GPT-5.6 Terra vs Muse Spark
Full profiles: GPT-5.6 Terra (OpenAI) and Muse Spark (Meta): every benchmark, price and rank.
Updated · Data from 10 sources
As of 25 Oct 2026, GPT-5.6 Terra (max) and Muse Spark are neck and neck on quality (64.4 vs 64.3, inside the ±5.9 margin of error) and close on price, so pick on the category that matters to you. Pick GPT-5.6 Terra for maths (69 vs 59); pick Muse Spark for instruction following (77 vs 70).
GPT-5.6 Terra benchmarks 
Muse Spark benchmarks Which to pick for…
The pick's numbers come first. Category scores on the BenchLeader scale (50 is the average model, 15 points one standard deviation). High confidence means a lead of half a standard deviation or more; under one point is called either.
| Use case | Pick | Why | Confidence |
|---|---|---|---|
| Coding | Either | 65 vs 65 category score; SciCode 55.0% vs 51.5% | Either |
| Agents & tool use | Muse Spark | 66 vs 59 category score; Terminal-Bench Hard 45.5% vs 57.6% | Medium |
| Maths | GPT-5.6 Terra | 69 vs 59 category score; OTIS Mock AIME 99.7% vs 88.9% | High |
| Reasoning | GPT-5.6 Terra | 70 vs 65 category score; GPQA Diamond 93.3% vs 89.8% | Medium |
| Knowledge | Muse Spark | 63 vs 57 category score; AA-Omniscience 7.2 vs 0.1 | Medium |
| Long documents | GPT-5.6 Terra | 67 vs 64 category score; AA-LCR 83.0% vs 78.0% | Medium |
| Images and other media | Either | 64 vs 65 category score; MMMU-Pro 80.7% vs 80.5% | Either |
| Following instructions | Muse Spark | 77 vs 70 category score; IFBench 75.9% vs 71.2% | Medium |
| Chat quality (human preference) | – | Only Muse Spark has an Arena rating (68 category score) | Not comparable |
| High volume on a budget | Neither flagship | A smaller model is usually the better fit: Cheapest good LLMs, Fastest LLMs | – |
Key differences
- GPT-5.6 Terra (max) and Muse Spark are neck and neck on quality (64.4 vs 64.3, within the ±5.9 margin).
- GPT-5.6 Terra (max) is stronger in coding, composite, long context, maths, reasoning.
- Muse Spark is stronger in agents & tools, instruction following, knowledge, multimodal, human preference.
At a glance
| Spec | GPT-5.6 Terra | Muse Spark |
|---|---|---|
| Developer | OpenAI | Meta |
| Released | 9 Jul 2026 | 8 Apr 2026 |
| Context window (tokens) | 1,050,000 | 262,144 |
| Compared at | GPT-5.6 Terra (max) | Muse Spark |
| Open weights | No | No |
| Price in / out / cached input per 1M | $2.00 / $12.00 / $0.200 | – |
Category by category
Category scores on the BenchLeader scale: 50 is the average evaluated model, 15 points is one standard deviation. A gap under one point is called level.
| Category | GPT-5.6 Terra (max) | Muse Spark | Leader |
|---|---|---|---|
| Reasoning | 70.1 | 65.3 | GPT-5.6 Terra |
| Coding | 65.1 | 65.0 | level |
| Agents & tools | 58.9 | 66.1 | Muse Spark |
| Maths | 68.9 | 59.1 | GPT-5.6 Terra |
| Knowledge | 57.2 | 63.3 | Muse Spark |
| Instruction following | 69.9 | 77.3 | Muse Spark |
| Human preference | – | 68.3 | not comparable |
| Multimodal | 63.7 | 64.5 | level |
| Long context | 66.6 | 64.0 | GPT-5.6 Terra |
| Composite | 76.6 | 64.5 | GPT-5.6 Terra |
Where sources disagree
Across the 19 benchmarks both have, GPT-5.6 Terra leads 13, Muse Spark leads 6. Independent sources split: GPT-5.6 Terra leads on AA Intelligence Index v4.3.2; Muse Spark leads on Arena Text.
| Overall index | GPT-5.6 Terra (max) | Muse Spark | Leader |
|---|---|---|---|
| BenchLeader Index | 64.4 | 64.3 | neck and neck |
| AA Intelligence Index v4.3.2 | 42.1 | 31.3 | GPT-5.6 Terra |
| Arena Text | 1467† | 1489 | Muse Spark |
Each publisher runs its own tasks, harnesses and effort settings, so their overall verdicts can differ; BenchLeader reconciles them on one scale. † measured at another effort setting of the same model (the publisher did not test the one compared here).
