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ModelCap

Model decision surface

Compare AI models

Start with Ling 3.0 Flash VL and Kimi K2.7 Code, 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

Ling 3.0 Flash VL vs Kimi K2.7 Code

Live dataset updated 9/13/2026, 2:40:29 PM UTC

Open 1200×630 evidence receipt
Factual comparison of Ling 3.0 Flash VL and Kimi K2.7 Code
Field
Kimi K2.7 Code

Moonshot AI

ModelCap position#55#52
Index score58.059.1
EvidenceMeasured1 public benchmark observation across 1 boardMeasured2 public benchmark observations across 2 boards
Input / 1M$0.06$0.71
Output / 1M$0.18$3.50
Pricing statusfreshfresh
Context131K262K
Providers114
Weight accessOpen weightsRestricted license

Decision facts

  • Ling 3.0 Flash VL is #55; Kimi K2.7 Code is #52 on the same current language board.
  • Index scores are 58.0 for Ling 3.0 Flash VL and 59.1 for Kimi K2.7 Code. 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 $0.18 for Ling 3.0 Flash VL and $3.50 for Kimi K2.7 Code. For 1,000 requests with 2,000 input and 500 output tokens each (2M input + 0.5M output), the listed-rate estimate is $0.21 for Ling 3.0 Flash VL versus $3.17 for Kimi K2.7 Code. Ling 3.0 Flash VL costs 93.4% 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 131,072 tokens for Ling 3.0 Flash VL and 262,144 for Kimi K2.7 Code.
  • Weight access differs: Ling 3.0 Flash VL is open; Kimi K2.7 Code is restricted.
  • ModelCap currently lists 1 providers for Ling 3.0 Flash VL and 14 for Kimi K2.7 Code.

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.