Model decision surface
Compare AI models
Start with Claude Sonnet 5.5 and Muse Wonder, or choose any two current ranked language models. Compare capability evidence, price, context, provider availability, and weight access without pretending one field decides every use case.
Current public data
Claude Sonnet 5.5 vs Muse Wonder
Live dataset updated 10/12/2026, 5:49:31 PM UTC
Open 1200×630 evidence receipt| Field | Claude Sonnet 5.5 Anthropic | Muse Wonder Meta |
|---|---|---|
| ModelCap position | #14 | #6 |
| Index score | 80.8 | 83.0 |
| Evidence | Measured3 public benchmark observations across 3 boards | Estimated1 reported rows against measured corpus ladders (69%); publisher-corpus-prior over 211 held-out anchors (31%); shrunk 0.2 up toward the measured corpus |
| Input / 1M | $2.00 | $4.00 |
| Output / 1M | $10.00 | $20.00 |
| Pricing status | fresh | fresh |
| Context | 1M | 1M |
| Providers | 5 | 1 |
| Weight access | No linked weights | No linked weights |
Decision facts
- Claude Sonnet 5.5 is #14; Muse Wonder is #6 on the same current language board.
- Index scores are 80.8 for Claude Sonnet 5.5 and 83.0 for Muse Wonder. Their published uncertainty intervals overlap, so the rank difference alone does not establish a reliable capability advantage for your workload.
- Evidence differs: Claude Sonnet 5.5 is Measured; Muse Wonder is Estimated.
- Listed output price per 1M tokens is $10.00 for Claude Sonnet 5.5 and $20.00 for Muse Wonder. For 1,000 requests with 2,000 input and 500 output tokens each (2M input + 0.5M output), the listed-rate estimate is $9.00 for Claude Sonnet 5.5 versus $18.00 for Muse Wonder. Claude Sonnet 5.5 costs 50.0% less in this scenario. This excludes caching, batch discounts, prompt-length tiers, tool charges and retries; verify the selected endpoint before budgeting.
- Published context is 1,000,000 tokens for Claude Sonnet 5.5 and 1,048,576 for Muse Wonder.
- ModelCap currently lists 5 providers for Claude Sonnet 5.5 and 1 for Muse Wonder.
These are separate published fields, not a synthetic winner. ModelCap does not collapse price, access, context, and capability evidence into a hidden recommendation score.
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Each comparison page is a permanent, shareable URL with the same live figures as this tool: ModelCap Index position, API pricing, context window, provider count, weight access and every shared benchmark board.