Price, speed and latency
List prices blended at three input tokens per output token. Per-task prices use the token counts on the methodology page; suite cost is what Artificial Analysis paid to run its whole Intelligence Index.
| Measure | GPT-5.6 Terra (max) | Muse Spark |
|---|---|---|
| Blended price per 1M tokens | $4.50 | – |
| Input / output per 1M | $2.00 / $12.00 | – / – |
| Cached input per 1M | $0.200 | – |
| Price per task: chat reply | $0.0044 | – |
| Price per task: summarize a 30-page report | $0.031 | – |
| Price per task: code edit | $0.030 | – |
| Price per task: agentic coding session | $0.168 | – |
| Price per task: structured extraction | $0.0064 | – |
| Cost to run a full benchmark suite | $1.40 | – |
| Output speed | 126 tok/s | – |
| Time to first answer | 101.0 s | – |
| Time to a complete answer | 105.0 s | – |
Each model is compared at its best-ranked reasoning-effort setting. GPT-5.6 Terra (max) scores 64.4 and takes 101 s to its first answer token; GPT-5.6 Terra (xhigh) scores 62.8 in 7 s, GPT-5.6 Terra (high) scores 61.3 in 2 s. Muse Spark scores 64.3. Higher effort means more thinking before the answer: better scores, longer waits and more tokens billed. How reasoning effort changes scores and cost.
Every benchmark
130 benchmarks, grouped by category; each name links to the board and its leaders. † measured at another effort setting of the same model, shown for reference and not counted as a win.
| Metric | Publisher | GPT-5.6 Terra (max) | Muse Spark |
|---|---|---|---|
| BenchLeader Index | BenchLeader | 64.4 | 64.3 |
| Agents & tools score | BenchLeader | 58.9 | 66.1 |
| Coding score | BenchLeader | 65.1 | 65.0 |
| Composite score | BenchLeader | 76.6 | 64.5 |
| Instruction following score | BenchLeader | 69.9 | 77.3 |
| Knowledge score | BenchLeader | 57.2 | 63.3 |
| Long context score | BenchLeader | 66.6 | 64.0 |
| Maths score | BenchLeader | 68.9 | 59.1 |
| Multimodal score | BenchLeader | 63.7 | 64.5 |
| Reasoning score | BenchLeader | 70.1 | 65.3 |
| Human preference score | BenchLeader | – | 68.3 |
| Blended price $/M | BenchLeader | $4.50 | – |
| Output speed | BenchLeader | 126 tok/s | – |
| Time to first answer | BenchLeader | 101.0 s | – |
| Context window | BenchLeader | 1,050,000 tokens | 262,144 tokens |
| Reasoning | |||
| GPQA Diamond | Epoch AI Benchmarking Hub | 93.3% | 89.8% |
| Humanity's Last Exam | Scale AI / CAIS | – | 40.6% |
| SimpleBench | SimpleBench | 48.9%† | – |
| Arena Hard Prompts | Arena (LMArena) | 1490† | 1506 |
| LiveBench 2.0 Reasoning | LiveBench | 90.6%† | – |
| LiveBench 1.0 Reasoning | LiveBench | 90.6% | – |
| GPQA Diamond (AA) | Artificial Analysis | 92.5% | 88.4% |
| Humanity's Last Exam (AA) | Artificial Analysis | 42.9% | 40.7% |
| GPQA Diamond (Vals) | Vals AI | 90.9%† | 89.7% |
| Kagi LLM Benchmark | Kagi LLM Benchmark | 51.3%† | – |
| ARC-AGI-1 | ARC Prize | 96.5% | – |
| ARC-AGI-2 | ARC Prize | 83.9% | – |
| ARC-AGI-3 | ARC Prize | 0.8% | – |
| CritPt | Artificial Analysis | 30.0% | 11.3% |
| Chess Puzzles | Epoch AI Benchmarking Hub | 47.0% | – |
