Skip to content
ModelCap

Model decision surface

Compare AI models

Start with Ling-3.0-flash and Qwen3 235B A22B Instruct 2507, 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 235B A22B Instruct 2507

Live dataset updated 9/3/2026, 3:17:25 AM UTC

Open 1200×630 evidence receipt
Factual comparison of Ling-3.0-flash and Qwen3 235B A22B Instruct 2507
Field
Ling-3.0-flash

InclusionAI

ModelCap position#49#50
Index score51.750.2
EvidenceMeasured1 public benchmark observation across 1 boardMeasured4 public benchmark observations across 4 boards
Input / 1M$0.021$0.087
Output / 1M$0.063$0.35
Pricing statusfreshfresh
Context262K262K
Providers210
Weight accessOpen weightsOpen weights

Decision facts

  • Ling-3.0-flash is #49; Qwen3 235B A22B Instruct 2507 is #50 on the same current language board.
  • Index scores are 51.7 for Ling-3.0-flash and 50.2 for Qwen3 235B A22B Instruct 2507.
  • Both positions use Measured evidence.
  • Listed output price per 1M tokens is $0.06 for Ling-3.0-flash and $0.35 for Qwen3 235B A22B Instruct 2507.
  • Published context is 262,144 tokens for Ling-3.0-flash and 262,144 for Qwen3 235B A22B Instruct 2507.
  • ModelCap currently lists 2 providers for Ling-3.0-flash and 10 for Qwen3 235B A22B Instruct 2507.

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.