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ModelCap

Model decision surface

Compare AI models

Start with Claude Haiku 4.5 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

Claude Haiku 4.5 vs Laguna XS 2.1

Live dataset updated 9/9/2026, 9:50:24 PM UTC

Open 1200×630 evidence receipt
Factual comparison of Claude Haiku 4.5 and Laguna XS 2.1
Field
ModelCap position#56#60
Index score56.454.9
EvidenceMeasured3 public benchmark observations across 3 boardsEstimated3 reported rows against measured corpus ladders (30%); global-corpus-prior over 180 held-out anchors (70%); shrunk 1.3 toward the measured corpus
Input / 1M$1.00$0.06
Output / 1M$5.00$0.12
Pricing statusfreshfresh
Context200K262K
Providers41
Weight accessAPI onlyRestricted license

Decision facts

  • Claude Haiku 4.5 is #56; Laguna XS 2.1 is #60 on the same current language board.
  • Index scores are 56.4 for Claude Haiku 4.5 and 54.9 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: Claude Haiku 4.5 is Measured; Laguna XS 2.1 is Estimated.
  • Listed output price per 1M tokens is $5.00 for Claude Haiku 4.5 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 $4.50 for Claude Haiku 4.5 versus $0.18 for Laguna XS 2.1. Laguna XS 2.1 costs 96.0% 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 200,000 tokens for Claude Haiku 4.5 and 262,144 for Laguna XS 2.1.
  • Weight access differs: Claude Haiku 4.5 is none; Laguna XS 2.1 is restricted.
  • ModelCap currently lists 4 providers for Claude Haiku 4.5 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.

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.