Model comparison
GPT-5 Nano vs Muse Spark 1.3
Muse Spark 1.3 is the stronger model overall, scoring 54.8 to 33.5 on the Noometry Index. GPT-5 Nano costs 15× less per token, which makes it the better buy when Muse Spark 1.3's lead doesn't matter for your workload.
Last verified . 27 shared benchmarks.
MetaSummary
- They share 27 benchmarks with published results for both. GPT-5 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 29.4.
- The biggest single-benchmark swing is FrontierMath (Tiers 1-3): 20% for GPT-5 Nano and 74.4% for Muse Spark 1.3.
- GPT-5 Nano is cheaper at $0.05 / $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 400K.
Side by side
| GPT-5 Nano | Muse Spark 1.3 | |
|---|---|---|
| Provider | OpenAI | Meta |
| Noometry Index | 33.5 | 54.8 |
| Released | 2025-08-07 | 2026-09-02 |
| Weights | Proprietary | Proprietary |
| Context window | 400K | 1.05M |
| Max output | 128K | 131K |
| Input $ / M tokens | $0.05 | $1.25 |
| Output $ / M tokens | $0.40 | $4.25 |
| Results tracked | 49 | 37 |
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Category by category
Coding Muse Spark 1.3 leads
GPT-5 Nano: 33.6 (#254), Muse Spark 1.3: 56.6 (#21)
| Benchmark | GPT-5 Nano | Muse Spark 1.3 |
|---|---|---|
| LMArena Coding | 1351 | 1514 |
| SWE-bench Verified (bash only) | 34.8% | — |
| CursorBench | — | 41.6% |
| LMArena WebDev | — | 1657 |
| SciCode | — | 59.7% |
| WeirdML | 38.1% | — |
| ALE-Bench | 718.67 | — |
Agentic & Tool Use Muse Spark 1.3 leads
GPT-5 Nano: 25.8 (#106), Muse Spark 1.3: 38.6 (#30)
| Benchmark | GPT-5 Nano | Muse Spark 1.3 |
|---|---|---|
| Terminal-Bench | 21.8% | — |
| APEX-Agents | — | 57.8% |
| Berkeley Function Calling Leaderboard | 51.5% | — |
| GDP.pdf | — | 27.6% |
Reasoning Muse Spark 1.3 leads
GPT-5 Nano: 16.3 (#306), Muse Spark 1.3: 54.0 (#27)
| Benchmark | GPT-5 Nano | Muse Spark 1.3 |
|---|---|---|
| Chess Puzzles | 27% | 38% |
| LMArena Hard Prompts | 1328 | 1503 |
| Mystery Game Puzzles | 9% | 25% |
| DTBench | 62.7% | 96.5% |
| LMCA | 7.9% | 53.9% |
| Epoch Capabilities Index | 139.38 | 156.75 |
| ARC-AGI-2 | 2.6% | — |
| Kagi LLM Benchmark | 62.2% | — |
| NYT Connections (extended) | — | 85.1% |
| ARC-AGI-1 | 20.7% | — |
| CritPt | — | 26% |
| Bench to the Future 3 | — | 0.14 |
| ForecastBench | 59.1 | — |
Math Muse Spark 1.3 leads
GPT-5 Nano: 29.4 (#241), Muse Spark 1.3: 73.1 (#21)
| Benchmark | GPT-5 Nano | Muse Spark 1.3 |
|---|---|---|
| FrontierMath (Tiers 1-3) | 20% | 74.4% |
| FrontierMath Tier 4 | 2.4% | 46.3% |
| OTIS Mock AIME 2024-2025 | 81.1% | 99.2% |
| ProofBench | 12% | 58% |
| LMArena Math | 1317 | 1494 |
| Omni-MATH | 54.6% | — |
| MATH Level 5 | 95.2% | — |
| FrontierMath (Feb 2025 set) | 8.3% | — |
| FrontierMath Tier 4 (v1) | 2.1% | — |
Knowledge Muse Spark 1.3 leads
GPT-5 Nano: 35.9 (#178), Muse Spark 1.3: 42.6 (#95)
| Benchmark | GPT-5 Nano | Muse Spark 1.3 |
|---|---|---|
| LMArena Expert | 1321 | 1516 |
| GPQA Diamond | 69.4% | — |
| SimpleQA Verified | 11.7% | — |
| MMLU-Pro | 77.8% | — |
| Vectara Hallucination Rate | 10.5% | — |
| GPQA (HELM) | 67.9% | — |
Multimodal Muse Spark 1.3 leads
GPT-5 Nano: 31.3 (#108), Muse Spark 1.3: 43.7 (#22)
| Benchmark | GPT-5 Nano | Muse Spark 1.3 |
|---|---|---|
| LMArena Vision | 1159 | 1309 |
| VPCT | 37.2% | — |
| LMArena Document | — | 1471 |
Multilingual Muse Spark 1.3 leads
GPT-5 Nano: 45.3 (#172), Muse Spark 1.3: 57.4 (#8)
| Benchmark | GPT-5 Nano | Muse Spark 1.3 |
|---|---|---|
| LMArena Non-English | 1313 | 1481 |
| LMArena Chinese | 1356 | 1529 |
| LMArena German | 1327 | 1515 |
| LMArena Japanese | 1226 | 1474 |
| LMArena Korean | 1269 | 1501 |
| LMArena Russian | 1296 | 1490 |
| LMArena Spanish | 1360 | 1490 |
| LMArena French | — | 1524 |
Instruction Following Muse Spark 1.3 leads
GPT-5 Nano: 75.0 (#79), Muse Spark 1.3: 77.5 (#22)
| Benchmark | GPT-5 Nano | Muse Spark 1.3 |
|---|---|---|
| LMArena Instruction Following | 1306 | 1477 |
| IFEval | 93.2% | — |
Long Context Muse Spark 1.3 leads
GPT-5 Nano: 31.3 (#281), Muse Spark 1.3: 45.6 (#32)
| Benchmark | GPT-5 Nano | Muse Spark 1.3 |
|---|---|---|
| LMArena Longer Query | 1312 | 1488 |
| Fiction.LiveBench | 44.4% | — |
Writing & Preference Muse Spark 1.3 leads
GPT-5 Nano: 39.1 (#249), Muse Spark 1.3: 73.6 (#9)
| Benchmark | GPT-5 Nano | Muse Spark 1.3 |
|---|---|---|
| LMArena Text | 1320 | 1490 |
| LMArena Creative Writing | 1249 | 1455 |
| EQ-Bench Creative Writing | 705 | 1906 |
| LMArena Multi-Turn | 1311 | 1482 |
| WildBench | 80.6% | — |
Frequently asked questions
Is GPT-5 Nano better than Muse Spark 1.3?
Muse Spark 1.3 is the stronger model overall, scoring 54.8 to 33.5 on the Noometry Index. GPT-5 Nano costs 15× 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-5 Nano or Muse Spark 1.3?
GPT-5 Nano is cheaper. It lists at $0.05 per million input tokens and $0.40 per million output tokens; Muse Spark 1.3 lists at $1.25 and $4.25.
Is GPT-5 Nano or Muse Spark 1.3 better for coding?
Muse Spark 1.3 scores higher on coding benchmarks: 56.6 versus 33.6 in the Noometry coding category.
Which has the bigger context window?
Muse Spark 1.3 does, with 1.05M tokens against 400K.
How many benchmarks do GPT-5 Nano and Muse Spark 1.3 share?
27 benchmarks have published results for both models. GPT-5 Nano has 49 scored results on Noometry and Muse Spark 1.3 has 37.