GPT-5.6 Terra vs Muse Spark 1.2
GPT-5.6 Terra leads Muse Spark 1.2 on coding, 63.9 to 55.7 on the Vibe Coding Index, and Muse Spark 1.2 costs 2.8x less per output token ($4.25 vs $12.00 per million). Updated October 22, 2026; 95 benchmarks have a result for both.
GPT-5.6 Terra or Muse Spark 1.2: which to pick
Pick GPT-5.6 Terra for coding: it scores 63.9 on the Vibe Coding Index against 55.7 for Muse Spark 1.2.
Pick Muse Spark 1.2 for output tokens 2.8x cheaper ($4.25 vs $12.00 per million) and work measured by LMArena WebDev or Vibe Code Bench (Vals AI), where it leads.
- Shared results
- 95
- GPT-5.6 Terra only
- 34
- Muse Spark 1.2 only
- 2
- Like-for-like categories
- 8 of 9
Only benchmarks that tested both models count toward a pick; a result only one model has is shown but not compared.
Which one for your work
Each card is decided by one number both models carry. Where only one has it, the card says so and makes no call.
Coding
Vibe Coding Index, six public coding benchmarks
GPT-5.6 Terra
GPT-5.6 Terra scores 63.9 against 55.7.
6 and 5 benchmarks behind the scores
Intelligence
AA Intelligence Index
GPT-5.6 Terra
GPT-5.6 Terra leads, 42.1 against 39.6.
Same board, both measured
Agentic work
AA Agentic Index
No call
Tied at 43.2.
Same board, both measured
Reasoning
GPQA Diamond
No call
Only GPT-5.6 Terra has a GPQA Diamond result, 90.9%.
Directional only
Knowledge
MMLU Pro
Muse Spark 1.2
Muse Spark 1.2 leads, 88.3% against 86.7%.
Same board, both measured
Web design
Design Arena: websites
Muse Spark 1.2
Muse Spark 1.2 leads, 1312 against 1268.
Same board, both measured
Long documents
Listed context window
GPT-5.6 Terra
GPT-5.6 Terra takes 1.05M tokens against 1.05M.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Muse Spark 1.2
GPT-5.6 Terra $0.0080, Muse Spark 1.2 $0.0034 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
GPT-5.6 Terra
GPT-5.6 Terra $0.42, Muse Spark 1.2 $0.64.
Published attempt cost and pass rate
At a glance
- Coding index
- GPT-5.6 Terra 63.9 from 6 benchmarks, Muse Spark 1.2 55.7 from 5 benchmarks.
- Widest category
- Agentic work, 12.3 points apart on average over 17 shared benchmarks.
- Widest single gap
- IOI (Vals AI): GPT-5.6 Terra 87.6% against Muse Spark 1.2 21.8%, 65.8 points apart on a 0 to 100 scale.
- Output price
- GPT-5.6 Terra $12.00 against Muse Spark 1.2 $4.25 per million output tokens, 2.8x apart.
- Context window
- GPT-5.6 Terra takes 1.05M tokens, Muse Spark 1.2 1.05M.
Benchmark by benchmark
First the score: boards each model leads, per category, where both have a result. Then every board, a category to a fold; bars are each result on a 0 to 100 scale, so compare the two in a row, not one row with another.
