Model decision surface
Compare AI models
Start with Kimi K2.7 Code and Laguna XS 2.1, 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
Kimi K2.7 Code vs Laguna XS 2.1
Live dataset updated 9/15/2026, 9:19:37 PM UTC
Open 1200×630 evidence receipt| Field | Kimi K2.7 Code Moonshot AI | Laguna XS 2.1 Poolside |
|---|---|---|
| ModelCap position | #55 | #81 |
| Index score | 58.5 | 50.8 |
| Evidence | Measured2 public benchmark observations across 2 boards | Estimated3 reported rows against measured corpus ladders (27%); global-corpus-prior over 194 held-out anchors (73%); shrunk 3.7 up toward the measured corpus |
| Input / 1M | $0.71 | $0.06 |
| Output / 1M | $3.50 | $0.12 |
| Pricing status | fresh | fresh |
| Context | 262K | 262K |
| Providers | 14 | 1 |
| Weight access | Restricted license | Restricted license |
Decision facts
- Kimi K2.7 Code is #55; Laguna XS 2.1 is #81 on the same current language board.
- Index scores are 58.5 for Kimi K2.7 Code and 50.8 for Laguna XS 2.1. Their published uncertainty intervals overlap, so the rank difference alone does not establish a reliable capability advantage for your workload.
- Evidence differs: Kimi K2.7 Code is Measured; Laguna XS 2.1 is Estimated.
- Listed output price per 1M tokens is $3.50 for Kimi K2.7 Code and $0.12 for Laguna XS 2.1. For 1,000 requests with 2,000 input and 500 output tokens each (2M input + 0.5M output), the listed-rate estimate is $3.17 for Kimi K2.7 Code versus $0.18 for Laguna XS 2.1. Laguna XS 2.1 costs 94.3% 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 262,144 tokens for Kimi K2.7 Code and 262,144 for Laguna XS 2.1.
- ModelCap currently lists 14 providers for Kimi K2.7 Code and 1 for Laguna XS 2.1.
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.