GPT-6 Sol vs Muse Spark 1.3
Full profiles: GPT-6 Sol (OpenAI) and Muse Spark 1.3 (Meta): every benchmark, price and rank.
Updated · Data from 11 sources
As of 9 Nov 2026, GPT-6 Sol and Muse Spark 1.3 are neck and neck on quality (62.9 vs 61.7 on the BenchLeader Index, inside the ±4.7 margin), and Muse Spark 1.3 is 2.0× cheaper at $2.00 vs $4.00 per 1M tokens blended. Choose GPT-6 Sol for reasoning (66 vs 60), coding (67 vs 61), and maths (69 vs 63); choose Muse Spark 1.3 for fast first answers (36.1 s vs 72.1 s) and agents & tools (66 vs 60), multimodal (66 vs 61), and human preference (69 vs 64).
Key facts (as of 9 Nov 2026)
- GPT-6 Sol scores 62.9 on the BenchLeader Index and Muse Spark 1.3 scores 61.7 (BenchLeader, 9 Nov 2026).
- GPT-6 Sol costs $4.00 per 1M tokens blended (list price, 9 Nov 2026).
- Muse Spark 1.3 costs $2.00 per 1M tokens blended (list price, 9 Nov 2026).
- Of the 51 benchmarks both models have, GPT-6 Sol leads 30 (BenchLeader, 9 Nov 2026).
- On Arena WebDev, GPT-6 Sol is rated 1674 and Muse Spark 1.3 1654 (LMArena, as published by 9 Nov 2026).
GPT-6 Sol benchmarks 
Muse Spark 1.3 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 | GPT-6 Sol | 67 vs 61 category score; Arena WebDev 1674 vs 1654 | Medium |
| Agents & tool use | Muse Spark 1.3 | 66 vs 60 category score; APEX-Agents 47.6% vs 54.3% | Medium |
| Maths | GPT-6 Sol | 69 vs 63 category score; FrontierMath Tiers 1–3 89.8% vs 74.0% | Medium |
| Reasoning | GPT-6 Sol | 66 vs 60 category score; HLE-Diamond (AA) 45.2% vs 33.7% | Medium |
| Knowledge | GPT-6 Sol | 62 vs 57 category score; AA-Omniscience v1.1 21.4 vs 22.4 | Medium |
| Long documents | Either | 67 vs 66 category score; AA-LCR v1.1 83.7% vs 83.0% | Either |
| Images and other media | Muse Spark 1.3 | 66 vs 61 category score; Arena Vision 1309 vs 1232 | Medium |
| Chat quality (human preference) | Muse Spark 1.3 | 69 vs 64 on Arena votes | Medium |
| Lowest cost | Muse Spark 1.3 | $2.00 vs $4.00 per 1M blended; agentic coding session $0.092 vs $0.160 | – |
| Fastest first answer | Muse Spark 1.3 | 36.1 s (Muse Spark 1.3 (max)) vs 72.1 s (GPT-6 Sol (max)) to the first answer token | – |
| High volume on a budget | Neither flagship | A smaller model is usually the better fit: Cheapest good LLMs, Fastest LLMs | – |
Key differences
- GPT-6 Sol (max) and Muse Spark 1.3 (max) are neck and neck on quality (62.9 vs 61.7, within the ±4.7 margin).
- GPT-6 Sol (max) is stronger in coding, knowledge, long context, maths, reasoning.
- Muse Spark 1.3 (max) is stronger in agents & tools, human preference, multimodal.
- Muse Spark 1.3 (max) is 2.0× cheaper ($2.00 vs $4.00 per 1M blended).
At a glance
| Spec | GPT-6 Sol | Muse Spark 1.3 |
|---|---|---|
| Developer | OpenAI | Meta |
| Released | 22 Sep 2026 | 2 Sep 2026 |
| Context window (tokens) | 1,050,000 | 1,048,576 |
| Compared at | GPT-6 Sol (max) | Muse Spark 1.3 (max) |
| Open weights | No | No |
| Price in / out / cached input per 1M | $2.00 / $10.00 / $0.200 | $1.25 / $4.25 / $0.150 |
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 Sol (max) | Muse Spark 1.3 (max) | Leader |
|---|---|---|---|
| Reasoning | 66.2 | 59.8 | GPT-6 Sol |
| Coding | 66.5 | 60.7 | GPT-6 Sol |
| Agents & tools | 59.6 | 65.5 | Muse Spark 1.3 |
| Maths | 68.5 | 63.1 | GPT-6 Sol |
| Knowledge | 61.5 | 57.2 | GPT-6 Sol |
| Human preference | 64.2 | 69.0 | Muse Spark 1.3 |
| Multimodal | 60.7 | 65.8 | Muse Spark 1.3 |
| Long context | 66.6 | 66.3 | level |
On one chart
Each domain on the index's own scale, where 50 is an average model. Click a domain to see the benchmarks behind it. Pick up to 5 models from the list.
