Model comparison
GPT-4 vs Muse Spark 1.3
Muse Spark 1.3 is the stronger model overall, scoring 54.8 to 29.1 on the Noometry Index.
Last verified . 24 shared benchmarks.
MetaSummary
- They share 24 benchmarks with published results for both. GPT-4 scores higher in 0 categories and Muse Spark 1.3 in 8 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in math, where Muse Spark 1.3 leads 73.1 to 10.8.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 1.1% for GPT-4 and 99.2% for Muse Spark 1.3.
- Muse Spark 1.3 is cheaper at $1.25 / $4.25 per million input/output tokens, against $30 / $60 for GPT-4.
- Muse Spark 1.3 accepts more context: 1.05M tokens versus 8K.
Side by side
| GPT-4 | Muse Spark 1.3 | |
|---|---|---|
| Provider | OpenAI | Meta |
| Noometry Index | 29.1 | 54.8 |
| Released | 2023-03-14 | 2026-09-02 |
| Weights | Proprietary | Proprietary |
| Context window | 8K | 1.05M |
| Max output | 8K | 131K |
| Input $ / M tokens | $30 | $1.25 |
| Output $ / M tokens | $60 | $4.25 |
| Results tracked | 38 | 37 |
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Category by category
Coding Muse Spark 1.3 leads
GPT-4: 31.6 (#283), Muse Spark 1.3: 56.6 (#21)
| Benchmark | GPT-4 | Muse Spark 1.3 |
|---|---|---|
| LMArena Coding | 1254 | 1514 |
| CursorBench | — | 41.6% |
| LMArena WebDev | — | 1657 |
| SciCode | — | 59.7% |
| WeirdML | 12.4% | — |
| BigCodeBench Instruct | 46% | — |
| BigCodeBench Complete | 57.2% | — |
| HumanEval+ | 79.3% | — |
Agentic & Tool Use Not comparable
GPT-4: —, Muse Spark 1.3: 38.6 (#30)
| Benchmark | GPT-4 | Muse Spark 1.3 |
|---|---|---|
| APEX-Agents | — | 57.8% |
| GDP.pdf | — | 27.6% |
| METR Time Horizons | 36.1% | — |
Reasoning Muse Spark 1.3 leads
GPT-4: 17.8 (#289), Muse Spark 1.3: 54.0 (#27)
| Benchmark | GPT-4 | Muse Spark 1.3 |
|---|---|---|
| Chess Puzzles | 4% | 38% |
| LMArena Hard Prompts | 1241 | 1503 |
| Mystery Game Puzzles | 12% | 25% |
| DTBench | 62.7% | 96.5% |
| LMCA | 17.1% | 53.9% |
| Epoch Capabilities Index | 125.89 | 156.75 |
| NYT Connections (extended) | — | 85.1% |
| CritPt | — | 26% |
| Bench to the Future 3 | — | 0.14 |
| BIG-Bench Hard | 75.1% | — |
| ForecastBench | 57.8 | — |
| HellaSwag | 95.3% | — |
| WinoGrande | 87.5% | — |
Math Muse Spark 1.3 leads
GPT-4: 10.8 (#309), Muse Spark 1.3: 73.1 (#21)
| Benchmark | GPT-4 | Muse Spark 1.3 |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 1.1% | 99.2% |
| LMArena Math | 1269 | 1494 |
| FrontierMath (Tiers 1-3) | — | 74.4% |
| FrontierMath Tier 4 | — | 46.3% |
| ProofBench | — | 58% |
| MATH Level 5 | 23% | — |
| GSM8K | 92% | — |
Knowledge Muse Spark 1.3 leads
GPT-4: 18.4 (#282), Muse Spark 1.3: 42.6 (#95)
| Benchmark | GPT-4 | Muse Spark 1.3 |
|---|---|---|
| LMArena Expert | 1211 | 1516 |
| GPQA Diamond | 35.7% | — |
| MMLU | 86.4% | — |
| TriviaQA | 84.8% | — |
Multimodal Not comparable
GPT-4: —, Muse Spark 1.3: 43.7 (#22)
| Benchmark | GPT-4 | Muse Spark 1.3 |
|---|---|---|
| LMArena Vision | — | 1309 |
| LMArena Document | — | 1471 |
Multilingual Muse Spark 1.3 leads
GPT-4: 40.6 (#215), Muse Spark 1.3: 57.4 (#8)
| Benchmark | GPT-4 | Muse Spark 1.3 |
|---|---|---|
| LMArena Non-English | 1246 | 1481 |
| LMArena Chinese | 1242 | 1529 |
| LMArena French | 1283 | 1524 |
| LMArena German | 1251 | 1515 |
| LMArena Japanese | 1209 | 1474 |
| LMArena Korean | 1184 | 1501 |
| LMArena Russian | 1251 | 1490 |
| LMArena Spanish | 1261 | 1490 |
Instruction Following Muse Spark 1.3 leads
GPT-4: 65.3 (#222), Muse Spark 1.3: 77.5 (#22)
| Benchmark | GPT-4 | Muse Spark 1.3 |
|---|---|---|
| LMArena Instruction Following | 1241 | 1477 |
Long Context Muse Spark 1.3 leads
GPT-4: 37.7 (#212), Muse Spark 1.3: 45.6 (#32)
| Benchmark | GPT-4 | Muse Spark 1.3 |
|---|---|---|
| LMArena Longer Query | 1244 | 1488 |
Writing & Preference Muse Spark 1.3 leads
GPT-4: 34.9 (#268), Muse Spark 1.3: 73.6 (#9)
| Benchmark | GPT-4 | Muse Spark 1.3 |
|---|---|---|
| LMArena Text | 1263 | 1490 |
| LMArena Creative Writing | 1244 | 1455 |
| EQ-Bench Creative Writing | 752 | 1906 |
| LMArena Multi-Turn | 1257 | 1482 |
Frequently asked questions
Is GPT-4 better than Muse Spark 1.3?
Muse Spark 1.3 is the stronger model overall, scoring 54.8 to 29.1 on the Noometry Index.
Which is cheaper, GPT-4 or Muse Spark 1.3?
Muse Spark 1.3 is cheaper. It lists at $1.25 per million input tokens and $4.25 per million output tokens; GPT-4 lists at $30 and $60.
Is GPT-4 or Muse Spark 1.3 better for coding?
Muse Spark 1.3 scores higher on coding benchmarks: 56.6 versus 31.6 in the Noometry coding category.
Which has the bigger context window?
Muse Spark 1.3 does, with 1.05M tokens against 8K.
How many benchmarks do GPT-4 and Muse Spark 1.3 share?
24 benchmarks have published results for both models. GPT-4 has 38 scored results on Noometry and Muse Spark 1.3 has 37.