Claude Opus 4.6 vs Muse Wonder Full
Full profiles: Claude Opus 4.6 (Anthropic) and Muse Wonder Full (Meta): every benchmark, price and rank.
Updated · Data from 9 sources
As of 24 Oct 2026, Claude Opus 4.6 (high) and Muse Wonder Full (max) are neck and neck on quality (62.7 vs 70.7, inside the ±9.0 margin of error) and close on price, so pick on the category that matters to you. Muse Wonder Full leads in every category we measure both in.
Claude Opus 4.6 benchmarks high Anthropic
Muse Wonder Full benchmarks max MetaOpen in the comparison toolWhich 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 | Muse Wonder Full | 72 vs 63 category score; Arena WebDev 1726 vs 1546 | High |
| Reasoning | Muse Wonder Full | 95 vs 66 category score | High |
| Chat quality (human preference) | – | Only Claude Opus 4.6 has an Arena rating (70 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
- Claude Opus 4.6 (high) and Muse Wonder Full (max) are neck and neck on quality (62.7 vs 70.7, within the ±9.0 margin).
- Claude Opus 4.6 (high) is stronger in human preference, maths, multimodal.
- Muse Wonder Full (max) is stronger in coding, reasoning, composite, knowledge, long context.
At a glance
| Spec | Claude Opus 4.6 | Muse Wonder Full |
|---|---|---|
| Developer | Anthropic | Meta |
| Released | 5 Feb 2026 | 12 Oct 2026 |
| Context window (tokens) | 1,000,000 | 1,000,000 |
| Compared at | Claude Opus 4.6 (high) | Muse Wonder Full (max) |
| Open weights | No | No |
| Price in / out / cached input per 1M | $5.00 / $25.00 / $0.500 | – |
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 | Claude Opus 4.6 (high) | Muse Wonder Full (max) | Leader |
|---|---|---|---|
| Reasoning | 65.5 | 94.9 | Muse Wonder Full |
| Coding | 62.8 | 72.3 | Muse Wonder Full |
| Maths | 63.5 | – | not comparable |
| Knowledge | – | 71.4 | not comparable |
| Human preference | 70.0 | – | not comparable |
| Multimodal | 66.6 | – | not comparable |
| Long context | – | 67.0 | not comparable |
| Composite | – | 91.9 | not comparable |
Where sources disagree
Across the 1 benchmarks both have, Claude Opus 4.6 leads 0, Muse Wonder Full leads 1. Every overall index that rates both puts Muse Wonder Full ahead.
| Overall index | Claude Opus 4.6 (high) | Muse Wonder Full (max) | Leader |
|---|---|---|---|
| BenchLeader Index | 62.7 | 70.7 | neck and neck |
| AA Intelligence Index v4.3.2 | 26.4† | 55.8 | Muse Wonder Full |
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 | Claude Opus 4.6 (high) | Muse Wonder Full (max) |
|---|---|---|
| Blended price per 1M tokens | $10.00 | – |
| Input / output per 1M | $5.00 / $25.00 | – / – |
| Cached input per 1M | $0.500 | – |
| Price per task: chat reply | $0.0095 | – |
| Price per task: summarize a 30-page report | $0.075 | – |
| Price per task: code edit | $0.068 | – |
| Price per task: agentic coding session | $0.400 | – |
| Price per task: structured extraction | $0.015 | – |
| Output speed | 40 tok/s | – |
| Time to first answer | 1.2 s | – |
Each model is compared at its best-ranked reasoning-effort setting. Claude Opus 4.6 (high) scores 62.7 and takes 1 s to its first answer token; Claude Opus 4.6 scores 62.6 in 1 s, Claude Opus 4.6 (thinking) scores 62.5 in 1 s. Muse Wonder Full (max) scores 70.7. 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
146 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 | Claude Opus 4.6 (high) | Muse Wonder Full (max) |
|---|---|---|---|