| Category | GPT-5.6 Terra | Bars | Muse Spark 1.2 | Ties |
|---|---|---|---|---|
| Coding | 10 | 7 | 1 tie | |
| Intelligence | 2 | 0 | ||
| Agentic work | 5 | 11 | 1 tie | |
| Reasoning | 5 | 5 | ||
| Math | 1 | 2 | ||
| Knowledge | 1 | 10 | ||
| Web design | 1 | 8 | ||
| General | 4 | 21 | ||
| All shared boards | 29 | 64 | 2 ties |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index107
| Benchmark | GPT-5.6 Terra | Muse Spark 1.2 | Leader |
|---|---|---|---|
| LiveBench coding | 86.2% | 78.2% | GPT-5.6 Terra |
| LMArena WebDev | 1522 | 1534 | Muse Spark 1.2 |
| AA Coding Index | 76.7 | 72.2 | GPT-5.6 Terra |
| LiveCodeBench (Vals AI) | 85.9% | Not measured | Only GPT-5.6 Terra measured |
| SWE-bench Verified (Vals AI) | 95.4% | 86.6% | GPT-5.6 Terra |
| Terminal-Bench 4 (Vals AI) | 22.7% | 6.1% | GPT-5.6 Terra |
| Vibe Code Bench (Vals AI) | 74.6% | 79.1% | Muse Spark 1.2 |
| Code migration (Vals AI) | 47.8% | 29.9% | GPT-5.6 Terra |
| ProgramBench (Vals AI) | 0.5% | 0.5% | Tie |
| IOI (Vals AI) | 87.6% | 21.8% | GPT-5.6 Terra |
| Terminal-Bench 2.1 (Vals AI) | 77.5% | 69.7% | GPT-5.6 Terra |
| Vibe Code Bench 1-100 (Vals AI) | 14.8% | Not measured | Only GPT-5.6 Terra measured |
| SkillsBench (Vals AI) | 58.9% | 53.0% | GPT-5.6 Terra |
| CyberBench (Vals AI) | 72.1% | 69.5% | GPT-5.6 Terra |
| SciCode | 55.0% | 57.4% | Muse Spark 1.2 |
| Terminal-Bench Hard (Artificial Analysis run) | 62.9% | Not measured | Only GPT-5.6 Terra measured |
| FrontierCode | 41.3% | Not measured | Only GPT-5.6 Terra measured |
| FrontierSWE | Not measured | 12.0% | Only Muse Spark 1.2 measured |
| WeirdML | 78.3% | 60.3% | GPT-5.6 Terra |
| ALE-Bench | 1951.4 | Not measured | Only GPT-5.6 Terra measured |
| LMArena Text: coding | 1485 | 1505 | Muse Spark 1.2 |
| LMArena Text: software and IT | 1482 | 1505 | Muse Spark 1.2 |
| LMArena WebDev: React | 1513 | 1526 | Muse Spark 1.2 |
| LMArena WebDev: HTML | 1526 | 1543 | Muse Spark 1.2 |
| LMArena WebDev: from an image | 1541 | Not measured | Only GPT-5.6 Terra measured |
| SciCode | 10.8% | Not measured | Only GPT-5.6 Terra measured |
| SWE-Bench Pro V2 | 92.4% | Not measured | Only GPT-5.6 Terra measured |
| Neither model has a result on the other 16 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | GPT-5.6 Terra | Muse Spark 1.2 | Leader |
|---|---|---|---|
| AA Intelligence Index | 42.1 | 39.6 | GPT-5.6 Terra |
| Epoch Capabilities Index | 160.1 | 155.1 | GPT-5.6 Terra |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index511
| Benchmark | GPT-5.6 Terra | Muse Spark 1.2 | Leader |
|---|---|---|---|
| AA Agentic Index | 43.2 | 43.2 | Tie |
| Design Arena: agents building web apps | 1120 | 1221 | Muse Spark 1.2 |
| Design Arena: agents building full-stack apps | 1061 | 1210 | Muse Spark 1.2 |
| Design Arena: agents building mobile apps | 1110 | 1181 | Muse Spark 1.2 |
| Design Arena: agents building Android apps | 1060 | 1222 | Muse Spark 1.2 |
| Design Arena: agents building games | 1083 | 1178 | Muse Spark 1.2 |
| Design Arena: HTML slides | 1047 | 1074 | Muse Spark 1.2 |
