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ModelCap

Model decision surface

Compare AI models

Start with Gemini 4 Argon 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

Gemini 4 Argon vs Kimi K3

Live dataset updated 10/13/2026, 6:04:47 PM UTC

Open 1200×630 evidence receipt
Factual comparison of Gemini 4 Argon and Kimi K3
Field
Kimi K3

Moonshot AI

ModelCap position#33#9
Index score73.082.0
EvidenceEstimated1 reported rows against measured corpus ladders (72%); publisher-corpus-prior over 211 held-out anchors (28%); shrunk 3.7 toward the measured corpusMeasured5 public benchmark observations across 5 boards
Input / 1M$2.00$0.73
Output / 1M$10.00$10.00
Pricing statusfreshfresh
Context1M1M
Providers220
Weight accessNo linked weightsRestricted license

Decision facts

  • Gemini 4 Argon is #33; Kimi K3 is #9 on the same current language board.
  • Index scores are 73.0 for Gemini 4 Argon and 82.0 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: Gemini 4 Argon is Estimated; Kimi K3 is Measured.
  • Listed output price per 1M tokens is $10.00 for Gemini 4 Argon and $10.00 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 $9.00 for Gemini 4 Argon versus $6.46 for Kimi K3. Kimi K3 costs 28.2% 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 1,048,576 tokens for Gemini 4 Argon and 1,048,576 for Kimi K3.
  • Weight access differs: Gemini 4 Argon is none; Kimi K3 is restricted.
  • ModelCap currently lists 2 providers for Gemini 4 Argon and 20 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.