Model comparison
GPT-5.6 Terra vs Muse Spark 1.3
GPT-5.6 Terra is the stronger model overall, scoring 59.2 to 54.8 on the Noometry Index. Muse Spark 1.3 costs 2.3× less per token, which makes it the better buy when GPT-5.6 Terra's lead doesn't matter for your workload.
Last verified . 36 shared benchmarks.
MetaSummary
- They share 36 benchmarks with published results for both. GPT-5.6 Terra scores higher in 6 categories and Muse Spark 1.3 in 4 categories; 10 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where GPT-5.6 Terra leads 61.2 to 42.6.
- The biggest single-benchmark swing is FrontierMath Tier 4: 70.7% for GPT-5.6 Terra and 46.3% for Muse Spark 1.3.
- Muse Spark 1.3 is cheaper at $1.25 / $4.25 per million input/output tokens, against $2 / $12 for GPT-5.6 Terra.
- GPT-5.6 Terra accepts more context: 1.05M tokens versus 1.05M.
Side by side
| GPT-5.6 Terra | Muse Spark 1.3 | |
|---|---|---|
| Provider | OpenAI | Meta |
| Noometry Index | 59.2 | 54.8 |
| Released | 2026-07-09 | 2026-09-02 |
| Weights | Proprietary | Proprietary |
| Context window | 1.05M | 1.05M |
| Max output | 128K | 131K |
| Input $ / M tokens | $2 | $1.25 |
| Output $ / M tokens | $12 | $4.25 |
| Results tracked | 52 | 37 |
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Category by category
Coding GPT-5.6 Terra leads
GPT-5.6 Terra: 57.7 (#19), Muse Spark 1.3: 56.6 (#21)
| Benchmark | GPT-5.6 Terra | Muse Spark 1.3 |
|---|---|---|
| CursorBench | 41.3% | 41.6% |
| LMArena WebDev | 1522 | 1657 |
| SciCode | 55% | 59.7% |
| LMArena Coding | 1484 | 1514 |
| DeepSWE | 69.6% | — |
| FrontierCode | 41.3% | — |
| WeirdML | 78.3% | — |
| ALE-Bench | 1,951 | — |
Agentic & Tool Use GPT-5.6 Terra leads
GPT-5.6 Terra: 40.1 (#25), Muse Spark 1.3: 38.6 (#30)
| Benchmark | GPT-5.6 Terra | Muse Spark 1.3 |
|---|---|---|
| APEX-Agents | 58.2% | 57.8% |
| GDP.pdf | 24.7% | 27.6% |
| BALROG | 53.2% | — |
| Vending-Bench 2 | 7,343 | — |
Reasoning GPT-5.6 Terra leads
GPT-5.6 Terra: 60.7 (#21), Muse Spark 1.3: 54.0 (#27)
| Benchmark | GPT-5.6 Terra | Muse Spark 1.3 |
|---|---|---|
| NYT Connections (extended) | 78.4% | 85.1% |
| CritPt | 30% | 26% |
| Chess Puzzles | 54% | 38% |
| LMArena Hard Prompts | 1468 | 1503 |
| Mystery Game Puzzles | 35% | 25% |
| DTBench | 93.3% | 96.5% |
| LMCA | 55% | 53.9% |
| Epoch Capabilities Index | 159.62 | 156.75 |
| ARC-AGI-2 | 83.9% | — |
| SimpleBench | 48.9% | — |
| Kagi LLM Benchmark | 51.3% | — |
| ARC-AGI-1 | 96.5% | — |
| Surface Evolver Bench | 83.8% | — |
| Bench to the Future 3 | — | 0.14 |
Math GPT-5.6 Terra leads
GPT-5.6 Terra: 81.6 (#12), Muse Spark 1.3: 73.1 (#21)
| Benchmark | GPT-5.6 Terra | Muse Spark 1.3 |
|---|---|---|