| Design Arena: PowerPoint slides | 1104 | 1170 | Muse Spark 1.2 |
| LiveBench research | 60.4% | 67.7% | Muse Spark 1.2 |
| LiveBench browser | 84.0% | 36.0% | GPT-5.6 Terra |
| LiveBench long agentic | 48.4% | 21.3% | GPT-5.6 Terra |
| SREBench (Vals AI) | 9.5% | 0.0% | GPT-5.6 Terra |
| Finance Agent (Vals AI) | 54.4% | 60.6% | Muse Spark 1.2 |
| Tax Agent Bench (Vals AI) | 30.0% | 32.8% | Muse Spark 1.2 |
| Legal Research Bench (Vals AI) | 41.4% | 43.8% | Muse Spark 1.2 |
| Excel Modeling Benchmark (Vals AI) | 66.2% | 57.0% | GPT-5.6 Terra |
| BioMysteryBench (Vals AI) | Not measured | 64.8% | Only Muse Spark 1.2 measured |
| Terminal-Bench-Science (Vals AI) | 10.0% | Not measured | Only GPT-5.6 Terra measured |
| τ²-Bench Telecom | 86.3% | Not measured | Only GPT-5.6 Terra measured |
| APEX-Agents | 58.2% | 45.4% | GPT-5.6 Terra |
| BALROG | 53.2% | Not measured | Only GPT-5.6 Terra measured |
| Vending-Bench 2 | $7,343 | Not measured | Only GPT-5.6 Terra measured |
| Neither model has a result on the other 20 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index55
| Benchmark | GPT-5.6 Terra | Muse Spark 1.2 | Leader |
|---|---|---|---|
| GPQA Diamond | 90.9% | Not measured | Only GPT-5.6 Terra measured |
| LiveBench reasoning | 90.6% | 90.0% | GPT-5.6 Terra |
| MMMU Pro (Vals AI) | 86.5% | 86.1% | GPT-5.6 Terra |
| GPQA Diamond (Artificial Analysis run) | 92.5% | 90.4% | GPT-5.6 Terra |
| Humanity's Last Exam (Artificial Analysis run) | 42.9% | 45.5% | Muse Spark 1.2 |
| GPQA Diamond (Epoch AI run) | 93.3% | Not measured | Only GPT-5.6 Terra measured |
| ARC-AGI | 96.5% | Not measured | Only GPT-5.6 Terra measured |
| ARC-AGI-2 | 83.9% | Not measured | Only GPT-5.6 Terra measured |
| SimpleBench | 48.9% | 74.5% | Muse Spark 1.2 |
| Chess puzzles | 47.0% | 27.0% | GPT-5.6 Terra |
| Mystery game puzzles | 35.0% | Not measured | Only GPT-5.6 Terra measured |
| LMArena Text: hard prompts | 1469 | 1489 | Muse Spark 1.2 |
| LMArena Text: expert | 1496 | 1475 | GPT-5.6 Terra |
| LMArena Text: hard prompts in English | 1465 | 1487 | Muse Spark 1.2 |
| LMArena Vision: diagrams | 1295 | 1317 | Muse Spark 1.2 |
| LMArena Vision: homework | 1312 | Not measured | Only GPT-5.6 Terra measured |
| Kagi LLM Benchmark | 51.3% | Not measured | Only GPT-5.6 Terra measured |
| Neither model has a result on the other 6 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index12
| Benchmark | GPT-5.6 Terra | Muse Spark 1.2 | Leader |
|---|---|---|---|
| OTIS Mock AIME | 99.7% | Not measured | Only GPT-5.6 Terra measured |
| FrontierMath, tiers 1 to 3 | 86.0% | Not measured | Only GPT-5.6 Terra measured |
| FrontierMath, tier 4 | 70.7% | Not measured | Only GPT-5.6 Terra measured |
| ProofBench | 74.0% | 43.0% | GPT-5.6 Terra |
| LMArena Text: math | 1465 | 1484 | Muse Spark 1.2 |
| LMArena Text: mathematical work | 1478 | 1480 | Muse Spark 1.2 |
| Neither model has a result on the other 8 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index110
| Benchmark | GPT-5.6 Terra | Muse Spark 1.2 | Leader |
|---|---|---|---|
| MMLU Pro | 86.7% | 88.3% | Muse Spark 1.2 |
