Model comparison
GPT-4 vs Muse Spark 1.2
Muse Spark 1.2 is the stronger model overall, scoring 50.3 to 29.1 on the Noometry Index.
Last verified . 19 shared benchmarks.
Summary
- They share 19 benchmarks with published results for both. GPT-4 scores higher in 0 categories and Muse Spark 1.2 in 8 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where Muse Spark 1.2 leads 72.3 to 34.9.
- The biggest single-benchmark swing is WeirdML: 12.4% for GPT-4 and 60.3% for Muse Spark 1.2.
- Muse Spark 1.2 is cheaper at $1.25 / $4.25 per million input/output tokens, against $30 / $60 for GPT-4.
- Muse Spark 1.2 accepts more context: 1.05M tokens versus 8K.
Side by side
| GPT-4 | Muse Spark 1.2 | |
|---|---|---|
| Provider | OpenAI | Meta |
| Noometry Index | 29.1 | 50.3 |
| Released | 2023-03-14 | 2026-08-05 |
| 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 | 31 |
Sponsored placements are available on pages like this one. Advertise on Noometry
Category by category
Coding Muse Spark 1.2 leads
GPT-4: 31.6 (#283), Muse Spark 1.2: 49.2 (#51)
| Benchmark | GPT-4 | Muse Spark 1.2 |
|---|---|---|
| WeirdML | 12.4% | 60.3% |
| LMArena Coding | 1254 | 1495 |
| DeepSWE | — | 54.9% |
| LMArena WebDev | — | 1533 |
| FrontierSWE | — | 12% |
| SciCode | — | 56.4% |
| BigCodeBench Instruct | 46% | — |
| BigCodeBench Complete | 57.2% | — |
| HumanEval+ | 79.3% | — |
Agentic & Tool Use Not comparable
GPT-4: —, Muse Spark 1.2: 29.4 (#87)
| Benchmark | GPT-4 | Muse Spark 1.2 |
|---|---|---|
| APEX-Agents | — | 36.4% |
| GDP.pdf | — | 16% |
| METR Time Horizons | 36.1% | — |
Reasoning Muse Spark 1.2 leads
GPT-4: 17.8 (#289), Muse Spark 1.2: 51.3 (#34)
| Benchmark | GPT-4 | Muse Spark 1.2 |
|---|---|---|
| LMArena Hard Prompts | 1241 | 1486 |
| DTBench | 62.7% | 94.7% |
| LMCA | 17.1% | 48.4% |
| Epoch Capabilities Index | 125.89 | 154.87 |
| SimpleBench | — | 74.5% |
| NYT Connections (extended) | — | 79.2% |
| CritPt | — | 17.7% |
| Chess Puzzles | 4% | — |
| Mystery Game Puzzles | 12% | — |
| BIG-Bench Hard | 75.1% | — |
| ForecastBench | 57.8 | — |
| HellaSwag | 95.3% | — |
| WinoGrande | 87.5% | — |
Math Muse Spark 1.2 leads
GPT-4: 10.8 (#309), Muse Spark 1.2: 46.4 (#70)
| Benchmark | GPT-4 | Muse Spark 1.2 |
|---|---|---|
| LMArena Math | 1269 | 1471 |
| OTIS Mock AIME 2024-2025 | 1.1% | — |
| ProofBench | — | 43% |
| MATH Level 5 | 23% | — |
| GSM8K | 92% | — |
Knowledge Muse Spark 1.2 leads
GPT-4: 18.4 (#282), Muse Spark 1.2: 54.1 (#53)
| Benchmark | GPT-4 | Muse Spark 1.2 |
|---|---|---|
| LMArena Expert | 1211 | 1480 |
| GPQA Diamond | 35.7% | — |
| SimpleQA Verified | — | 60.3% |
| MMLU | 86.4% | — |
| TriviaQA | 84.8% | — |
Multimodal Not comparable
GPT-4: —, Muse Spark 1.2: 43.4 (#25)
| Benchmark | GPT-4 | Muse Spark 1.2 |
|---|---|---|
| LMArena Vision | — | 1305 |
Multilingual Muse Spark 1.2 leads
GPT-4: 40.6 (#215), Muse Spark 1.2: 57.1 (#11)
| Benchmark | GPT-4 | Muse Spark 1.2 |
|---|---|---|
| LMArena Non-English | 1246 | 1478 |
| LMArena Chinese | 1242 | 1511 |
| LMArena French | 1283 | 1513 |
| LMArena Russian | 1251 | 1487 |
| LMArena Spanish | 1261 | 1498 |
| LMArena German | 1251 | — |
| LMArena Japanese | 1209 | — |
| LMArena Korean | 1184 | — |
Instruction Following Muse Spark 1.2 leads
GPT-4: 65.3 (#222), Muse Spark 1.2: 76.7 (#36)
| Benchmark | GPT-4 | Muse Spark 1.2 |
|---|---|---|
| LMArena Instruction Following | 1241 | 1461 |
Long Context Muse Spark 1.2 leads
GPT-4: 37.7 (#212), Muse Spark 1.2: 45.2 (#48)
| Benchmark | GPT-4 | Muse Spark 1.2 |
|---|---|---|
| LMArena Longer Query | 1244 | 1475 |
Writing & Preference Muse Spark 1.2 leads
GPT-4: 34.9 (#268), Muse Spark 1.2: 72.3 (#14)
| Benchmark | GPT-4 | Muse Spark 1.2 |
|---|---|---|
| LMArena Text | 1263 | 1482 |
| LMArena Creative Writing | 1244 | 1449 |
| EQ-Bench Creative Writing | 752 | 1840 |
| LMArena Multi-Turn | 1257 | 1494 |
Frequently asked questions
Is GPT-4 better than Muse Spark 1.2?
Muse Spark 1.2 is the stronger model overall, scoring 50.3 to 29.1 on the Noometry Index.
Which is cheaper, GPT-4 or Muse Spark 1.2?
Muse Spark 1.2 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 1.2 better for coding?
Muse Spark 1.2 scores higher on coding benchmarks: 49.2 versus 31.6 in the Noometry coding category.
Which has the bigger context window?
Muse Spark 1.2 does, with 1.05M tokens against 8K.
How many benchmarks do GPT-4 and Muse Spark 1.2 share?
19 benchmarks have published results for both models. GPT-4 has 38 scored results on Noometry and Muse Spark 1.2 has 31.