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ModelCap

Model decision surface

Compare AI models

Start with LongCat 2.0 and Kimi K3, 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

LongCat 2.0 vs Kimi K3

Live dataset updated 9/9/2026, 8:46:14 PM UTC

Open 1200×630 evidence receipt
Factual comparison of LongCat 2.0 and Kimi K3
Field
Kimi K3

Moonshot AI

ModelCap position#10#6
Index score79.082.6
EvidenceEstimatedglobal-corpus-prior over 182 held-out anchors (7%); launch card against 4 resolved peers on 6 rows (93%); no cross-lab optimism probe available; shrunk 2 toward the measured corpusMeasured6 public benchmark observations across 6 boards
Input / 1M$0.30$3.00
Output / 1M$1.20$15.00
Pricing statusfreshfresh
Context1M1M
Providers116
Weight accessOpen weightsRestricted license

Decision facts

  • LongCat 2.0 is #10; Kimi K3 is #6 on the same current language board.
  • Index scores are 79.0 for LongCat 2.0 and 82.6 for Kimi K3. Their published uncertainty intervals overlap, so the rank difference alone does not establish a reliable capability advantage for your workload.
  • Evidence differs: LongCat 2.0 is Estimated; Kimi K3 is Measured.
  • Listed output price per 1M tokens is $1.20 for LongCat 2.0 and $15.00 for Kimi K3. For 1,000 requests with 2,000 input and 500 output tokens each (2M input + 0.5M output), the listed-rate estimate is $1.20 for LongCat 2.0 versus $13.50 for Kimi K3. LongCat 2.0 costs 91.1% 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 1,048,756 tokens for LongCat 2.0 and 1,048,576 for Kimi K3.
  • Weight access differs: LongCat 2.0 is open; Kimi K3 is restricted.
  • ModelCap currently lists 1 providers for LongCat 2.0 and 16 for Kimi K3.

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.