| LegalBench (Vals AI) | 85.1% | 85.3% | Muse Spark 1.2 |
| CorpFin (Vals AI) | 65.3% | 70.9% | Muse Spark 1.2 |
| TaxEval (Vals AI) | 76.2% | 80.4% | Muse Spark 1.2 |
| MortgageTax (Vals AI) | 67.3% | 65.4% | GPT-5.6 Terra |
| MedCode (Vals AI) | 43.4% | 49.4% | Muse Spark 1.2 |
| SimpleQA Verified | 43.2% | 60.3% | Muse Spark 1.2 |
| LMArena Text: science | 1452 | 1500 | Muse Spark 1.2 |
| LMArena Text: medicine and healthcare | 1430 | 1496 | Muse Spark 1.2 |
| LMArena Text: legal and government | 1461 | 1517 | Muse Spark 1.2 |
| LMArena Text: business and finance | 1448 | 1484 | Muse Spark 1.2 |
| FACTS Benchmark Suite | 52.0% | Not measured | Only GPT-5.6 Terra measured |
| Neither model has a result on the other 8 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index18
| Benchmark | GPT-5.6 Terra | Muse Spark 1.2 | Leader |
|---|---|---|---|
| Design Arena: websites | 1268 | 1312 | Muse Spark 1.2 |
| Design Arena: UI components | 1256 | 1299 | Muse Spark 1.2 |
| Design Arena: game dev | 1229 | 1300 | Muse Spark 1.2 |
| Design Arena: data viz | 1240 | 1334 | Muse Spark 1.2 |
| Design Arena: 3D | 1134 | 1300 | Muse Spark 1.2 |
| Design Arena: all code categories | 1240 | 1312 | Muse Spark 1.2 |
| Design Arena: SVG | 1219 | 1283 | Muse Spark 1.2 |
| Design Arena: ASCII art | 1178 | 1284 | Muse Spark 1.2 |
| LiveBench design | 76.0% | 67.1% | GPT-5.6 Terra |
GeneralLike-for-likePublic boards, shown as published, kept out of the index421
| Benchmark | GPT-5.6 Terra | Muse Spark 1.2 | Leader |
|---|---|---|---|
| LiveBench data analysis | 79.3% | 76.5% | GPT-5.6 Terra |
| Public Benefits Bench (Vals AI) | 62.4% | 68.5% | Muse Spark 1.2 |
| SAGE (Vals AI) | 47.0% | 47.7% | Muse Spark 1.2 |
| MedScribe (Vals AI) | 82.9% | 90.1% | Muse Spark 1.2 |
| Vals Multimodal Index | 65.1% | 69.8% | Muse Spark 1.2 |
| IFBench | 71.2% | Not measured | Only GPT-5.6 Terra measured |
| Long context reasoning (AA-LCR) | 83.0% | 79.0% | GPT-5.6 Terra |
| DTBench | 93.3% | 94.7% | Muse Spark 1.2 |
| LMCA | 54.9% | 48.4% | GPT-5.6 Terra |
| Surface Evolver Bench | 83.8% | Not measured | Only GPT-5.6 Terra measured |
| Furniture assembly | 54.2% | Not measured | Only GPT-5.6 Terra measured |
| LMArena Text | 1448 | 1482 | Muse Spark 1.2 |
| LMArena Text: instruction following | 1456 | 1462 | Muse Spark 1.2 |
| LMArena Text: creative writing | 1413 | 1436 | Muse Spark 1.2 |
| LMArena Vision | 1271 | 1304 | Muse Spark 1.2 |
| LMArena Text: English | 1449 | 1483 | Muse Spark 1.2 |
| LMArena Text: non-English | 1441 | 1476 | Muse Spark 1.2 |
| LMArena Text: Chinese | 1514 | 1509 | GPT-5.6 Terra |
| LMArena Text: German | 1460 | Not measured | Only GPT-5.6 Terra measured |
| LMArena Text: Japanese | 1454 | Not measured | Only GPT-5.6 Terra measured |
| LMArena Text: Korean | 1427 | 1462 | Muse Spark 1.2 |
| LMArena Text: French | 1466 | 1495 | Muse Spark 1.2 |
| LMArena Text: Spanish | 1451 | 1484 | Muse Spark 1.2 |
| LMArena Text: Russian | 1452 | 1483 | Muse Spark 1.2 |
| LMArena Text: Polish | 1446 | Not measured | Only GPT-5.6 Terra measured |
