Model comparison
GPT-5 Nano vs Muse Spark 1.3
Muse Spark 1.3 is the stronger model overall, scoring 54.4 to 33.4 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 . 24 shared benchmarks.
MetaSummary
- They share 24 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 72.4 to 29.1.
- 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 | 33.4 | 54.4 |
| 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 | 48 | 34 |
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Category by category
Coding Muse Spark 1.3 leads
GPT-5 Nano: 33.3 (#248), Muse Spark 1.3: 56.1 (#18)
| Benchmark | GPT-5 Nano | Muse Spark 1.3 |
|---|---|---|
| LMArena Coding | 1351 | 1516 |
| SWE-bench Verified (bash only) | 34.8% | — |
| CursorBench | — | 41.6% |
| LMArena WebDev | — | 1655 |
| SciCode | — | 59.7% |
| WeirdML | 38.1% | — |
| ALE-Bench | 718.67 | — |
Agentic & Tool Use Muse Spark 1.3 leads
GPT-5 Nano: 25.6 (#99), Muse Spark 1.3: 38.6 (#28)
| 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: 16.4 (#291), Muse Spark 1.3: 52.9 (#27)
| Benchmark | GPT-5 Nano | Muse Spark 1.3 |
|---|---|---|
| Chess Puzzles | 27% | 38% |
| LMArena Hard Prompts | 1329 | 1503 |
| Mystery Game Puzzles | 9% | 25% |
| DTBench | 62.7% | 96.5% |
| LMCA | 7.9% | 53.9% |
| Epoch Capabilities Index | 139.39 | 156.89 |
| ARC-AGI-2 | 2.6% | — |
| Kagi LLM Benchmark | 62.2% | — |
| NYT Connections (extended) | — | 85.1% |
| ARC-AGI-1 | 20.7% | — |
| CritPt | — | 24.9% |
| Bench to the Future 3 | — | 0.14 |
| ForecastBench | 59.1 | — |
Math Muse Spark 1.3 leads
GPT-5 Nano: 29.1 (#221), Muse Spark 1.3: 72.4 (#16)
| 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% |
| LMArena Math | 1318 | 1497 |
| ProofBench | 12% | — |
| 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: 35.8 (#166), Muse Spark 1.3: 42.0 (#92)
| 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: 30.7 (#102), Muse Spark 1.3: 43.0 (#21)
| Benchmark | GPT-5 Nano | Muse Spark 1.3 |
|---|---|---|
| LMArena Vision | 1159 | 1310 |
| VPCT | 37.2% | — |
| LMArena Document | — | 1471 |
Multilingual Muse Spark 1.3 leads
GPT-5 Nano: 45.5 (#167), Muse Spark 1.3: 57.8 (#6)
| Benchmark | GPT-5 Nano | Muse Spark 1.3 |
|---|---|---|
| LMArena Non-English | 1313 | 1485 |
| LMArena Chinese | 1355 | 1527 |
| LMArena Korean | 1269 | 1513 |
| LMArena Russian | 1296 | 1491 |
| LMArena Spanish | 1360 | 1485 |
| LMArena French | — | 1534 |
| LMArena German | 1329 | — |
Instruction Following Muse Spark 1.3 leads
GPT-5 Nano: 75.2 (#72), Muse Spark 1.3: 77.8 (#14)
| Benchmark | GPT-5 Nano | Muse Spark 1.3 |
|---|---|---|
| LMArena Instruction Following | 1306 | 1481 |
| IFEval | 93.2% | — |
Long Context Muse Spark 1.3 leads
GPT-5 Nano: 31.3 (#275), Muse Spark 1.3: 45.7 (#29)
| Benchmark | GPT-5 Nano | Muse Spark 1.3 |
|---|---|---|
| LMArena Longer Query | 1313 | 1491 |
| Fiction.LiveBench | 44.4% | — |
Writing & Preference Muse Spark 1.3 leads
GPT-5 Nano: 39.4 (#244), Muse Spark 1.3: 73.7 (#10)
| Benchmark | GPT-5 Nano | Muse Spark 1.3 |
|---|---|---|
| LMArena Text | 1320 | 1490 |
| LMArena Creative Writing | 1250 | 1450 |
| EQ-Bench Creative Writing | 705 | 1906 |
| LMArena Multi-Turn | 1311 | 1486 |
| 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 54.4 to 33.4 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: 56.1 versus 33.3 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?
24 benchmarks have published results for both models. GPT-5 Nano has 48 scored results on Noometry and Muse Spark 1.3 has 34.