Not drawn, measured for fewer than two of these models: Instruction following.
Where sources disagree
Across the 51 benchmarks both have, GPT-6 Sol leads 30, Muse Spark 1.3 leads 21. Independent sources split: GPT-6 Sol leads on AA Intelligence Index v5.0; Muse Spark 1.3 leads on Arena Text.
| Overall index | GPT-6 Sol (max) | Muse Spark 1.3 (max) | Leader |
|---|---|---|---|
| BenchLeader Index | 62.9 | 61.7 | neck and neck |
| AA Intelligence Index v5.0 | 44.2 | 36.6 | GPT-6 Sol |
| Arena Text | 1457 | 1496 | Muse Spark 1.3 |
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. Cost, tokens and time per benchmark task are measured: Artificial Analysis’ averages over its whole Intelligence Index run.
| Measure | GPT-6 Sol (max) | Muse Spark 1.3 (max) |
|---|---|---|
| Blended price per 1M tokens | $4.00 | $2.00 |
| Input / output per 1M | $2.00 / $10.00 | $1.25 / $4.25 |
| Cached input per 1M | $0.200 | $0.150 |
| Price per task: chat reply | $0.0038 | $0.0018 |
| Price per task: summarize a 30-page report | $0.030 | $0.018 |
| Price per task: code edit | $0.027 | $0.014 |
| Price per task: agentic coding session | $0.160 | $0.092 |
| Price per task: structured extraction | $0.0060 | $0.0034 |
| Agentic coding session, input mostly cached | $0.079 | $0.043 |
| Cost per benchmark task (AA Index) | $2.47 | $2.39 |
| Output tokens per task (AA Index) | 54k | 91k |
| Of which reasoning | 35k | 55k |
| Time per task (AA Index) | 7 min | 12 min |
| Output speed | 121 tok/s | 123 tok/s |
| Time to first answer | 72.1 s | 36.1 s |
| Time to a complete answer | 130.2 s | 88.3 s |
Per token is not per task: an average task of Artificial Analysis' Intelligence Index cost $2.47 on GPT-6 Sol (max) and $2.39 on Muse Spark 1.3 (max), and Muse Spark 1.3 (max) wrote 1.7× as many output tokens for the same work, which a per-token price hides.
Each model is compared at its best-ranked reasoning-effort setting. GPT-6 Sol (max) scores 62.9 and takes 72 s to its first answer token; GPT-6 Sol (xhigh) scores 58.6 in 24 s, GPT-6 Sol (high) scores 58.2 in 9 s. Muse Spark 1.3 (max) scores 61.7 and takes 36 s to its first answer token; Muse Spark 1.3 scores 59.2 in 4 s, Muse Spark 1.3 (xhigh) scores 58.1 in 13 s. 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
122 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 Sol (max) | Muse Spark 1.3 (max) |
|---|---|---|---|
| BenchLeader Index | BenchLeader | 62.9 | 61.7 |
| Agents & tools score | BenchLeader | 59.6 | 65.5 |
| Coding score | BenchLeader | 66.5 | 60.7 |
| Human preference score | BenchLeader | 64.2 | 69.0 |
| Knowledge score | BenchLeader | 61.5 | 57.2 |
| Long context score | BenchLeader | 66.6 | 66.3 |
| Maths score | BenchLeader | 68.5 | 63.1 |
| Multimodal score | BenchLeader | 60.7 | 65.8 |
| Reasoning score | BenchLeader | 66.2 | 59.8 |
| Blended price $/M | BenchLeader | $4.00 | $2.00 |
| Output speed | BenchLeader | 121 tok/s | 123 tok/s |
| Time to first answer | BenchLeader | 72.1 s | 36.1 s |
| Context window | BenchLeader | 1,050,000 tokens | 1,048,576 tokens |
| Reasoning | |||
| GPQA Diamond | Epoch AI Benchmarking Hub | 94.3% | – |
| Arena Hard Prompts | Arena (LMArena) | 1483 | 1515 |
| LiveBench 2.0 Reasoning | LiveBench | – | 89.7%† |
| LiveBench 1.0 Reasoning | LiveBench | 88.7% | 89.7%† |
| GPQA Diamond (AA) | Artificial Analysis | – | 93.5% |