| BenchLeader Index | BenchLeader | 62.7 | 70.7 |
| Coding score | BenchLeader | 62.8 | 72.3 |
| Human preference score | BenchLeader | 70.0 | – |
| Maths score | BenchLeader | 63.5 | – |
| Multimodal score | BenchLeader | 66.6 | – |
| Reasoning score | BenchLeader | 65.5 | 94.9 |
| Composite score | BenchLeader | – | 91.9 |
| Knowledge score | BenchLeader | – | 71.4 |
| Long context score | BenchLeader | – | 67.0 |
| Blended price $/M | BenchLeader | $10.00 | – |
| Output speed | BenchLeader | 40 tok/s | – |
| Time to first answer | BenchLeader | 1.2 s | – |
| Context window | BenchLeader | 1,000,000 tokens | 1,000,000 tokens |
| Reasoning | |||
| GPQA Diamond | Epoch AI Benchmarking Hub | 90.5%† | – |
| Humanity's Last Exam | Scale AI / CAIS | 19.0%† | – |
| SimpleBench | SimpleBench | 67.6%† | – |
| Arena Hard Prompts | Arena (LMArena) | 1530 | – |
| LiveBench 1.0 Reasoning | LiveBench | 88.7% | – |
| GPQA Diamond (AA) | Artificial Analysis | 89.6%† | – |
| Humanity's Last Exam (AA) | Artificial Analysis | 39.9%† | 53.6% |
| GPQA Diamond (Vals) | Vals AI | 89.7%† | – |
| Kagi LLM Benchmark | Kagi LLM Benchmark | 72.4%† | – |
| ARC-AGI-1 | ARC Prize | 94.0% | – |
| ARC-AGI-2 | ARC Prize | 69.2% | – |
| ARC-AGI-3 | ARC Prize | 0.5%† | – |
| CritPt | Artificial Analysis | 12.6%† | 32.9% |
| MysteryMechanism | Vals AI | – | 35.1% |
| Chess Puzzles | Epoch AI Benchmarking Hub | 21.0%† | – |
| Mystery Game Puzzles | Epoch AI Benchmarking Hub | 15.0%† | – |
| CL-bench | Epoch AI Benchmarking Hub | 20.7%† | – |
| CL-bench Life | Epoch AI Benchmarking Hub | 17.0% | – |
| LMCA | Epoch AI Benchmarking Hub | 55.8%† | – |
| DTBench | Epoch AI Benchmarking Hub | 91.2%† | – |
| ForecastBench | ForecastBench | 63.4%† | – |
| Coding | |||
| SWE-bench Verified (Epoch) | Epoch AI Benchmarking Hub | 78.7%† | – |
| WeirdML | WeirdML | 78.0% | – |
| FrontierCode | Cognition | 26.6%† | – |
| GSO-Bench | GSO-Bench | 41.2% | – |
Show all 146 benchmarks
| Metric | Publisher | Claude Opus 4.6 (high) | Muse Wonder Full (max) |
|---|---|---|---|
| Coding | |||
| Arena Coding | Arena (LMArena) | 1547 | – |
| Arena WebDev | Arena (LMArena) | 1546 | 1726 |
| LiveBench 1.0 Coding | LiveBench | 78.2% | – |
| SciCode (AA) | Artificial Analysis | – | 62.6% |
| LiveCodeBench | Vals AI | 84.7%† | – |
| IOI | Vals AI | – | 79.8% |
| SWE-bench (Vals) | Vals AI | 78.2%† | – |
| SWE-Bench Pro | Scale AI SEAL | 51.9%† | – |
| SWE-bench Verified (bash only) | SWE-bench | 75.6%† | – |
| SWE-bench Verified (any scaffold) | SWE-bench | 75.6%† | – |
| Code Migration | Vals AI | – | 61.0% |
| Code Migration v1.1 | Vals AI | – | 62.8% |
| ProgramBench | Vals AI | – | 0.5% |
| SWE-bench Multimodal | Vals AI | – | 47.3% |
| Vibe Code Bench 1-100 | Vals AI | – | 34.0% |
| Vibe Code Bench v1.1 | Vals AI | 57.6%† | 86.0% |
| SWE-Bench Pro (private) | Scale AI SEAL | 51.9%† | – |
| SWE Atlas: Codebase QnA | Scale AI SEAL | 33.3%† | – |
| SWE Atlas: Refactoring | Scale AI SEAL | 35.6%† | – |
| SWE Atlas: Test Writing | Scale AI SEAL | 36.7%† | – |
| ALE-Bench | Epoch AI Benchmarking Hub | 996.5† | – |
| AlgoTune | AlgoTune | 1.5 | – |
| Terminal-Bench 4.0 (AA) | Artificial Analysis | – | 57.1% |
| FrontierCode 1.1 (AA) | Artificial Analysis | – | 44.9% |
| Agents & tools | |||
| Terminal-Bench | Terminal-Bench | 79.8%† | – |
| Cybench | Cybench | 93.0%† | – |
| Remote Labor Index | Scale AI / CAIS | 4.2%† | – |
| APEX-Agents | Mercor | 46.3%† | – |
