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ModelCap

Model decision surface

Compare AI models

Start with GPT-5.4 Nano and GPT-6 Astra, 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 GPT-6 Astra

Live dataset updated 10/24/2026, 7:29:10 PM UTC

Open 1200×630 evidence receipt
Factual comparison of GPT-5.4 Nano and GPT-6 Astra
Field
ModelCap position#111#13
Index score51.979.9
EvidenceMeasured3 public benchmark observations across 3 boardsMeasured5 public benchmark observations across 5 boards
Input / 1M$0.20$10.00
Output / 1M$1.25$50.00
Pricing statusfreshfresh
Context400K1M
Providers23
Weight accessNo linked weightsNo linked weights

Decision facts

  • GPT-5.4 Nano is #111; GPT-6 Astra is #13 on the same current language board.
  • Index scores are 51.9 for GPT-5.4 Nano and 79.9 for GPT-6 Astra. 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 $1.25 for GPT-5.4 Nano and $50.00 for GPT-6 Astra. 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 $45.00 for GPT-6 Astra. GPT-5.4 Nano costs 97.7% 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 1,050,000 for GPT-6 Astra.
  • ModelCap currently lists 2 providers for GPT-5.4 Nano and 3 for GPT-6 Astra.

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.