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ModelCap

Model decision surface

Compare AI models

Start with Qwen3.5-9B and Qwen3.8 27B, 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

Qwen3.5-9B vs Qwen3.8 27B

Live dataset updated 10/2/2026, 12:44:27 PM UTC

Open 1200×630 evidence receipt
Factual comparison of Qwen3.5-9B and Qwen3.8 27B
Field
ModelCap position#95#39
Index score54.968.9
EvidenceMeasured1 public benchmark observation across 1 boardMeasured5 public benchmark observations across 5 boards
Input / 1M$0.10$0.42
Output / 1M$0.15$3.00
Pricing statusfreshfresh
Context262K1M
Providers617
Weight accessOpen weightsOpen weights

Decision facts

  • Qwen3.5-9B is #95; Qwen3.8 27B is #39 on the same current language board.
  • Index scores are 54.9 for Qwen3.5-9B and 68.9 for Qwen3.8 27B. 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 $0.15 for Qwen3.5-9B and $3.00 for Qwen3.8 27B. For 1,000 requests with 2,000 input and 500 output tokens each (2M input + 0.5M output), the listed-rate estimate is $0.27 for Qwen3.5-9B versus $2.34 for Qwen3.8 27B. Qwen3.5-9B costs 88.2% 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 262,144 tokens for Qwen3.5-9B and 1,000,000 for Qwen3.8 27B.
  • ModelCap currently lists 6 providers for Qwen3.5-9B and 17 for Qwen3.8 27B.

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.