Model comparison
GPT-5 Nano vs Muse Spark 1.2
Muse Spark 1.2 is the stronger model overall, scoring 50.3 to 33.5 on the Noometry Index. GPT-5 Nano costs 15× less per token, which makes it the better buy when Muse Spark 1.2's lead doesn't matter for your workload.
Last verified . 21 shared benchmarks.
MetaSummary
- They share 21 benchmarks with published results for both. GPT-5 Nano scores higher in 0 categories and Muse Spark 1.2 in 10 categories; 10 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where Muse Spark 1.2 leads 51.3 to 16.3.
- The biggest single-benchmark swing is SimpleQA Verified: 11.7% for GPT-5 Nano and 60.3% for Muse Spark 1.2.
- GPT-5 Nano is cheaper at $0.05 / $0.40 per million input/output tokens, against $1.25 / $4.25 for Muse Spark 1.2.
- Muse Spark 1.2 accepts more context: 1.05M tokens versus 400K.
Side by side
| GPT-5 Nano | Muse Spark 1.2 | |
|---|---|---|
| Provider | OpenAI | Meta |
| Noometry Index | 33.5 | 50.3 |
| Released | 2025-08-07 | 2026-08-05 |
| 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 | 31 |
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Category by category
Coding Muse Spark 1.2 leads
GPT-5 Nano: 33.6 (#254), Muse Spark 1.2: 49.2 (#51)
| Benchmark | GPT-5 Nano | Muse Spark 1.2 |
|---|---|---|
| WeirdML | 38.1% | 60.3% |
| LMArena Coding | 1351 | 1495 |
| DeepSWE | — | 54.9% |
| SWE-bench Verified (bash only) | 34.8% | — |
| LMArena WebDev | — | 1533 |
| FrontierSWE | — | 12% |
| SciCode | — | 56.4% |
| ALE-Bench | 718.67 | — |
Agentic & Tool Use Muse Spark 1.2 leads
GPT-5 Nano: 25.8 (#106), Muse Spark 1.2: 29.4 (#87)
| Benchmark | GPT-5 Nano | Muse Spark 1.2 |
|---|---|---|
| Terminal-Bench | 21.8% | — |
| APEX-Agents | — | 36.4% |
| Berkeley Function Calling Leaderboard | 51.5% | — |
| GDP.pdf | — | 16% |
Reasoning Muse Spark 1.2 leads
GPT-5 Nano: 16.3 (#306), Muse Spark 1.2: 51.3 (#34)
| Benchmark | GPT-5 Nano | Muse Spark 1.2 |
|---|---|---|
| LMArena Hard Prompts | 1328 | 1486 |
| DTBench | 62.7% | 94.7% |
| LMCA | 7.9% | 48.4% |
| Epoch Capabilities Index | 139.38 | 154.87 |
| ARC-AGI-2 | 2.6% | — |
| SimpleBench | — | 74.5% |
| Kagi LLM Benchmark | 62.2% | — |
| NYT Connections (extended) | — | 79.2% |
| ARC-AGI-1 | 20.7% | — |
| CritPt | — | 17.7% |
| Chess Puzzles | 27% | — |
| Mystery Game Puzzles | 9% | — |
| ForecastBench | 59.1 | — |
Math Muse Spark 1.2 leads
GPT-5 Nano: 29.4 (#241), Muse Spark 1.2: 46.4 (#70)
| Benchmark | GPT-5 Nano | Muse Spark 1.2 |
|---|---|---|
| ProofBench | 12% | 43% |
| LMArena Math | 1317 | 1471 |
| FrontierMath (Tiers 1-3) | 20% | — |
| FrontierMath Tier 4 | 2.4% | — |
| OTIS Mock AIME 2024-2025 | 81.1% | — |
| Omni-MATH | 54.6% | — |
| MATH Level 5 | 95.2% | — |
