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ModelCap

Model decision surface

Compare AI models

Start with GPT-6 Astra 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-6 Astra vs Qwen3.8 Flash

Live dataset updated 9/10/2026, 1:00:55 AM UTC

Open 1200×630 evidence receipt
Factual comparison of GPT-6 Astra and Qwen3.8 Flash
Field
ModelCap position#1#14
Index score93.778.0
EvidenceMeasured4 public benchmark observations across 4 boardsMeasured1 public benchmark observation across 1 board
Input / 1M$10.00$0.15
Output / 1M$50.00$0.47
Pricing statusfreshfresh
Context1M1M
Providers22
Weight accessAPI onlyRestricted license

Decision facts

  • GPT-6 Astra is #1; Qwen3.8 Flash is #14 on the same current language board.
  • Index scores are 93.7 for GPT-6 Astra and 78.0 for Qwen3.8 Flash. 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 $50.00 for GPT-6 Astra 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 $45.00 for GPT-6 Astra versus $0.53 for Qwen3.8 Flash. Qwen3.8 Flash costs 98.8% 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 1,050,000 tokens for GPT-6 Astra and 1,000,000 for Qwen3.8 Flash.
  • Weight access differs: GPT-6 Astra 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.