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ModelCap

Model decision surface

Compare AI models

Start with Claude Haiku 5.5 and Claude Sonnet 5.5, 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 5.5 vs Claude Sonnet 5.5

Live dataset updated 10/14/2026, 6:29:17 AM UTC

Open 1200×630 evidence receipt
Factual comparison of Claude Haiku 5.5 and Claude Sonnet 5.5
Field
ModelCap position#59#16
Index score63.579.1
EvidenceMeasured1 reported rows against measured corpus ladders (24%); publisher-corpus-prior over 213 held-out anchors (14%); measured predecessor anthropic/claude-haiku-4.5 less the succession penalty (51%); 1 specialist-board observation at 2.5% support (11%); shrunk 2.3 up toward the measured corpusMeasured3 public benchmark observations across 3 boards
Input / 1M$0.10$2.00
Output / 1M$0.50$10.00
Pricing statusfreshfresh
Context1M1M
Providers55
Weight accessNo linked weightsNo linked weights

Decision facts

  • Claude Haiku 5.5 is #59; Claude Sonnet 5.5 is #16 on the same current language board.
  • Index scores are 63.5 for Claude Haiku 5.5 and 79.1 for Claude Sonnet 5.5. Their published uncertainty intervals overlap, so the rank difference alone does not establish a reliable capability advantage for your workload.
  • Both positions use Measured evidence.
  • Listed output price per 1M tokens is $0.50 for Claude Haiku 5.5 and $10.00 for Claude Sonnet 5.5. For 1,000 requests with 2,000 input and 500 output tokens each (2M input + 0.5M output), the listed-rate estimate is $0.45 for Claude Haiku 5.5 versus $9.00 for Claude Sonnet 5.5. Claude Haiku 5.5 costs 95.0% 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 Haiku 5.5 and 1,000,000 for Claude Sonnet 5.5.

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.