| Humanity's Last Exam (AA) | Artificial Analysis | 47.9% | 48.7% |
| HLE-Diamond (AA) | Artificial Analysis | 45.2% | 33.7% |
| ARC-AGI-1 | ARC Prize | 95.5% | – |
| ARC-AGI-2 | ARC Prize | 89.6% | – |
| ARC-AGI-3 | ARC Prize | 23.0% | – |
| CritPt | Artificial Analysis | 30.9% | 24.9% |
| CritPt v2 hard subset (AA) | Artificial Analysis | 66.5% | 48.0% |
| MysteryMechanism | Vals AI | 30.2% | 36.0% |
| Chess Puzzles | Epoch AI Benchmarking Hub | 56.0% | 37.0% |
| Mystery Game Puzzles | Epoch AI Benchmarking Hub | 56.0% | 25.0% |
| LMCA | Epoch AI Benchmarking Hub | 59.1% | 53.9%† |
| DTBench | Epoch AI Benchmarking Hub | 97.3% | 96.5%† |
| BTF-3 | Epoch AI Benchmarking Hub | – | 14.1%† |
| Coding | |||
| SciCode | SciCode | 57.6% | 58.8% |
| FrontierCode | Cognition | 49.3% | – |
| Arena Coding | Arena (LMArena) | 1520 | 1532 |
| Arena WebDev | Arena (LMArena) | 1674 | 1654 |
| LiveBench 2.0 Coding | LiveBench | – | 83.1%† |
| LiveBench 1.0 Coding | LiveBench | 81.8% | 81.1%† |
| IOI | Vals AI | 82.6% | 56.6% |
Show all 122 benchmarks
| Metric | Publisher | GPT-6 Sol (max) | Muse Spark 1.3 (max) |
|---|---|---|---|
| Coding | |||
| Code Migration | Vals AI | 57.2% | 47.4% |
| ProgramBench | Vals AI | 2.0% | 2.5% |
| SWE-bench Multimodal | Vals AI | – | 43.1% |
| Vibe Code Bench 1-100 | Vals AI | – | 20.5% |
| Vibe Code Bench v1.1 | Vals AI | 87.8% | 85.9% |
| CursorBench | Cursor | – | 41.6% |
| ALE-Bench | Epoch AI Benchmarking Hub | 2462 | 1688.3† |
| FrontierSWE | Epoch AI Benchmarking Hub | – | 25.8% |
| Terminal-Bench 4.0 (AA) | Artificial Analysis | 43.9% | 33.3% |
| Terminal-Bench 2.1 (AA) | Artificial Analysis | – | 84.3% |
| Startrise Frontend | Startrise | – | 74.7%† |
| GameBench 2 Overall | DuelLab GameBench 2 | 72.9† | 57.8† |
| GameBench 2 by reasoning setting | DuelLab GameBench 2 | 79.3† | 68.7† |
| Design Arena Website | Design Arena | 1285† | 1343 |
| FrontierCode 1.1 (AA) | Artificial Analysis | – | 40.6% |
| FrontierCode 2.0 (AA) | Artificial Analysis | 35.6% | 23.1% |
| Agents & tools | |||
| Terminal-Bench | Terminal-Bench | 50.3% | 14.8%† |
| APEX-Agents | Mercor | 54.3% | 47.6% |
| Arena Agent | Arena (LMArena) | 7 | 2.2 |
| LiveBench Long Agentic | LiveBench | – | 47.9%† |
| LiveBench Browser | LiveBench | – | 30.9%† |
| LiveBench Agentic Coding | LiveBench | 52.9% | 64.1%† |
| Terminal-Bench 2.1 (Vals) | Vals AI | 83.2% | 79.0% |
| HiL-Bench | Scale AI SEAL | – | 66.9%† |
| τ³-Banking (AA) | Artificial Analysis | – | 50.5% |
| ITBench SRE (AA) | Artificial Analysis | 49.4% | 33.2% |
| Analyst Agent (AA) | Artificial Analysis | – | 37.5% |
| CUA-bench | Vals AI | – | 5.8% |
| CyberBench | Vals AI | 78.0% | 72.7% |
| Finance Agent v2 | Vals AI | 49.0% | 60.0% |
| Harvey's Legal Agent Benchmark v1 | Vals AI | 1.7% | 23.8% |
| Legal Research Bench | Vals AI | 28.9% | 55.3% |
| SREBench | Vals AI | 30.5% | 3.8% |
| Tax Agent Bench | Vals AI | 15.0% | 42.4% |
| Terminal-Bench 4.0 (Vals) | Vals AI | 44.4% | 24.8% |
| Terminal-Bench Science | Vals AI | 30.0% | 10.0% |
| Arena Search | Arena (LMArena) | 1229 | – |
| Vending-Bench 2 | Andon Labs | 14427.9† | – |
| AutomationBench | Artificial Analysis | 61.6% | 57.9% |
| GDP.pdf (AA) | Artificial Analysis | 25.2% | 26.6% |
| Harvey LAB-AA v1.1 | Harvey | 3.6% | 8.9% |
