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ModelCap

Model decision surface

Compare AI models

Start with Qwen3 Coder Next and Qwen3 VL 32B Instruct, 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

Qwen3 Coder Next vs Qwen3 VL 32B Instruct

Live dataset updated 10/11/2026, 3:39:45 PM UTC

Open 1200×630 evidence receipt
Factual comparison of Qwen3 Coder Next and Qwen3 VL 32B Instruct
Field
ModelCap position#76#154
Index score60.441.7
EvidenceEstimated3 reported rows against measured corpus ladders (66%); publisher-corpus-prior over 211 held-out anchors (34%); shrunk 4.5 toward the measured corpusEstimated4 reported rows against measured corpus ladders (51%); publisher-corpus-prior over 211 held-out anchors (50%); shrunk 9.8 up toward the measured corpus
Input / 1M$0.12Unavailable
Output / 1M$0.80Unavailable
Pricing statusfreshempty
Context262K131K
Providers10
Weight accessOpen weightsOpen weights

Decision facts

  • Qwen3 Coder Next is #76; Qwen3 VL 32B Instruct is #154 on the same current language board.
  • Index scores are 60.4 for Qwen3 Coder Next and 41.7 for Qwen3 VL 32B Instruct. Their published uncertainty intervals overlap, so the rank difference alone does not establish a reliable capability advantage for your workload.
  • Both positions use Estimated evidence.
  • Published context is 262,144 tokens for Qwen3 Coder Next and 131,072 for Qwen3 VL 32B Instruct.
  • ModelCap currently lists 1 providers for Qwen3 Coder Next and 0 for Qwen3 VL 32B Instruct.

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.