Model comparison
GPT-4.1 nano vs Muse Spark 1.1
Muse Spark 1.1 is the stronger model overall, scoring 49.9 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 1.1'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 1.1 in 10 categories; 10 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where Muse Spark 1.1 leads 47.1 to 8.5.
- The biggest single-benchmark swing is SimpleQA Verified: 6% for GPT-4.1 nano and 57.8% for Muse Spark 1.1.
- GPT-4.1 nano is cheaper at $0.10 / $0.40 per million input/output tokens, against $1.25 / $4.25 for Muse Spark 1.1.
- Muse Spark 1.1 accepts more context: 1.05M tokens versus 1.05M.
Side by side
| GPT-4.1 nano | Muse Spark 1.1 | |
|---|---|---|
| Provider | OpenAI | Meta |
| Noometry Index | 27.9 | 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 | $0.10 | $1.25 |
| Output $ / M tokens | $0.40 | $4.25 |
| Results tracked | 38 | 37 |
Sponsored placements are available on pages like this one. Advertise on Noometry
Category by category
Coding Muse Spark 1.1 leads
GPT-4.1 nano: 24.1 (#330), Muse Spark 1.1: 51.3 (#40)
| Benchmark | GPT-4.1 nano | Muse Spark 1.1 |
|---|---|---|
| SciCode | 25.9% | 58.8% |
| LMArena Coding | 1306 | 1498 |
| DeepSWE | — | 53.3% |
| Aider Polyglot | 8.9% | — |
| LMArena WebDev | — | 1542 |
| WeirdML | 19% | — |
Agentic & Tool Use Muse Spark 1.1 leads
GPT-4.1 nano: 26.5 (#104), Muse Spark 1.1: 30.8 (#73)
| Benchmark | GPT-4.1 nano | Muse Spark 1.1 |
|---|---|---|
| APEX-Agents | — | 31.8% |
| Berkeley Function Calling Leaderboard | 33% | — |
| 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 nano: 8.5 (#349), Muse Spark 1.1: 47.1 (#44)
| Benchmark | GPT-4.1 nano | Muse Spark 1.1 |
|---|---|---|
| CritPt | 0% | 15.1% |
| LMArena Hard Prompts | 1286 | 1486 |
| DTBench | 52.5% | 94.4% |
| LMCA | 5.5% | 49.9% |
| Epoch Capabilities Index | 129.62 | 154.21 |
| ARC-AGI-2 | 0% | — |
| Kagi LLM Benchmark | 33.3% | — |
| NYT Connections (extended) | — | 84.9% |
| ARC-AGI-1 | 0% | — |
| Surface Evolver Bench | — | 52.5% |
Math Muse Spark 1.1 leads
GPT-4.1 nano: 26.9 (#252), Muse Spark 1.1: 45.5 (#76)
| Benchmark | GPT-4.1 nano | Muse Spark 1.1 |
|---|---|---|
| LMArena Math | 1274 | 1483 |
| OTIS Mock AIME 2024-2025 | 28.9% | — |
| ProofBench | — | 39% |
| Omni-MATH | 36.7% | — |
| MATH Level 5 | 70% | — |
| FrontierMath (Feb 2025 set) | 1% | — |
Knowledge Muse Spark 1.1 leads
GPT-4.1 nano: 21.8 (#273), Muse Spark 1.1: 53.1 (#59)
| Benchmark | GPT-4.1 nano | Muse Spark 1.1 |
|---|---|---|
| SimpleQA Verified | 6% | 57.8% |
| LMArena Expert | 1272 | 1478 |
| GPQA Diamond | 48.9% | — |
| MMLU-Pro | 55% | — |
| GPQA (HELM) | 50.7% | — |
Multimodal Muse Spark 1.1 leads
GPT-4.1 nano: 29.2 (#113), Muse Spark 1.1: 42.6 (#29)
| Benchmark | GPT-4.1 nano | Muse Spark 1.1 |
|---|---|---|
| LMArena Vision | 1063 | 1293 |
| LMArena Document | — | 1465 |
Multilingual Muse Spark 1.1 leads
GPT-4.1 nano: 41.6 (#205), Muse Spark 1.1: 56.7 (#17)
| Benchmark | GPT-4.1 nano | Muse Spark 1.1 |
|---|---|---|
| LMArena Non-English | 1260 | 1472 |
| LMArena Chinese | 1270 | 1518 |
| LMArena German | 1288 | 1466 |
| LMArena Japanese | 1198 | 1451 |
| LMArena Russian | 1261 | 1483 |
| LMArena French | — | 1494 |
| LMArena Korean | — | 1458 |
| LMArena Spanish | — | 1464 |
Instruction Following Muse Spark 1.1 leads
GPT-4.1 nano: 67.8 (#193), Muse Spark 1.1: 76.5 (#39)
| Benchmark | GPT-4.1 nano | Muse Spark 1.1 |
|---|---|---|
| LMArena Instruction Following | 1267 | 1457 |
| IFEval | 84.3% | — |
Long Context Muse Spark 1.1 leads
GPT-4.1 nano: 23.7 (#296), Muse Spark 1.1: 44.8 (#58)
| Benchmark | GPT-4.1 nano | Muse Spark 1.1 |
|---|---|---|
| LMArena Longer Query | 1283 | 1462 |
| Fiction.LiveBench | 25% | — |
Writing & Preference Muse Spark 1.1 leads
GPT-4.1 nano: 40.5 (#243), Muse Spark 1.1: 73.4 (#11)
| Benchmark | GPT-4.1 nano | Muse Spark 1.1 |
|---|---|---|
| LMArena Text | 1285 | 1479 |
| LMArena Creative Writing | 1260 | 1437 |
| EQ-Bench Creative Writing | 946 | 1927 |
| LMArena Multi-Turn | 1277 | 1485 |
| WildBench | 81.2% | — |
| EQ-Bench 4 | — | 1260 |
Frequently asked questions
Is GPT-4.1 nano better than Muse Spark 1.1?
Muse Spark 1.1 is the stronger model overall, scoring 49.9 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 1.1's lead doesn't matter for your workload.
Which is cheaper, GPT-4.1 nano or Muse Spark 1.1?
GPT-4.1 nano is cheaper. It lists at $0.10 per million input tokens and $0.40 per million output tokens; Muse Spark 1.1 lists at $1.25 and $4.25.
Is GPT-4.1 nano or Muse Spark 1.1 better for coding?
Muse Spark 1.1 scores higher on coding benchmarks: 51.3 versus 24.1 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 nano and Muse Spark 1.1 share?
22 benchmarks have published results for both models. GPT-4.1 nano has 38 scored results on Noometry and Muse Spark 1.1 has 37.