebDev | — | 1657 |
| WeirdML | 19% | — |
Agentic & Tool Use Muse Spark 1.3 leads
GPT-4.1 nano: 26.5 (#104), Muse Spark 1.3: 38.6 (#30)
| Benchmark | GPT-4.1 nano | Muse Spark 1.3 |
|---|---|---|
| APEX-Agents | — | 57.8% |
| Berkeley Function Calling Leaderboard | 33% | — |
| GDP.pdf | — | 27.6% |
Reasoning Muse Spark 1.3 leads
GPT-4.1 nano: 8.5 (#349), Muse Spark 1.3: 54.0 (#27)
| Benchmark | GPT-4.1 nano | Muse Spark 1.3 |
|---|---|---|
| CritPt | 0% | 26% |
| LMArena Hard Prompts | 1286 | 1503 |
| DTBench | 52.5% | 96.5% |
| LMCA | 5.5% | 53.9% |
| Epoch Capabilities Index | 129.62 | 156.75 |
| ARC-AGI-2 | 0% | — |
| Kagi LLM Benchmark | 33.3% | — |
| NYT Connections (extended) | — | 85.1% |
| ARC-AGI-1 | 0% | — |
| Chess Puzzles | — | 38% |
| Mystery Game Puzzles | — | 25% |
| Bench to the Future 3 | — | 0.14 |
Math Muse Spark 1.3 leads
GPT-4.1 nano: 26.9 (#252), Muse Spark 1.3: 73.1 (#21)
| Benchmark | GPT-4.1 nano | Muse Spark 1.3 |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 28.9% | 99.2% |
| LMArena Math | 1274 | 1494 |
| FrontierMath (Tiers 1-3) | — | 74.4% |
| FrontierMath Tier 4 | — | 46.3% |
| ProofBench | — | 58% |
| Omni-MATH | 36.7% | — |
| MATH Level 5 | 70% | — |
| FrontierMath (Feb 2025 set) | 1% | — |
Knowledge Muse Spark 1.3 leads
GPT-4.1 nano: 21.8 (#273), Muse Spark 1.3: 42.6 (#95)
| Benchmark | GPT-4.1 nano | Muse Spark 1.3 |
|---|---|---|
| LMArena Expert | 1272 | 1516 |
| GPQA Diamond | 48.9% | — |
| SimpleQA Verified | 6% | — |
| MMLU-Pro | 55% | — |
| GPQA (HELM) | 50.7% | — |
Multimodal Muse Spark 1.3 leads
GPT-4.1 nano: 29.2 (#113), Muse Spark 1.3: 43.7 (#22)
| Benchmark | GPT-4.1 nano | Muse Spark 1.3 |
|---|---|---|
| LMArena Vision | 1063 | 1309 |
| LMArena Document | — | 1471 |
Multilingual Muse Spark 1.3 leads
GPT-4.1 nano: 41.6 (#205), Muse Spark 1.3: 57.4 (#8)
| Benchmark | GPT-4.1 nano | Muse Spark 1.3 |
|---|---|---|
| LMArena Non-English | 1260 | 1481 |
| LMArena Chinese | 1270 | 1529 |
| LMArena German | 1288 | 1515 |
| LMArena Japanese | 1198 | 1474 |
| LMArena Russian | 1261 | 1490 |
| LMArena French | — | 1524 |
| LMArena Korean | — | 1501 |
| LMArena Spanish | — | 1490 |
Instruction Following Muse Spark 1.3 leads
GPT-4.1 nano: 67.8 (#193), Muse Spark 1.3: 77.5 (#22)
| Benchmark | GPT-4.1 nano | Muse Spark 1.3 |
|---|---|---|
| LMArena Instruction Following | 1267 | 1477 |
| IFEval | 84.3% | — |
Long Context Muse Spark 1.3 leads
GPT-4.1 nano: 23.7 (#296), Muse Spark 1.3: 45.6 (#32)
| Benchmark | GPT-4.1 nano | Muse Spark 1.3 |
|---|---|---|
| LMArena Longer Query | 1283 | 1488 |
| Fiction.LiveBench | 25% | — |
Writing & Preference Muse Spark 1.3 leads
GPT-4.1 nano: 40.5 (#243), Muse Spark 1.3: 73.6 (#9)
| Benchmark | GPT-4.1 nano | Muse Spark 1.3 |
|---|---|---|
| LMArena Text | 1285 | 1490 |
| LMArena Creative Writing | 1260 | 1455 |
| EQ-Bench Creative Writing | 946 | 1906 |
| LMArena Multi-Turn | 1277 | 1482 |
| WildBench | 81.2% | — |
Frequently asked questions
Is GPT-4.1 nano better than Muse Spark 1.3?
Muse Spark 1.3 is the stronger model overall, scoring 54.8 to 27.9 on the Noometry Index. GPT-4.1 nano costs 11× 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 nano or Muse Spark 1.3?
GPT-4.1 nano is cheaper. It lists at $0.10 per million input tokens and $0.40 per million output tokens; Muse Spark 1.3 lists at $1.25 and $4.25.
Is GPT-4.1 nano or Muse Spark 1.3 better for coding?
Muse Spark 1.3 scores higher on coding benchmarks: 56.6 versus 24.1 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 nano and Muse Spark 1.3 share?
22 benchmarks have published results for both models. GPT-4.1 nano has 38 scored results on Noometry and Muse Spark 1.3 has 37.