| AA-Briefcase v1.1 | Artificial Analysis | 1476 | 1581 |
| Design Arena Agentic | Design Arena | 1212† | 1278 |
| Terminal-Bench-Science 0.1 (AA) | Artificial Analysis | 30.0% | 10.9% |
| CWE-Bench (AA) | Artificial Analysis | 64.2% | – |
| DeepSec-Bench (AA) | Artificial Analysis | 46.3% | – |
| CyberGym end-to-end (AA) | Artificial Analysis | 0.0% | – |
| Maths | |||
| FrontierMath Tiers 1–3 | Epoch AI Benchmarking Hub | 89.8% | 74.0% |
| FrontierMath Tier 4 | Epoch AI Benchmarking Hub | 90.0% | 46.3% |
| OTIS Mock AIME | Epoch AI Benchmarking Hub | 100.0% | 99.2%† |
| ProofBench | Vals AI | 83.0%† | 58.0% |
| LiveBench Mathematics | LiveBench | 96.4% | 96.0%† |
| Arena Maths | Arena (LMArena) | 1440 | 1507 |
| Knowledge | |||
| SimpleQA Verified | Epoch AI Benchmarking Hub | 60.7% | – |
| LiveBench 2.0 Data Analysis | LiveBench | – | 79.6%† |
| LiveBench Research | LiveBench | – | 82.5%† |
| LiveBench 1.0 Data Analysis | LiveBench | 81.2% | 79.6%† |
| AA-Omniscience v1.1 | Artificial Analysis | 21.4 | 22.4 |
| PRBench Finance | Scale AI SEAL | – | 59.5%† |
| PRBench Legal | Scale AI SEAL | 38.6%† | 61.6%† |
| BioMysteryBench | Vals AI | 74.8% | – |
| Excel Modeling Benchmark | Vals AI | 71.5% | 67.4% |
| MedCode | Vals AI | 47.1% | – |
| MedScribe | Vals AI | 82.0% | – |
| Public Benefits Bench v1.1 | Vals AI | 56.6% | – |
| DrugDiscoveryBench | Scale AI SEAL | – | 62.2%† |
| EBR-bench | Epoch AI Benchmarking Hub | 53.3% | – |
| GDP.pdf | Epoch AI Benchmarking Hub | 26.4% | 27.6%† |
| AA-Omniscience v1.1: accuracy | Artificial Analysis | 51.1% | 38.0% |
| AA-Omniscience v1.1: non-hallucination | Artificial Analysis | 39.1% | 74.8% |
| HealthBench Professional (AA) | OpenAI | 62.3% | – |
| Instruction following | |||
| LiveBench Language | LiveBench | 85.3% | 82.8%† |
| LiveBench Instruction Following | LiveBench | 68.6% | 78.0%† |
| Arena Instruction Following | Arena (LMArena) | 1448 | 1485 |
| Human preference | |||
| Arena Text | Arena (LMArena) | 1457 | 1496 |
| Arena Creative Writing | Arena (LMArena) | 1430 | 1467 |
| Arena Multi-turn | Arena (LMArena) | 1466 | 1493 |
| Arena Longer Queries | Arena (LMArena) | 1466 | 1497 |
| Multimodal | |||
| Arena Vision | Arena (LMArena) | 1232 | 1309 |
| LiveBench Design | LiveBench | – | 74.8%† |
| MMMU-Pro | Artificial Analysis | 83.0% | 82.0%† |
| Blueprint-Bench 2 | Epoch AI Benchmarking Hub | 36.9%† | – |
| Code2Video-AA | Artificial Analysis | – | 1019 |
| AA-3D | Artificial Analysis | 1131 | 1032 |
| Long context | |||
| AA-LCR v1.1 | Artificial Analysis | 83.7% | 83.0% |
| Arena Document | Arena (LMArena) | – | 1475 |
| MLCR | Artificial Analysis | 33.9% | 13.9% |
| Composite | |||
| Epoch Capabilities Index | Epoch AI Benchmarking Hub | 164.1† | 158.0† |
| LiveBench 2.0 | LiveBench | – | 68.4%† |
| LiveBench 1.0 | LiveBench | 79.3% | 81.6%† |
| AA Intelligence Index v5.0 | Artificial Analysis | 44.2 | 36.6 |
| AA Intelligence Index v4.3.2 | Artificial Analysis | 47.6 | 48.1 |
| AA Progress Index v1 | Artificial Analysis | 334 | 324.5 |
| Vals RSI Index | Vals AI | 28.1% | 19.6% |
| Vals Science Index | Vals AI | 45.0% | – |
| AA Cyber Index | Artificial Analysis | 36.8 | – |
| Safety & honesty | |||
| FORTRESS | Scale AI SEAL | 13.5%† | – |
Data as of 2026-11-09. Best configuration of each model; every score links to its source on the model pages.
