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ModelCap

Model decision surface

Compare AI models

Start with Ling-3.0-flash and Qwen3.5-122B-A10B, 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 vs Qwen3.5-122B-A10B

Live dataset updated 8/17/2026, 11:13:20 PM UTC

Open 1200×630 evidence receipt
Factual comparison of Ling-3.0-flash and Qwen3.5-122B-A10B
Field
Ling-3.0-flash

InclusionAI

ModelCap position#42#41
Index score53.053.6
EvidenceMeasured1 public benchmark observation across 1 boardMeasured3 public benchmark observations across 3 boards
Input / 1M$0.021$0.29
Output / 1M$0.063$2.40
Pricing statusfreshfresh
Context262K262K
Providers25
Weight accessOpen weightsOpen weights

Decision facts

  • Ling-3.0-flash is #42; Qwen3.5-122B-A10B is #41 on the same current language board.
  • Index scores are 53.0 for Ling-3.0-flash and 53.6 for Qwen3.5-122B-A10B.
  • Both positions use Measured evidence.
  • Listed output price per 1M tokens is $0.06 for Ling-3.0-flash and $2.40 for Qwen3.5-122B-A10B.
  • Published context is 262,144 tokens for Ling-3.0-flash and 262,144 for Qwen3.5-122B-A10B.
  • ModelCap currently lists 2 providers for Ling-3.0-flash and 5 for Qwen3.5-122B-A10B.

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.