| LiveBench Agentic Coding | LiveBench | 49.0% | – |
| Terminal-Bench Hard | Artificial Analysis | 46.2%† | – |
| τ²-Bench Telecom (AA) | Artificial Analysis | 92.1%† | – |
| MCP Atlas | Scale AI SEAL | 76.8%† | – |
| HiL-Bench | Scale AI SEAL | 38.3%† | – |
| τ³-bench Banking | τ²-bench | 27.3%† | – |
| GDPval-AA v2.1 | Artificial Analysis | – | 67.8% |
| APEX-Agents (AA) | Artificial Analysis | 33.0%† | – |
| CyberBench | Vals AI | – | 73.6% |
| Finance Agent v2 | Vals AI | – | 59.1% |
| Finance Agent v2.1 | Vals AI | – | 67.6% |
| Harvey's Legal Agent Benchmark v1.1 | Vals AI | – | 23.3% |
| Harvey's Legal Agent Benchmark v1 | Vals AI | – | 21.7% |
| Legal Research Bench | Vals AI | – | 53.4% |
| Robo-bench | Vals AI | – | 10.4% |
| SREBench | Vals AI | – | 11.8% |
| Tax Agent Bench | Vals AI | – | 43.0% |
| Terminal-Bench 2.0 (Vals) | Vals AI | 58.4%† | – |
| Terminal-Bench 4.0 (Vals) | Vals AI | – | 58.1% |
| Terminal-Bench Science | Vals AI | – | 37.1% |
| DeepResearch Bench | DeepResearch Bench | 55.3% | – |
| METR Time Horizons | METR | 78.9%† | – |
| GBAEval | Epoch AI Benchmarking Hub | 44.1%† | – |
| Vending-Bench 2 | Andon Labs | 8017.6† | – |
| AutomationBench | Artificial Analysis | – | 71.3% |
| GDP.pdf (AA) | Artificial Analysis | – | 32.6% |
| Harvey LAB-AA v1.1 | Harvey | – | 13.1% |
| AA-Briefcase v1.1 | Artificial Analysis | – | 1729 |
| Terminal-Bench-Science 0.1 (AA) | Artificial Analysis | – | 37.1% |
| Maths | |||
| FrontierMath Tiers 1–3 | Epoch AI Benchmarking Hub | 66.0%† | – |
| FrontierMath Tier 4 | Epoch AI Benchmarking Hub | 26.8%† | – |
| OTIS Mock AIME | Epoch AI Benchmarking Hub | 94.4%† | – |
| ProofBench | Vals AI | 50.0%† | – |
| LiveBench Mathematics | LiveBench | 89.3% | – |
| AIME (Vals) | Vals AI | 95.6%† | – |
| AIME 2026 | MathArena | 96.7% | – |
| HMMT February 2026 | MathArena | 96.2% | – |
| USAMO 2026 | MathArena | 47.0% | – |
| MathArena Apex | MathArena | 34.5% | – |
| Arena Maths | Arena (LMArena) | 1517 | – |
| Knowledge | |||
| SimpleQA Verified | Epoch AI Benchmarking Hub | 47.0%† | – |
| LiveBench 1.0 Data Analysis | LiveBench | 69.9% | – |
| AA-Omniscience | Artificial Analysis | 13.7† | 30.1 |
| MMLU-Pro | Vals AI | 89.1%† | – |
| LegalBench | Vals AI | 85.3%† | 87.4% |
| CorpFin | Vals AI | 67.0%† | – |
| TaxEval | Vals AI | 76.0%† | – |
| MedQA | Vals AI | 95.4%† | – |
| PRBench Finance | Scale AI SEAL | 53.3%† | – |
| PRBench Legal | Scale AI SEAL | 52.3%† | – |
| MultiNRC | Scale AI SEAL | 57.1%† | – |
| BioMysteryBench | Vals AI | – | 73.3% |
| CaseLaw v2 | Vals AI | 62.1%† | – |
| Excel Modeling Benchmark | Vals AI | – | 71.9% |
| Excel Modeling Benchmark v1.1 | Vals AI | – | 75.0% |
| MedCode | Vals AI | 48.2%† | 49.9% |
| MedScribe | Vals AI | 86.7%† | 89.3% |
| Public Benefits Bench v1.1 | Vals AI | – | 73.8% |
| DrugDiscoveryBench | Scale AI SEAL | 27.7%† | – |
| EBR-bench | Epoch AI Benchmarking Hub | 12.7%† | – |
| AA-Omniscience: accuracy | Artificial Analysis | 47.0%† | 43.2% |
| AA-Omniscience: non-hallucination | Artificial Analysis | 37.2%† | 77.0% |
| Global-MMLU-Lite (AA) | Artificial Analysis | 92.2%† | – |
| Instruction following | |||
| LiveBench Language | LiveBench | 83.3% | – |
| LiveBench Instruction Following | LiveBench | 63.3% | – |
| IFBench | Artificial Analysis | 53.1%† | – |
| MultiChallenge | Scale AI SEAL | 37.1%† | – |
| TutorBench | Scale AI SEAL | 53.7%† | – |
| Arena Instruction Following | Arena (LMArena) | 1511 | – |
