Skip to content
ModelCap

Model decision surface

Compare AI models

Start with Qwen3 235B A22B Thinking 2507 and Qwen3.5 397B A17B, 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 235B A22B Thinking 2507 vs Qwen3.5 397B A17B

Live dataset updated 9/22/2026, 10:37:09 PM UTC

Open 1200×630 evidence receipt
Factual comparison of Qwen3 235B A22B Thinking 2507 and Qwen3.5 397B A17B
Field
ModelCap position#89#42
Index score55.469.7
EvidenceMeasured2 public benchmark observations across 2 boardsMeasured3 public benchmark observations across 3 boards
Input / 1M$0.23$0.55
Output / 1M$2.30$3.50
Pricing statusfreshfresh
Context131K262K
Providers310
Weight accessOpen weightsOpen weights

Decision facts

  • Qwen3 235B A22B Thinking 2507 is #89; Qwen3.5 397B A17B is #42 on the same current language board.
  • Index scores are 55.4 for Qwen3 235B A22B Thinking 2507 and 69.7 for Qwen3.5 397B A17B. Their published uncertainty intervals do not overlap, but the aggregate Index does not predict performance on every task; compare the relevant benchmark configurations before choosing.
  • Both positions use Measured evidence.
  • Listed output price per 1M tokens is $2.30 for Qwen3 235B A22B Thinking 2507 and $3.50 for Qwen3.5 397B A17B. For 1,000 requests with 2,000 input and 500 output tokens each (2M input + 0.5M output), the listed-rate estimate is $1.61 for Qwen3 235B A22B Thinking 2507 versus $2.85 for Qwen3.5 397B A17B. Qwen3 235B A22B Thinking 2507 costs 43.5% 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 Qwen3 235B A22B Thinking 2507 and 262,144 for Qwen3.5 397B A17B.
  • ModelCap currently lists 3 providers for Qwen3 235B A22B Thinking 2507 and 10 for Qwen3.5 397B A17B.

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.