| FrontierMath (Feb 2025 set) | 8.3% | — |
| FrontierMath Tier 4 (v1) | 2.1% | — |
Knowledge Muse Spark 1.2 leads
GPT-5 Nano: 35.9 (#178), Muse Spark 1.2: 54.1 (#53)
| Benchmark | GPT-5 Nano | Muse Spark 1.2 |
|---|---|---|
| SimpleQA Verified | 11.7% | 60.3% |
| LMArena Expert | 1321 | 1480 |
| GPQA Diamond | 69.4% | — |
| MMLU-Pro | 77.8% | — |
| Vectara Hallucination Rate | 10.5% | — |
| GPQA (HELM) | 67.9% | — |
Multimodal Muse Spark 1.2 leads
GPT-5 Nano: 31.3 (#108), Muse Spark 1.2: 43.4 (#25)
| Benchmark | GPT-5 Nano | Muse Spark 1.2 |
|---|---|---|
| LMArena Vision | 1159 | 1305 |
| VPCT | 37.2% | — |
Multilingual Muse Spark 1.2 leads
GPT-5 Nano: 45.3 (#172), Muse Spark 1.2: 57.1 (#11)
| Benchmark | GPT-5 Nano | Muse Spark 1.2 |
|---|---|---|
| LMArena Non-English | 1313 | 1478 |
| LMArena Chinese | 1356 | 1511 |
| LMArena Russian | 1296 | 1487 |
| LMArena Spanish | 1360 | 1498 |
| LMArena French | — | 1513 |
| LMArena German | 1327 | — |
| LMArena Japanese | 1226 | — |
| LMArena Korean | 1269 | — |
Instruction Following Muse Spark 1.2 leads
GPT-5 Nano: 75.0 (#79), Muse Spark 1.2: 76.7 (#36)
| Benchmark | GPT-5 Nano | Muse Spark 1.2 |
|---|---|---|
| LMArena Instruction Following | 1306 | 1461 |
| IFEval | 93.2% | — |
Long Context Muse Spark 1.2 leads
GPT-5 Nano: 31.3 (#281), Muse Spark 1.2: 45.2 (#48)
| Benchmark | GPT-5 Nano | Muse Spark 1.2 |
|---|---|---|
| LMArena Longer Query | 1312 | 1475 |
| Fiction.LiveBench | 44.4% | — |
Writing & Preference Muse Spark 1.2 leads
GPT-5 Nano: 39.1 (#249), Muse Spark 1.2: 72.3 (#14)
| Benchmark | GPT-5 Nano | Muse Spark 1.2 |
|---|---|---|
| LMArena Text | 1320 | 1482 |
| LMArena Creative Writing | 1249 | 1449 |
| EQ-Bench Creative Writing | 705 | 1840 |
| LMArena Multi-Turn | 1311 | 1494 |
| WildBench | 80.6% | — |
Frequently asked questions
Is GPT-5 Nano better than Muse Spark 1.2?
Muse Spark 1.2 is the stronger model overall, scoring 50.3 to 33.5 on the Noometry Index. GPT-5 Nano costs 15× less per token, which makes it the better buy when Muse Spark 1.2's lead doesn't matter for your workload.
Which is cheaper, GPT-5 Nano or Muse Spark 1.2?
GPT-5 Nano is cheaper. It lists at $0.05 per million input tokens and $0.40 per million output tokens; Muse Spark 1.2 lists at $1.25 and $4.25.
Is GPT-5 Nano or Muse Spark 1.2 better for coding?
Muse Spark 1.2 scores higher on coding benchmarks: 49.2 versus 33.6 in the Noometry coding category.
Which has the bigger context window?
Muse Spark 1.2 does, with 1.05M tokens against 400K.
How many benchmarks do GPT-5 Nano and Muse Spark 1.2 share?
21 benchmarks have published results for both models. GPT-5 Nano has 49 scored results on Noometry and Muse Spark 1.2 has 31.