| FrontierMath (Tiers 1-3) | 86% | 74.4% |
| FrontierMath Tier 4 | 70.7% | 46.3% |
| OTIS Mock AIME 2024-2025 | 99.7% | 99.2% |
| ProofBench | 74% | 58% |
| LMArena Math | 1466 | 1494 |
Knowledge GPT-5.6 Terra leads
GPT-5.6 Terra: 61.2 (#30), Muse Spark 1.3: 42.6 (#95)
| Benchmark | GPT-5.6 Terra | Muse Spark 1.3 |
|---|---|---|
| LMArena Expert | 1492 | 1516 |
| GPQA Diamond | 93.3% | — |
| SimpleQA Verified | 43.2% | — |
Multimodal GPT-5.6 Terra leads
GPT-5.6 Terra: 47.3 (#11), Muse Spark 1.3: 43.7 (#22)
| Benchmark | GPT-5.6 Terra | Muse Spark 1.3 |
|---|---|---|
| LMArena Vision | 1271 | 1309 |
| LMArena Document | 1472 | 1471 |
| Blueprint-Bench 2 | 30.8% | — |
| Furniture Assembly | 54.2% | — |
Multilingual Muse Spark 1.3 leads
GPT-5.6 Terra: 54.4 (#44), Muse Spark 1.3: 57.4 (#8)
| Benchmark | GPT-5.6 Terra | Muse Spark 1.3 |
|---|---|---|
| LMArena Non-English | 1439 | 1481 |
| LMArena Chinese | 1513 | 1529 |
| LMArena French | 1471 | 1524 |
| LMArena German | 1460 | 1515 |
| LMArena Japanese | 1457 | 1474 |
| LMArena Korean | 1425 | 1501 |
| LMArena Russian | 1450 | 1490 |
| LMArena Spanish | 1448 | 1490 |
Instruction Following Muse Spark 1.3 leads
GPT-5.6 Terra: 76.4 (#40), Muse Spark 1.3: 77.5 (#22)
| Benchmark | GPT-5.6 Terra | Muse Spark 1.3 |
|---|---|---|
| LMArena Instruction Following | 1454 | 1477 |
Long Context Muse Spark 1.3 leads
GPT-5.6 Terra: 44.4 (#68), Muse Spark 1.3: 45.6 (#32)
| Benchmark | GPT-5.6 Terra | Muse Spark 1.3 |
|---|---|---|
| LMArena Longer Query | 1451 | 1488 |
Writing & Preference Muse Spark 1.3 leads
GPT-5.6 Terra: 70.2 (#23), Muse Spark 1.3: 73.6 (#9)
| Benchmark | GPT-5.6 Terra | Muse Spark 1.3 |
|---|---|---|
| LMArena Text | 1447 | 1490 |
| LMArena Creative Writing | 1410 | 1455 |
| EQ-Bench Creative Writing | 1855 | 1906 |
| LMArena Multi-Turn | 1449 | 1482 |
| EQ-Bench 4 | 1234 | — |
Frequently asked questions
Is GPT-5.6 Terra better than Muse Spark 1.3?
GPT-5.6 Terra is the stronger model overall, scoring 59.2 to 54.8 on the Noometry Index. Muse Spark 1.3 costs 2.3× less per token, which makes it the better buy when GPT-5.6 Terra's lead doesn't matter for your workload.
Which is cheaper, GPT-5.6 Terra 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-5.6 Terra lists at $2 and $12.
Is GPT-5.6 Terra or Muse Spark 1.3 better for coding?
GPT-5.6 Terra scores higher on coding benchmarks: 57.7 versus 56.6 in the Noometry coding category.
Which has the bigger context window?
GPT-5.6 Terra does, with 1.05M tokens against 1.05M.
How many benchmarks do GPT-5.6 Terra and Muse Spark 1.3 share?
36 benchmarks have published results for both models. GPT-5.6 Terra has 52 scored results on Noometry and Muse Spark 1.3 has 37.