DuelLab GameBench 2, release gb2-20261103-eaea31df94e6 (https://benchmarks.duellab.org/releases/gb2-20261103-eaea31df94e6/), CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/). Scores mapped to BenchLeader model names; not endorsed by DuelLab.
What changed
- GPT-6 Sol (max): BenchLeader Index 63.5 → 62.9.
- GPT-6 Sol (max): 2 score revisions.
- GPT-6 Sol (max): 1 score revision.
- Muse Spark 1.3 (max): 1 score revision.
- GPT-6 Sol (max): 1 score revision.
- GPT-6 Sol (max): 6 new results (AA Intelligence Index v5.0, AA-Omniscience v1.1, CritPt v2 hard subset (AA)…).
- Muse Spark 1.3 (max): 1 score revision.
- GPT-6 Sol (max): 1 score revision.
- GPT-6 Sol (max): 1 score revision.
- Muse Spark 1.3 (max): 1 score revision.
Related comparisons
- GPT-6 Sol vs Claude Fable 5.2
- GPT-6 Sol vs Claude Opus 5.5
- GPT-6 Sol vs Gemini 4 Carbon
- Muse Spark 1.3 vs Claude Fable 5.2
- Muse Spark 1.3 vs Claude Opus 5.5
- Muse Spark 1.3 vs Gemini 4 Carbon
- Muse Spark 1.3 vs GPT-6 Astra
- GPT-6 Sol vs Muse Spark 1.2
Rankings: Best LLM overall · Best LLM for agents · Best cheap LLMs
GPT-6 Sol vs Muse Spark 1.3: questions
- Is GPT-6 Sol better than Muse Spark 1.3?
- GPT-6 Sol (max) and Muse Spark 1.3 (max) are neck and neck on quality (62.9 vs 61.7, within the ±4.7 margin). The BenchLeader Index combines every independent quality benchmark; the two are within the margin of error as of 9 Nov 2026, so check the category scores for your use.
- GPT-6 Sol vs Muse Spark 1.3: which is cheaper, and will that change?
- Muse Spark 1.3 is cheaper today: $2.00 against $4.00 per million tokens, blended at three input tokens per output token. No price change has been announced for either.
- Is GPT-6 Sol or Muse Spark 1.3 better for coding?
- GPT-6 Sol scores higher in coding (67 vs 61 on the category index, where 50 is average). On Arena WebDev, the top shared coding benchmark, it is 1674 for GPT-6 Sol against 1654 for Muse Spark 1.3.
- Which is faster, GPT-6 Sol or Muse Spark 1.3?
- Muse Spark 1.3 streams faster (123 vs 121 output tokens per second, Artificial Analysis 7-day median).
- Is GPT-6 Sol or Muse Spark 1.3 better for agents and tool use?
- Muse Spark 1.3 scores higher in agentic tasks (66 vs 60 on the category index, where 50 is average). On APEX-Agents, the top shared agents & tools benchmark, it is 54.3% for GPT-6 Sol against 47.6% for Muse Spark 1.3.
More questions (4)
- Which is better for long documents?
- They are level on long-context benchmarks (67 vs 66). Both take about 1.1M tokens: GPT-6 Sol 1,050,000, Muse Spark 1.3 1,048,576.
- Which has lower latency?
- Muse Spark 1.3 answers first: 36.1 s against 72.1 s to the first answer token, as Artificial Analysis measures it. Reasoning effort drives most of this: a higher setting thinks longer before it answers.
- Do independent benchmarks agree on GPT-6 Sol vs Muse Spark 1.3?
- Across the 51 benchmarks both have, GPT-6 Sol leads 30, Muse Spark 1.3 leads 21. Independent sources split: GPT-6 Sol leads on AA Intelligence Index v5.0; Muse Spark 1.3 leads on Arena Text.
- When was GPT-6 Sol released?
- GPT-6 Sol was released on 22 Sep 2026.