GPT-6.1 Terra vs Muse Spark
Full profiles: GPT-6.1 Terra (OpenAI) and Muse Spark (Meta): every benchmark, price and rank.
Updated · Data from 7 sources
As of 27 Oct 2026, GPT-6.1 Terra (max) and Muse Spark are neck and neck on quality (65.9 vs 64.1, inside the ±7.7 margin of error) and close on price, so pick on the category that matters to you. GPT-6.1 Terra leads in every category we measure both in.
GPT-6.1 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 |
|---|---|---|---|
| Reasoning | GPT-6.1 Terra | 86 vs 65 category score; CritPt 28.0% vs 11.3% | High |
| Knowledge | GPT-6.1 Terra | 75 vs 63 category score; AA-Omniscience 29.8 vs 7.2 | High |
| Long documents | GPT-6.1 Terra | 66 vs 64 category score; AA-LCR 82.7% vs 78.0% | Medium |
| Images and other media | GPT-6.1 Terra | 68 vs 64 category score; MMMU-Pro 84.7% vs 80.5% | 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-6.1 Terra (max) and Muse Spark are neck and neck on quality (65.9 vs 64.1, within the ±7.7 margin).
- GPT-6.1 Terra (max) is stronger in composite, knowledge, long context, multimodal, reasoning.
- Muse Spark is stronger in agents & tools, coding, human preference, instruction following, maths.
At a glance
| Spec | GPT-6.1 Terra | Muse Spark |
|---|---|---|
| Developer | OpenAI | Meta |
| Released | 26 Oct 2026 | 8 Apr 2026 |
| Context window (tokens) | 1,050,000 | 262,144 |
| Compared at | GPT-6.1 Terra (max) | Muse Spark |
| Open weights | No | No |
| Price in / out / cached input per 1M | $1.00 / $5.00 / $0.050 | – |
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-6.1 Terra (max) | Muse Spark | Leader |
|---|---|---|---|
| Reasoning | 86.2 | 65.2 | GPT-6.1 Terra |
| Coding | – | 65.0 | not comparable |
| Agents & tools | – | 66.1 | not comparable |
| Maths | – | 59.1 | not comparable |
| Knowledge | 74.5 | 63.2 | GPT-6.1 Terra |
| Instruction following | – | 76.9 | not comparable |
| Human preference | – | 68.3 | not comparable |
| Multimodal | 67.5 | 64.3 | GPT-6.1 Terra |
| Long context | 66.3 | 63.9 | GPT-6.1 Terra |
| Composite | 82.8 | 64.1 | GPT-6.1 Terra |
Where sources disagree
Across the 7 benchmarks both have, GPT-6.1 Terra leads 6, Muse Spark leads 1. Every overall index that rates both puts GPT-6.1 Terra ahead.
| Overall index | GPT-6.1 Terra (max) | Muse Spark | Leader |
|---|---|---|---|
| BenchLeader Index | 65.9 | 64.1 | neck and neck |
| AA Intelligence Index v4.3.2 | 48.1 | 31.3 | GPT-6.1 Terra |
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-6.1 Terra (max) | Muse Spark |
|---|---|---|
| Blended price per 1M tokens | $2.00 | – |
| Input / output per 1M | $1.00 / $5.00 | – / – |
| Cached input per 1M | $0.050 | – |
| Price per task: chat reply | $0.0019 | – |
| Price per task: summarize a 30-page report | $0.015 | – |
| Price per task: code edit | $0.013 | – |
| Price per task: agentic coding session | $0.080 | – |
| Price per task: structured extraction | $0.0030 | – |
| Cost to run a full benchmark suite | $0.403 | – |
| Output speed | 91 tok/s | – |
| Time to first answer | 131.8 s | – |
| Time to a complete answer | 137.3 s | – |
