Model comparison
GPT-5 Mini vs Muse Spark 1.3
Muse Spark 1.3 is the stronger model overall, scoring 54.8 to 41.8 on the Noometry Index. GPT-5 Mini costs 2.9× less per token, which makes it the better buy when Muse Spark 1.3's lead doesn't matter for your workload.
Last verified . 30 shared benchmarks.
MetaSummary
- They share 30 benchmarks with published results for both. GPT-5 Mini scores higher in 1 category and Muse Spark 1.3 in 9 categories; 10 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where Muse Spark 1.3 leads 54.0 to 23.9.
- The biggest single-benchmark swing is ProofBench: 9% for GPT-5 Mini and 58% for Muse Spark 1.3.
- GPT-5 Mini is cheaper at $0.25 / $2 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 Mini | Muse Spark 1.3 | |
|---|---|---|
| Provider | OpenAI | Meta |
| Noometry Index | 41.8 | 54.8 |
| Released | 2025-08-07 | 2026-09-02 |
| Weights | Proprietary | Proprietary |
| Context window | 400K | 1.05M |
| Max output | 128K | 131K |
| Input $ / M tokens | $0.25 | $1.25 |
| Output $ / M tokens | $2 | $4.25 |
| Results tracked | 60 | 37 |
Sponsored placements are available on pages like this one. Advertise on Noometry
Category by category
Coding Muse Spark 1.3 leads
GPT-5 Mini: 40.1 (#146), Muse Spark 1.3: 56.6 (#21)
| Benchmark | GPT-5 Mini | Muse Spark 1.3 |
|---|---|---|
| SciCode | 39.2% | 59.7% |
| LMArena Coding | 1406 | 1514 |
| SWE-bench Verified | 64.7% | — |
| SWE-bench Verified (bash only) | 59.8% | — |
| CursorBench | — | 41.6% |
| LMArena WebDev | — | 1657 |
| SWE-bench Multilingual | 39.7% | — |
| WeirdML | 52.7% | — |
| ALE-Bench | 799.77 | — |
| AlgoTune | 1.38 | — |
Agentic & Tool Use Muse Spark 1.3 leads
GPT-5 Mini: 31.1 (#70), Muse Spark 1.3: 38.6 (#30)
| Benchmark | GPT-5 Mini | Muse Spark 1.3 |
|---|---|---|
| Terminal-Bench | 34.8% | — |
| APEX-Agents | — | 57.8% |
| Berkeley Function Calling Leaderboard | 55.5% | — |
| GDP.pdf | — | 27.6% |
| Vending-Bench 2 | -31.18 | — |
Reasoning Muse Spark 1.3 leads
GPT-5 Mini: 23.9 (#168), Muse Spark 1.3: 54.0 (#27)
| Benchmark | GPT-5 Mini | Muse Spark 1.3 |
|---|---|---|
| CritPt | 0% | 26% |
| Chess Puzzles | 30% | 38% |
| LMArena Hard Prompts | 1380 | 1503 |
| Mystery Game Puzzles | 10% | 25% |
| DTBench | 80.5% | 96.5% |
| LMCA | 34.2% | 53.9% |
| Epoch Capabilities Index | 145.52 | 156.75 |
| ARC-AGI-2 | 4.4% | — |
| Kagi LLM Benchmark | 70.3% | — |
| NYT Connections (extended) | — | 85.1% |
| ARC-AGI-1 | 54.3% | — |
| EnigmaEval | 8.2% | — |
| Bench to the Future 3 | — | 0.14 |
| ForecastBench | 61 | — |
Math Muse Spark 1.3 leads
GPT-5 Mini: 46.7 (#69), Muse Spark 1.3: 73.1 (#21)
| Benchmark | GPT-5 Mini | Muse Spark 1.3 |
|---|---|---|
| FrontierMath (Tiers 1-3) | 46.7% | 74.4% |
| FrontierMath Tier 4 | 12.2% | 46.3% |
| OTIS Mock AIME 2024-2025 | 86.7% | 99.2% |