| Human preference | |||
| Arena Text | Arena (LMArena) | 1503 | – |
| EQ-Bench 4 | EQ-Bench | 1223† | – |
| Arena Creative Writing | Arena (LMArena) | 1500 | – |
| Arena Multi-turn | Arena (LMArena) | 1516 | – |
| Arena Longer Queries | Arena (LMArena) | 1521 | – |
| Multimodal | |||
| Arena Vision | Arena (LMArena) | 1316 | – |
| MMMU-Pro | Artificial Analysis | 75.4%† | – |
| VISTA | Scale AI SEAL | 46.1%† | – |
| MMMU-Pro (Vals) | Vals AI | 83.9%† | – |
| MortgageTax | Vals AI | 68.5%† | – |
| SAGE | Vals AI | 51.6%† | – |
| VTB | Scale AI SEAL | 27.5%† | – |
| Long context | |||
| AA-LCR | Artificial Analysis | 78.0%† | 83.7% |
| Arena Document | Arena (LMArena) | 1495 | – |
| Composite | |||
| Epoch Capabilities Index | Epoch AI Benchmarking Hub | 155.7† | – |
| LiveBench 1.0 | LiveBench | 74.5% | – |
| AA Intelligence Index v4.3.2 | Artificial Analysis | 31.9† | 55.8 |
| Vals Index | Vals AI | – | 66.8 |
| Vals Finance Index | Vals AI | – | 64.5% |
| Vals RSI Index | Vals AI | – | 24.4% |
| Vals Science Index | Vals AI | – | 48.5% |
| Vals Router Index | Vals AI | – | 66.8%† |
| Safety & honesty | |||
| FORTRESS | Scale AI SEAL | 13.0%† | – |
| MASK | Scale AI SEAL | 85.4%† | – |
Data as of 2026-10-24. Best configuration of each model; every score links to its source on the model pages.
What changed
- Muse Wonder Full (max): 1 new result (Terminal-Bench-Science 0.1 (AA)).
- Muse Wonder Full (max): 9 new results (Code Migration v1.1, Excel Modeling Benchmark v1.1, Finance Agent v2.1…).
- Muse Wonder Full (max): 1 new result (FrontierCode 1.1 (AA)).
- Muse Wonder Full (max): BenchLeader Index 68.6 → 70.7.
- Muse Wonder Full (max): 1 new result (Arena WebDev); 2 score revisions.
- Claude Opus 4.6 (high): BenchLeader Index 60.4 → 62.9.
- Claude Opus 4.6 (high): 1 new result (USAMO 2026).
- Muse Wonder Full (max): 21 new results (IOI, LegalBench, Vals Index…).
- Muse Wonder Full (max): 1 new result (Harvey LAB-AA v1.1).
- Muse Wonder Full (max): first results.
Related comparisons
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- Claude Opus 4.6 vs Gemini 4 Argon
- Claude Opus 4.6 vs Claude Fable 5.1
- Muse Wonder Full vs Claude Opus 5.5
- Muse Wonder Full vs Gemini 4 Argon
- Muse Wonder Full vs Claude Fable 5.1
- Muse Wonder Full vs GPT-6 Astra
- Claude Opus 4.5 vs Muse Wonder Full
Rankings: Best LLM overall · Best LLM for coding · Best LLM for agents · Best cheap LLMs
Claude Opus 4.6 vs Muse Wonder Full: questions
- Is Claude Opus 4.6 better than Muse Wonder Full?
- Claude Opus 4.6 (high) and Muse Wonder Full (max) are neck and neck on quality (62.7 vs 70.7, within the ±9.0 margin). The BenchLeader Index combines every independent quality benchmark; the two are within the margin of error as of 2026-10-24, so check the category scores for your use.
- Is Claude Opus 4.6 better than Muse Wonder Full for coding?
- Muse Wonder Full scores higher in coding (72 vs 63 on the category index, where 50 is average). On Arena WebDev, the top shared coding benchmark, it is 1546 for Claude Opus 4.6 against 1726 for Muse Wonder Full.
- Which is better for long documents?
- Both accept 1,000,000 tokens of context.
- Do independent benchmarks agree on Claude Opus 4.6 vs Muse Wonder Full?
- Across the 1 benchmarks both have, Claude Opus 4.6 leads 0, Muse Wonder Full leads 1. Every overall index that rates both puts Muse Wonder Full ahead.
- When was Muse Wonder Full released?
- Muse Wonder Full was released on 12 Oct 2026.