Each model is compared at its best-ranked reasoning-effort setting. GPT-6.1 Terra (max) scores 65.9 and takes 132 s to its first answer token; GPT-6.1 Terra (xhigh) scores 65.0 in 18 s, GPT-6.1 Terra (high) scores 64.7 in 7 s. Muse Spark scores 64.1. 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
69 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-6.1 Terra (max) | Muse Spark |
|---|---|---|---|
| BenchLeader Index | BenchLeader | 65.9 | 64.1 |
| Composite score | BenchLeader | 82.8 | 64.1 |
| Knowledge score | BenchLeader | 74.5 | 63.2 |
| Long context score | BenchLeader | 66.3 | 63.9 |
| Multimodal score | BenchLeader | 67.5 | 64.3 |
| Reasoning score | BenchLeader | 86.2 | 65.2 |
| Agents & tools score | BenchLeader | – | 66.1 |
| Coding score | BenchLeader | – | 65.0 |
| Human preference score | BenchLeader | – | 68.3 |
| Instruction following score | BenchLeader | – | 76.9 |
| Maths score | BenchLeader | – | 59.1 |
| Blended price $/M | BenchLeader | $2.00 | – |
| Output speed | BenchLeader | 91 tok/s | – |
| Time to first answer | BenchLeader | 131.8 s | – |
| Context window | BenchLeader | 1,050,000 tokens | 262,144 tokens |
| Reasoning | |||
| GPQA Diamond | Epoch AI Benchmarking Hub | – | 89.8% |
| Humanity's Last Exam | Scale AI / CAIS | – | 40.6% |
| Arena Hard Prompts | Arena (LMArena) | – | 1506 |
| LiveBench 2.0 Reasoning | LiveBench | 88.7%† | – |
| GPQA Diamond (AA) | Artificial Analysis | – | 88.4% |
| Humanity's Last Exam (AA) | Artificial Analysis | 46.3% | 40.7% |
| GPQA Diamond (Vals) | Vals AI | – | 89.7% |
| CritPt | Artificial Analysis | 28.0% | 11.3% |
| Coding | |||
| SciCode | SciCode | – | 51.5% |
| Arena Coding | Arena (LMArena) | – | 1529 |
| LiveBench 2.0 Coding | LiveBench | 90.8%† | – |
| SciCode (AA) | Artificial Analysis | 55.1% | – |
| SWE-bench (Vals) | Vals AI | – | 74.4% |
| SWE-Bench Pro | Scale AI SEAL | – | 55.0% |
| Vibe Code Bench v1.1 | Vals AI | – | 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% |
| Terminal-Bench 4.0 (AA) | Artificial Analysis | 55.6% | – |
| Terminal-Bench 2.1 (AA) | Artificial Analysis | – | 62.2% |
| FrontierCode 1.1 (AA) | Artificial Analysis | 36.0% | – |
| Agents & tools | |||
| LiveBench Long Agentic | LiveBench | 48.6%† | – |
| LiveBench Browser | LiveBench | 93.1%† | – |
| Terminal-Bench Hard | Artificial Analysis | – | 45.5% |
| τ²-Bench Telecom (AA) | Artificial Analysis | – | 91.5% |
Show all 69 benchmarks
| Metric | Publisher | GPT-6.1 Terra (max) | Muse Spark |
|---|---|---|---|
| Agents & tools | |||
| MCP Atlas | Scale AI SEAL | – | 82.2% |
| Terminal-Bench 2.0 (Vals) | Vals AI | – | 59.5% |
| AutomationBench | Artificial Analysis | 60.2% | – |
| GDP.pdf (AA) | Artificial Analysis | 28.6% | – |
| AA-Briefcase v1.1 | Artificial Analysis | 1402 | – |
| Terminal-Bench-Science 0.1 (AA) | Artificial Analysis | 57.6% | – |
| Maths | |||
| OTIS Mock AIME | Epoch AI Benchmarking Hub | – | 88.9% |
| ProofBench | Vals AI | – | 17.0% |
| AIME (Vals) | Vals AI | – | 96.9% |
| Arena Maths | Arena (LMArena) | – | 1467 |
| Knowledge | |||
| LiveBench 2.0 Data Analysis | LiveBench | 82.3%† | – |
| LiveBench Research | LiveBench | 73.9%† | – |
