Model decision surface
Compare AI models
Start with Claude Opus 5.5 and Kimi K3.1 Pro, 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 Opus 5.5 vs Kimi K3.1 Pro
Live dataset updated 10/23/2026, 7:44:34 PM UTC
Open 1200×630 evidence receipt| Field | Claude Opus 5.5 Anthropic | Kimi K3.1 Pro Moonshot AI |
|---|---|---|
| ModelCap position | #1 | #21 |
| Index score | 87.4 | 78.6 |
| Evidence | Measured4 public benchmark observations across 4 boards | Estimated1 reported rows against measured corpus ladders (61%); publisher-corpus-prior over 211 held-out anchors (39%); shrunk 4 toward the measured corpus |
| Input / 1M | $4.00 | $2.00 |
| Output / 1M | $20.00 | $10.00 |
| Pricing status | fresh | fresh |
| Context | 1M | 1M |
| Providers | 5 | 1 |
| Weight access | No linked weights | No linked weights |
Decision facts
- Claude Opus 5.5 is #1; Kimi K3.1 Pro is #21 on the same current language board.
- Index scores are 87.4 for Claude Opus 5.5 and 78.6 for Kimi K3.1 Pro. Their published uncertainty intervals overlap, so the rank difference alone does not establish a reliable capability advantage for your workload.
- Evidence differs: Claude Opus 5.5 is Measured; Kimi K3.1 Pro is Estimated.
- Listed output price per 1M tokens is $20.00 for Claude Opus 5.5 and $10.00 for Kimi K3.1 Pro. For 1,000 requests with 2,000 input and 500 output tokens each (2M input + 0.5M output), the listed-rate estimate is $18.00 for Claude Opus 5.5 versus $9.00 for Kimi K3.1 Pro. Kimi K3.1 Pro 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 Opus 5.5 and 1,048,576 for Kimi K3.1 Pro.
- ModelCap currently lists 5 providers for Claude Opus 5.5 and 1 for Kimi K3.1 Pro.
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.