| Mystery Game Puzzles | Epoch AI Benchmarking Hub | 35.0% | – |
| LMCA | Epoch AI Benchmarking Hub | 55.0% | – |
| DTBench | Epoch AI Benchmarking Hub | 93.3% | – |
| Coding | |||
| SciCode | SciCode | 55.0% | 51.5% |
| WeirdML | WeirdML | 78.3%† | – |
| FrontierCode | Cognition | 41.3%† | – |
| Arena Coding | Arena (LMArena) | 1518† | 1529 |
| Arena WebDev | Arena (LMArena) | 1521† | – |
| LiveBench 2.0 Coding | LiveBench | 86.2%† | – |
| LiveBench 1.0 Coding | LiveBench | 78.3% | – |
Show all 130 benchmarks
| Metric | Publisher | GPT-5.6 Terra (max) | Muse Spark |
|---|---|---|---|
| Coding | |||
| SciCode (AA) | Artificial Analysis | 55.0% | – |
| LiveCodeBench | Vals AI | 85.9%† | – |
| IOI | Vals AI | 87.6% | – |
| SWE-bench (Vals) | Vals AI | 95.4% | 74.4% |
| SWE-Bench Pro | Scale AI SEAL | – | 55.0% |
| Code Migration | Vals AI | 47.8% | – |
| ProgramBench | Vals AI | 0.5% | – |
| Vibe Code Bench 1-100 | Vals AI | 14.8% | – |
| Vibe Code Bench v1.1 | Vals AI | 74.6% | 19.7% |
| SWE-Bench Pro (private) | Scale AI SEAL | – | 55.0% |
| SWE Atlas: Codebase QnA | Scale AI SEAL | – | 24.2% |
| SWE Atlas: Test Writing | Scale AI SEAL | – | 31.1% |
| Surface Evolver Bench | Epoch AI Benchmarking Hub | 83.8%† | – |
| DeepSWE v1.1 | Epoch AI Benchmarking Hub | 69.6% | – |
| CursorBench | Cursor | 41.3% | – |
| ALE-Bench | Epoch AI Benchmarking Hub | 1951.4 | – |
| Terminal-Bench 4.0 (AA) | Artificial Analysis | 35.4% | – |
| Terminal-Bench 2.1 (AA) | Artificial Analysis | 88.0% | 62.2% |
| Startrise Frontend | Startrise | 66.9%† | – |
| Agents & tools | |||
| Terminal-Bench | Terminal-Bench | 21.5% | – |
| APEX-Agents | Mercor | 58.2% | – |
| Arena Agent | Arena (LMArena) | 0.2† | – |
| LiveBench Long Agentic | LiveBench | 48.4%† | – |
| LiveBench Browser | LiveBench | 84.0%† | – |
| LiveBench Agentic Coding | LiveBench | 55.0% | – |
| Terminal-Bench Hard | Artificial Analysis | 57.6% | 45.5% |
| τ²-Bench Telecom (AA) | Artificial Analysis | 86.3% | 91.5% |
| Terminal-Bench 2.1 (Vals) | Vals AI | 77.5% | – |
| MCP Atlas | Scale AI SEAL | – | 82.2% |
| GDPval-AA v2.1 | Artificial Analysis | 47.6% | – |
| τ³-Banking (AA) | Artificial Analysis | 40.2% | – |
| ITBench SRE (AA) | Artificial Analysis | 51.0% | – |
| APEX-Agents (AA) | Artificial Analysis | 38.9% | – |
| CyberBench | Vals AI | 72.1% | – |
| Finance Agent v2 | Vals AI | 54.4% | – |
| Harvey's Legal Agent Benchmark v1 | Vals AI | 0.8% | – |
| Legal Research Bench | Vals AI | 41.4% | – |
| SkillsBench | Vals AI | 58.9% | – |
| SREBench | Vals AI | 9.5% | – |
| Tax Agent Bench | Vals AI | 30.0% | – |
| Terminal-Bench 2.0 (Vals) | Vals AI | – | 59.5% |
| Terminal-Bench 4.0 (Vals) | Vals AI | 22.7% | – |
| Terminal-Bench Science | Vals AI | 10.0% | – |
| BALROG | BALROG | 53.2% | – |
| Vending-Bench 2 | Andon Labs | 7343.2† | – |
| AutomationBench | Artificial Analysis | 59.6% | – |
| GDP.pdf (AA) | Artificial Analysis | 24.0% | – |
| EnterpriseOps-Gym | Artificial Analysis | 38.5% | – |
| Terminal-Bench-Science 0.1 (AA) | Artificial Analysis | 13.8% | – |