| LMArena Text: multi-turn | 1453 | 1502 | Muse Spark 1.2 |
| LMArena Text: longer queries | 1454 | 1473 | Muse Spark 1.2 |
| LMArena Text: writing and language | 1431 | 1453 | Muse Spark 1.2 |
| LMArena Text: entertainment and media | 1418 | 1443 | Muse Spark 1.2 |
| LMArena Vision: English | 1272 | 1291 | Muse Spark 1.2 |
| LMArena Vision: Chinese | 1337 | Not measured | Only GPT-5.6 Terra measured |
| LMArena Vision: reading text | 1278 | 1313 | Muse Spark 1.2 |
| LMArena Vision: humor | 1236 | Not measured | Only GPT-5.6 Terra measured |
| LMArena Vision: creative writing | 1248 | Not measured | Only GPT-5.6 Terra measured |
| LMArena Document | 1472 | Not measured | Only GPT-5.6 Terra measured |
| EQ-Bench 4 | 1234 | Not measured | Only GPT-5.6 Terra measured |
| Neither model has a result on the other 12 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-5.6 Terra | Muse Spark 1.2 | Leader |
|---|---|---|---|
| Neither model has a result on 5 boards here | |||
What each workload costs
Three fixed token mixes at each model's listed price, so per-token rates become a bill.
Chat turn
1K input + 500 output tokens
Muse Spark 1.2 costs less
Repository review
50K input + 3K output tokens
Muse Spark 1.2 costs less
Agent loop
200K input + 10K output tokens
Muse Spark 1.2 costs less
Listed OpenRouter rates, without cache or batch discounts. A workload that does not fit a model's context window would need splitting.
Specification differences
The leading value in a row is marked; a row with a missing value names no leader. Our two rows are marked in red.
| Specification | OpenAI GPT-5.6 Terra | Meta Muse Spark 1.2 |
|---|---|---|
| Maker | OpenAI | Meta |
| Weights | No public weights listed | No public weights listed |
| Released | July 9, 2026 | August 5, 2026 |
| Context window | 1.05M | 1.05M |
| Input $/Mtok | $2.00 | $1.25 |
| Output $/Mtok | $12.00 | $4.25 |
| Coding index | 63.9 | 55.7 |
| Independent measurements behind it | 6 | 5 |
| Cost per solved task | $0.42 | $0.64 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-5.6 Terra better than Muse Spark 1.2 for coding?
Pick GPT-5.6 Terra for coding: it scores 63.9 on the Vibe Coding Index against 55.7 for Muse Spark 1.2. Pick Muse Spark 1.2 for output tokens 2.8x cheaper ($4.25 vs $12.00 per million) and work measured by LMArena WebDev or Vibe Code Bench (Vals AI), where it leads.
Which is cheaper, GPT-5.6 Terra or Muse Spark 1.2?
GPT-5.6 Terra costs $2.00 per million input tokens and $12.00 per million output tokens; Muse Spark 1.2 costs $1.25 and $4.25. Per solved SWE-bench Verified task, GPT-5.6 Terra costs $0.42 and Muse Spark 1.2 $0.64.
Which has the bigger context window, GPT-5.6 Terra or Muse Spark 1.2?
GPT-5.6 Terra, with 1.05M tokens against 1.05M.
How many benchmarks is the GPT-5.6 Terra vs Muse Spark 1.2 comparison based on?
95 benchmarks have a result for both models as of October 22, 2026. GPT-5.6 Terra's coding index rests on 6 independent benchmarks and Muse Spark 1.2's on 5. Where only one model has a result, the page says so instead of naming a winner.