| ProofBench | 9% | 58% |
| LMArena Math | 1378 | 1494 |
| Omni-MATH | 72.2% | — |
| MATH Level 5 | 97.8% | — |
| FrontierMath (Feb 2025 set) | 27.2% | — |
| FrontierMath Tier 4 (v1) | 6.3% | — |
Knowledge GPT-5 Mini leads
GPT-5 Mini: 45.6 (#86), Muse Spark 1.3: 42.6 (#95)
| Benchmark | GPT-5 Mini | Muse Spark 1.3 |
|---|---|---|
| LMArena Expert | 1379 | 1516 |
| GPQA Diamond | 75% | — |
| Humanity's Last Exam | 19.4% | — |
| SimpleQA Verified | 21.6% | — |
| MMLU-Pro | 83.5% | — |
| Confabulations | 13.3% | — |
| Vectara Hallucination Rate | 12.9% | — |
| GPQA (HELM) | 75.6% | — |
Multimodal Muse Spark 1.3 leads
GPT-5 Mini: 35.6 (#85), Muse Spark 1.3: 43.7 (#22)
| Benchmark | GPT-5 Mini | Muse Spark 1.3 |
|---|---|---|
| LMArena Vision | 1202 | 1309 |
| VPCT | 40.2% | — |
| LMArena Document | — | 1471 |
Multilingual Muse Spark 1.3 leads
GPT-5 Mini: 48.9 (#137), Muse Spark 1.3: 57.4 (#8)
| Benchmark | GPT-5 Mini | Muse Spark 1.3 |
|---|---|---|
| LMArena Non-English | 1363 | 1481 |
| LMArena Chinese | 1385 | 1529 |
| LMArena French | 1386 | 1524 |
| LMArena German | 1366 | 1515 |
| LMArena Japanese | 1341 | 1474 |
| LMArena Korean | 1308 | 1501 |
| LMArena Russian | 1362 | 1490 |
| LMArena Spanish | 1355 | 1490 |
Instruction Following Muse Spark 1.3 leads
GPT-5 Mini: 76.2 (#46), Muse Spark 1.3: 77.5 (#22)
| Benchmark | GPT-5 Mini | Muse Spark 1.3 |
|---|---|---|
| LMArena Instruction Following | 1357 | 1477 |
| IFEval | 92.7% | — |
Long Context Muse Spark 1.3 leads
GPT-5 Mini: 41.9 (#132), Muse Spark 1.3: 45.6 (#32)
| Benchmark | GPT-5 Mini | Muse Spark 1.3 |
|---|---|---|
| LMArena Longer Query | 1355 | 1488 |
| Fiction.LiveBench | 69.4% | — |
Writing & Preference Muse Spark 1.3 leads
GPT-5 Mini: 55.2 (#148), Muse Spark 1.3: 73.6 (#9)
| Benchmark | GPT-5 Mini | Muse Spark 1.3 |
|---|---|---|
| LMArena Text | 1373 | 1490 |
| LMArena Creative Writing | 1325 | 1455 |
| EQ-Bench Creative Writing | 1313 | 1906 |
| LMArena Multi-Turn | 1363 | 1482 |
| Short-Story Creative Writing | 83.1% | — |
| WildBench | 85.5% | — |
Frequently asked questions
Is GPT-5 Mini better than Muse Spark 1.3?
Muse Spark 1.3 is the stronger model overall, scoring 54.8 to 41.8 on the Noometry Index. GPT-5 Mini costs 2.9× 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 Mini or Muse Spark 1.3?
GPT-5 Mini is cheaper. It lists at $0.25 per million input tokens and $2 per million output tokens; Muse Spark 1.3 lists at $1.25 and $4.25.
Is GPT-5 Mini or Muse Spark 1.3 better for coding?
Muse Spark 1.3 scores higher on coding benchmarks: 56.6 versus 40.1 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 Mini and Muse Spark 1.3 share?
30 benchmarks have published results for both models. GPT-5 Mini has 60 scored results on Noometry and Muse Spark 1.3 has 37.