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ModelCap

Model decision surface

Compare AI models

Start with GPT-5.4 Nano and Qwen3.8 Flash, 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

GPT-5.4 Nano vs Qwen3.8 Flash

Live dataset updated 9/9/2026, 9:50:24 PM UTC

Open 1200×630 evidence receipt
Factual comparison of GPT-5.4 Nano and Qwen3.8 Flash
Field
ModelCap position#71#62
Index score51.754.1
EvidenceMeasured4 public benchmark observations across 4 boardsEstimatedpublisher-corpus-prior over 180 held-out anchors (18%); measured predecessor qwen/qwen3.5-flash-02-23 less the succession penalty (65%); launch card against 4 resolved peers on 9 rows (17%); exceeds every named peer on 7 of 9 rows; optimism haircut 0 from cross-lab-probe; shrunk 0.7 toward the measured corpus
Input / 1M$0.20$0.15
Output / 1M$1.25$0.47
Pricing statusfreshfresh
Context400K1M
Providers22
Weight accessAPI onlyRestricted license

Decision facts

  • GPT-5.4 Nano is #71; Qwen3.8 Flash is #62 on the same current language board.
  • Index scores are 51.7 for GPT-5.4 Nano and 54.1 for Qwen3.8 Flash. Their published uncertainty intervals overlap, so the rank difference alone does not establish a reliable capability advantage for your workload.
  • Evidence differs: GPT-5.4 Nano is Measured; Qwen3.8 Flash is Estimated.
  • Listed output price per 1M tokens is $1.25 for GPT-5.4 Nano and $0.47 for Qwen3.8 Flash. For 1,000 requests with 2,000 input and 500 output tokens each (2M input + 0.5M output), the listed-rate estimate is $1.02 for GPT-5.4 Nano versus $0.53 for Qwen3.8 Flash. Qwen3.8 Flash costs 47.8% 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 400,000 tokens for GPT-5.4 Nano and 1,000,000 for Qwen3.8 Flash.
  • Weight access differs: GPT-5.4 Nano is none; Qwen3.8 Flash is restricted.

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.