Claude Opus 4.7 vs Muse Wonder
As of 13 Oct 2026, Muse Wonder (max) is the better pick for most workloads: it leads on quality (66.3 vs 63.7 on the BenchLeader Index) and costs 1.3× less.
Claude Opus 4.7 
Muse Wonder Key differences
- Muse Wonder (max) leads on quality: 66.3 vs 63.7.
- Claude Opus 4.7 is stronger in agents & tools, coding, human preference, maths, multimodal.
- Muse Wonder (max) is stronger in knowledge, reasoning, composite, long context.
- Muse Wonder (max) is 1.3× cheaper ($8.00 vs $10.00 per 1M blended).
Choose Claude Opus 4.7 if
- the wait for the first word matters: 1.9 s against 60.8 s to first answer
Choose Muse Wonder (max) if
- reasoning is the priority (88 vs 65 on the category score)
- knowledge is the priority (73 vs 62 on the category score)
- cost matters: $8.00 against $10.00 per million tokens blended
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 4.7 | Muse Wonder (max) | Leader |
|---|---|---|---|
| Reasoning | 65.3 | 87.8 | Muse Wonder |
| Coding | 61.6 | – | not comparable |
| Agents & tools | 67.5 | – | not comparable |
| Maths | 67.1 | – | not comparable |
| Knowledge | 62.3 | 73.0 | Muse Wonder |
| Human preference | 68.6 | – | not comparable |
| Multimodal | 66.8 | – | not comparable |
| Long context | – | 65.5 | not comparable |
| Composite | – | 78.2 | not comparable |
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 4.7 | Muse Wonder (max) |
|---|---|---|
| Blended price per 1M tokens | $10.00 | $8.00 |
| Input / output per 1M | $5.00 / $25.00 | $4.00 / $20.00 |
| Price per task: chat reply | $0.0095 | $0.0076 |
| Price per task: summarise a 30-page report | $0.075 | $0.060 |
| Price per task: code edit | $0.068 | $0.054 |
| Price per task: agentic coding session | $0.400 | $0.320 |
| Price per task: structured extraction | $0.015 | $0.012 |
| Cost to run a full benchmark suite | – | $4.52 |
| Output speed | 80 tok/s | 85 tok/s |
| Time to first answer | 1.9 s | 60.8 s |
| Time to a complete answer | – | 66.7 s |
Every benchmark
| Metric | Claude Opus 4.7 | Muse Wonder (max) |
|---|---|---|
| BenchLeader Index | 63.7 | 66.3 |
| Agents & tools score | 67.5 | – |
| Coding score | 61.6 | – |
| Human preference score | 68.6 | – |
| Knowledge score | 62.3 | 73.0 |
| Maths score | 67.1 | – |
| Multimodal score | 66.8 | – |
| Reasoning score | 65.3 | 87.8 |
| Composite score | – | 78.2 |
| Long context score | – | 65.5 |
| Blended price $/M | $10.00 | $8.00 |
| Output speed | 80 tok/s | 85 tok/s |
| Time to first answer | 1.9 s | 60.8 s |
| Context window | 1M | 1.0M |
| Humanity's Last Exam | 36.2% | – |
| Terminal-Bench | 80.2% | – |
| SimpleBench | 61.7% | – |
| WeirdML | 76.4% | – |
| FrontierCode | 38.5% | – |
| GSO-Bench | 44.1% | – |
| Epoch Capabilities Index | 156.3 | – |
| LMArena Text | 1494 | – |
| LMArena Hard Prompts | 1519 | – |
| LMArena Coding | 1547 | – |
| LMArena WebDev | 1555 | – |
| LMArena Vision | 1316 | – |
| LiveBench | – | 81.2% |
