Model decision surface
Compare AI models
Start with Kimi K2 Thinking and Laguna S 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 Thinking vs Laguna S 2.1
Live dataset updated 9/9/2026, 8:46:14 PM UTC
Open 1200×630 evidence receipt| Field | Kimi K2 Thinking Moonshot AI | Laguna S 2.1 Poolside |
|---|---|---|
| ModelCap position | #42 | #40 |
| Index score | 62.3 | 63.3 |
| Evidence | Measured2 public benchmark observations across 2 boards | Estimated5 reported rows against measured corpus ladders (67%); global-corpus-prior over 182 held-out anchors (33%); shrunk 4.8 toward the measured corpus |
| Input / 1M | $0.60 | $0.09 |
| Output / 1M | $2.50 | $0.18 |
| Pricing status | fresh | fresh |
| Context | 262K | 1M |
| Providers | 2 | 1 |
| Weight access | Restricted license | Restricted license |
Decision facts
- Kimi K2 Thinking is #42; Laguna S 2.1 is #40 on the same current language board.
- Index scores are 62.3 for Kimi K2 Thinking and 63.3 for Laguna S 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 Thinking is Measured; Laguna S 2.1 is Estimated.
- Listed output price per 1M tokens is $2.50 for Kimi K2 Thinking and $0.18 for Laguna S 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 $2.45 for Kimi K2 Thinking versus $0.27 for Laguna S 2.1. Laguna S 2.1 costs 89.0% 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 262,144 tokens for Kimi K2 Thinking and 1,048,576 for Laguna S 2.1.
- ModelCap currently lists 2 providers for Kimi K2 Thinking and 1 for Laguna S 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.