| FACTS Search | 81.7%† | – | |
| Maths | |||
| FrontierMath Tiers 1–3 | Epoch AI Benchmarking Hub | 86.0% | – |
| FrontierMath Tier 4 | Epoch AI Benchmarking Hub | 70.7% | – |
| OTIS Mock AIME | Epoch AI Benchmarking Hub | 99.7% | 88.9% |
| ProofBench | Vals AI | 74.0%† | 17.0% |
| LiveBench Mathematics | LiveBench | 94.9% | – |
| AIME (Vals) | Vals AI | – | 96.9% |
| Arena Maths | Arena (LMArena) | 1483† | 1467 |
| Knowledge | |||
| SimpleQA Verified | Epoch AI Benchmarking Hub | 43.2% | – |
| LiveBench 2.0 Data Analysis | LiveBench | 79.3%† | – |
| LiveBench Research | LiveBench | 60.4%† | – |
| LiveBench 1.0 Data Analysis | LiveBench | 79.3% | – |
| AA-Omniscience | Artificial Analysis | 0.1 | 7.2 |
| MMLU-Pro | Vals AI | 86.7%† | 87.3% |
| LegalBench | Vals AI | 85.1% | 84.2% |
| CorpFin | Vals AI | 65.3%† | 65.1% |
| TaxEval | Vals AI | 76.2%† | 77.7% |
| PRBench Finance | Scale AI SEAL | – | 52.4% |
| PRBench Legal | Scale AI SEAL | – | 52.3% |
| MultiNRC | Scale AI SEAL | – | 59.0% |
| CaseLaw v2 | Vals AI | – | 63.1% |
| Excel Modeling Benchmark | Vals AI | 66.2% | – |
| MedCode | Vals AI | 43.4%† | 51.3% |
| MedScribe | Vals AI | 82.9%† | 85.9% |
| Public Benefits Bench v1.1 | Vals AI | 62.4% | – |
| GDP.pdf | Epoch AI Benchmarking Hub | 24.7%† | – |
| AA-Omniscience: accuracy | Artificial Analysis | 46.8% | 49.6% |
| AA-Omniscience: non-hallucination | Artificial Analysis | 12.1% | 15.8% |
| Instruction following | |||
| LiveBench Language | LiveBench | 82.9% | – |
| LiveBench Instruction Following | LiveBench | 64.6% | – |
| IFBench | Artificial Analysis | 71.2% | 75.9% |
| MultiChallenge | Scale AI SEAL | – | 75.5% |
| TutorBench | Scale AI SEAL | – | 68.5% |
| Arena Instruction Following | Arena (LMArena) | 1464† | 1465 |
| Human preference | |||
| Arena Text | Arena (LMArena) | 1467† | 1489 |
| EQ-Bench 4 | EQ-Bench | 1224† | – |
| Arena Creative Writing | Arena (LMArena) | 1429† | 1464 |
| Arena Multi-turn | Arena (LMArena) | 1472† | 1494 |
| Arena Longer Queries | Arena (LMArena) | 1468† | 1476 |
| Multimodal | |||
| Arena Vision | Arena (LMArena) | 1271† | 1306 |
| LiveBench Design | LiveBench | 76.0%† | – |
| MMMU-Pro | Artificial Analysis | 80.7% | 80.5% |
| MMMU-Pro (official) | MMMU | – | 80.4%† |
| MMMU-Pro (Vals) | Vals AI | 86.5% | 87.4% |
| MortgageTax | Vals AI | 67.3%† | – |
| SAGE | Vals AI | 47.0% | – |
| Blueprint-Bench 2 | Epoch AI Benchmarking Hub | 30.8%† | – |
| Long context | |||
| AA-LCR | Artificial Analysis | 83.0% | 78.0% |
| Arena Document | Arena (LMArena) | 1477† | 1467 |
| MLCR | Artificial Analysis | 27.2% | – |
| Composite | |||
| Epoch Capabilities Index | Epoch AI Benchmarking Hub | 160.1† | 152.0 |
| LiveBench 2.0 | LiveBench | 75.0%† | – |
| LiveBench 1.0 | LiveBench | 77.9% | – |
| AA Intelligence Index v4.3.2 | Artificial Analysis | 42.1 | 31.3 |
| Vals Multimodal Index | Vals AI | 65.1%† | – |
| Safety & honesty | |||
| FORTRESS | Scale AI SEAL | – | 20.2% |
Data as of 2026-10-25. Best configuration of each model; every score links to its source on the model pages.