| AA-Omniscience | Artificial Analysis | 29.8 | 7.2 |
| MMLU-Pro | Vals AI | – | 87.3% |
| LegalBench | Vals AI | – | 84.2% |
| CorpFin | Vals AI | – | 65.1% |
| TaxEval | Vals AI | – | 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% |
| MedCode | Vals AI | – | 51.3% |
| MedScribe | Vals AI | – | 85.9% |
| AA-Omniscience: accuracy | Artificial Analysis | 49.1% | 49.6% |
| AA-Omniscience: non-hallucination | Artificial Analysis | 62.0% | 15.8% |
| Instruction following | |||
| IFBench | Artificial Analysis | – | 75.9% |
| MultiChallenge | Scale AI SEAL | – | 75.5% |
| TutorBench | Scale AI SEAL | – | 68.5% |
| Arena Instruction Following | Arena (LMArena) | – | 1465 |
| Human preference | |||
| Arena Text | Arena (LMArena) | – | 1489 |
| Arena Creative Writing | Arena (LMArena) | – | 1464 |
| Arena Multi-turn | Arena (LMArena) | – | 1494 |
| Arena Longer Queries | Arena (LMArena) | – | 1476 |
| Multimodal | |||
| Arena Vision | Arena (LMArena) | – | 1306 |
| LiveBench Design | LiveBench | 82.3%† | – |
| MMMU-Pro | Artificial Analysis | 84.7% | 80.5% |
| MMMU-Pro (official) | MMMU | – | 80.4%† |
| MMMU-Pro (Vals) | Vals AI | – | 87.4% |
| Long context | |||
| AA-LCR | Artificial Analysis | 82.7% | 78.0% |
| Arena Document | Arena (LMArena) | – | 1467 |
| Composite | |||
| Epoch Capabilities Index | Epoch AI Benchmarking Hub | – | 152.0 |
| LiveBench 2.0 | LiveBench | 77.2%† | – |
| AA Intelligence Index v4.3.2 | Artificial Analysis | 48.1 | 31.3 |
| Safety & honesty | |||
| FORTRESS | Scale AI SEAL | 18.2%† | 20.2% |
Data as of 2026-10-27. Best configuration of each model; every score links to its source on the model pages.
What changed
- 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).
- Muse Spark: 1 new result (PRBench Finance).
- Muse Spark: 1 new result (TutorBench); 1 score revision.
- Muse Spark: BenchLeader Index 64.9 → 64.4.
- Muse Spark: 1 new result (PRBench Finance).
- Muse Spark: 1 new result (MultiChallenge).
- Muse Spark: 3 new results (PRBench Finance, MultiNRC, SWE Atlas: Test Writing).
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- Muse Spark vs Claude Fable 5.1
- Muse Spark vs GPT-6 Astra
- Muse Spark vs Muse Wonder Full
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Rankings: Best LLM overall · Best LLM for agents · Best cheap LLMs
GPT-6.1 Terra vs Muse Spark: questions
- Is GPT-6.1 Terra better than Muse Spark?
- GPT-6.1 Terra (max) and Muse Spark are neck and neck on quality (65.9 vs 64.1, within the ±7.7 margin). The BenchLeader Index combines every independent quality benchmark; the two are within the margin of error as of 2026-10-27, so check the category scores for your use.
- Which is better for long documents?
- GPT-6.1 Terra scores higher on long-context benchmarks (66 vs 64). GPT-6.1 Terra accepts more context: 1,050,000 against 262,144 tokens for Muse Spark.
- Do independent benchmarks agree on GPT-6.1 Terra vs Muse Spark?
- Across the 7 benchmarks both have, GPT-6.1 Terra leads 6, Muse Spark leads 1. Every overall index that rates both puts GPT-6.1 Terra ahead.
- When was GPT-6.1 Terra released?
- GPT-6.1 Terra was released on 26 Oct 2026.