| LiveBench Reasoning | – | 90.6% |
| LiveBench Coding | – | 80.7% |
| LiveBench Agentic Coding | – | 62.7% |
| LiveBench Mathematics | – | 96.5% |
| LiveBench Data Analysis | – | 81.6% |
| LiveBench Language | – | 82.9% |
| LiveBench Instruction Following | – | 73.0% |
| AA Intelligence Index v4.3.2 | – | 52.4 |
| AA-LCR | – | 80.7% |
| AA-Omniscience | – | 25.5 |
| Humanity's Last Exam (AA) | – | 50.1% |
| SciCode (AA) | – | 60.3% |
| AIME (Vals) | 96.3% | – |
| LiveCodeBench | 85.1% | – |
| MMLU-Pro | 89.9% | – |
| LegalBench | 85.3% | – |
| CorpFin | 66.1% | – |
| TaxEval | 75.3% | – |
| Terminal-Bench 2.1 (Vals) | 68.5% | – |
| SWE-bench (Vals) | 82.0% | – |
| GPQA Diamond (Vals) | 90.2% | – |
| HiL-Bench | 41.7% | – |
| EQ-Bench 4 | 1311 | – |
| Kagi LLM Benchmark | 73.3% | – |
| CritPt | – | 28.3% |
| GDPval-AA v2.1 | – | 63.5% |
| CaseLaw v2 | 68.4% | – |
| Code Migration | 43.9% | – |
| Excel Modeling Benchmark | 63.7% | – |
| Finance Agent v2 | 51.5% | – |
| Harvey's Legal Agent Benchmark | 6.7% | – |
| Legal Research Bench | 38.5% | – |
| MedCode | 54.9% | – |
| MedScribe | 83.0% | – |
| MMMU-Pro (Vals) | 85.5% | – |
| MortgageTax | 70.3% | – |
| ProgramBench | 0.0% | – |
| SAGE | 56.1% | – |
| Tax Agent Bench | 63.9% | – |
| Terminal-Bench 2.0 (Vals) | 68.5% | – |
| Vals Multimodal Index | 67.4% | – |
| Vibe Code Bench v1.1 | 71.0% | – |
| SWE Atlas: Codebase QnA | 40.3% | – |
| SWE Atlas: Refactoring | 48.6% | – |
| SWE Atlas: Test Writing | 38.5% | – |
| LMArena Maths | 1492 | – |
| LMArena Creative Writing | 1483 | – |
| LMArena Instruction Following | 1493 | – |
| LMArena Multi-turn | 1514 | – |
| LMArena Longer Queries | 1508 | – |
| LMArena Search | 1212 | – |
| LMArena Document | 1494 | – |
| Mystery Game Puzzles | 13.0% | – |
| ExploitBench | 26.5% | – |
| ForecastBench | 60.3% | – |
| GBAEval | 43.8% | – |
| ALE-Bench | 1323.0 | – |
| Vending-Bench 2 | 10936.8 | – |
| Blueprint-Bench 2 | 24.5% | – |
| Terminal-Bench 4.0 (AA) | – | 52.0% |
| AutomationBench | – | 68.1% |
| GDP.pdf | – | 30.6% |
| AA-Omniscience: accuracy | – | 41.1% |
| AA-Omniscience: non-hallucination | – | 73.5% |
| AA-Briefcase v1.1 | – | 1659 |
Data as of 2026-10-13. Best configuration of each model; every score links to its source on the model pages.
Claude Opus 4.7 vs Muse Wonder: questions
- Is Claude Opus 4.7 better than Muse Wonder?
- Muse Wonder (max) leads on quality: 66.3 vs 63.7. The BenchLeader Index combines every independent quality benchmark; Muse Wonder (max) is ahead overall as of 2026-10-13, but check the category scores for your use.
- Which is cheaper, Claude Opus 4.7 or Muse Wonder?
- Muse Wonder is cheaper: $8.00 against $10.00 per million tokens, blended at three input tokens per output token.
- Which is faster, Claude Opus 4.7 or Muse Wonder?
- Muse Wonder streams faster: 85 against 80 output tokens per second.
- Which has the larger context window?
- Muse Wonder accepts more context: 1.0M against 1M tokens.