Model decision surface
Compare AI models
Start with Gemini 3.1 Pro Preview 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
Gemini 3.1 Pro Preview vs Muse Wonder
Live dataset updated 10/12/2026, 5:49:31 PM UTC
Open 1200×630 evidence receipt| Field | Gemini 3.1 Pro Preview | Muse Wonder Meta |
|---|---|---|
| ModelCap position | #8 | #6 |
| Index score | 82.2 | 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 | $12.00 | $20.00 |
| Pricing status | fresh | fresh |
| Context | 1M | 1M |
| Providers | 2 | 1 |
| Weight access | No linked weights | No linked weights |
Decision facts
- Gemini 3.1 Pro Preview is #8; Muse Wonder is #6 on the same current language board.
- Index scores are 82.2 for Gemini 3.1 Pro Preview 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: Gemini 3.1 Pro Preview is Measured; Muse Wonder is Estimated.
- Listed output price per 1M tokens is $12.00 for Gemini 3.1 Pro Preview 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 $10.00 for Gemini 3.1 Pro Preview versus $18.00 for Muse Wonder. Gemini 3.1 Pro Preview costs 44.4% 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 1,048,576 tokens for Gemini 3.1 Pro Preview and 1,048,576 for Muse Wonder.
- ModelCap currently lists 2 providers for Gemini 3.1 Pro Preview 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.