What changed
- GPT-5.6 Terra (max): 1 new result (Harvey's Legal Agent Benchmark v1).
- GPT-5.6 Terra (max): 1 score revision.
- GPT-5.6 Terra (max): BenchLeader Index 63.8 → 64.4.
- GPT-5.6 Terra (max): 5 new results (AutomationBench, GDP.pdf (AA), MLCR…).
- GPT-5.6 Terra (max): 1 new result (SREBench); 1 score revision.
- GPT-5.6 Terra (max): 1 score revision.
- Muse Spark: 1 new result (PRBench Legal).
- Muse Spark: 1 new result (SWE Atlas: Codebase QnA).
- Muse Spark: 2 new results (PRBench Legal, MultiNRC).
- Muse Spark: 1 new result (PRBench Finance).
Related comparisons
- GPT-5.6 Terra vs Claude Opus 5.5
- GPT-5.6 Terra vs Gemini 4 Argon
- GPT-5.6 Terra vs Muse Wonder Full
- Muse Spark vs Claude Opus 5.5
- Muse Spark vs Gemini 4 Argon
- Muse Spark vs Muse Wonder Full
- Muse Spark vs Claude Fable 5.1
- GPT-5.5 vs Muse Spark
Rankings: Best LLM overall · Best LLM for agents · Best cheap LLMs
GPT-5.6 Terra vs Muse Spark: questions
- Is GPT-5.6 Terra better than Muse Spark?
- GPT-5.6 Terra (max) and Muse Spark are neck and neck on quality (64.4 vs 64.3, within the ±5.9 margin). The BenchLeader Index combines every independent quality benchmark; the two are within the margin of error as of 2026-10-25, so check the category scores for your use.
- Is GPT-5.6 Terra better than Muse Spark for coding?
- They are level in coding (65 vs 65 on the category index). On SciCode, the top shared coding benchmark, it is 55.0% for GPT-5.6 Terra against 51.5% for Muse Spark.
- Is GPT-5.6 Terra better than Muse Spark for agents and tool use?
- Muse Spark scores higher in agentic tasks (66 vs 59 on the category index, where 50 is average). On Terminal-Bench Hard, the top shared agents & tools benchmark, it is 57.6% for GPT-5.6 Terra against 45.5% for Muse Spark.
- Which is better for long documents?
- GPT-5.6 Terra scores higher on long-context benchmarks (67 vs 64). GPT-5.6 Terra accepts more context: 1,050,000 against 262,144 tokens for Muse Spark.
- Do independent benchmarks agree on GPT-5.6 Terra vs Muse Spark?
- Across the 19 benchmarks both have, GPT-5.6 Terra leads 13, Muse Spark leads 6. Independent sources split: GPT-5.6 Terra leads on AA Intelligence Index v4.3.2; Muse Spark leads on Arena Text.
- When was GPT-5.6 Terra released?
- GPT-5.6 Terra was released on 9 Jul 2026.