Model comparison

GPT-5.6 Cyber vs Claude Opus 4.7

Compare GPT-5.6 Cyber vs Claude Opus 4.7 API pricing: input/output token costs, cache pricing, context windows, workload estimates, and routing fit.

GPT-5.6 Cyber

openai · gpt-5.6-cyber

Input
$12.5
Output
$75
Context
400K

Claude Opus 4.7

anthropic · claude-opus-4-7

Input
$5
Output
$25
Context
1M

Quick take

Claude Opus 4.7 has the lower input price at $5 per 1M input tokens. Claude Opus 4.7 is cheaper for the example blended workload below. Claude Opus 4.7 has the larger context window at 1M tokens.

Choose GPT-5.6 Cyber if...

  • GPT-5.6 Cyber is a reasonable pick when its provider, latency, or integration path fits your stack better.

Choose Claude Opus 4.7 if...

  • Claude Opus 4.7 is the better default for cost-sensitive traffic and repeated high-volume calls.
  • Claude Opus 4.7 is safer for long documents, repository analysis, and RAG prompts because it has the larger context window.

Example workload cost

Estimates use input tokens plus 20% output tokens. They exclude provider discounts, cache hits, and tool/search surcharges.

Workload GPT-5.6 Cyber Claude Opus 4.7 Cheaper
1M input + 200K output $27.50 $10.00 Claude Opus 4.7
10M input + 2M output $275.00 $100.00 Claude Opus 4.7
100M input + 20M output $2,750.00 $1,000.00 Claude Opus 4.7

Context, output, and capability fit

Claude Opus 4.7 provides the larger context window. Check max output separately when the task needs long reports, code generation, or full-document rewrites.

GPT-5.6 Cyber max output
128K
Claude Opus 4.7 max output
128K
GPT-5.6 Cyber features
prompt caching, function calling, vision
Claude Opus 4.7 features
prompt caching, function calling, vision

Risk notes for GPT-5.6 Cyber

  • High output price: cap max tokens for verbose generation workloads.

Risk notes for Claude Opus 4.7

  • High output price: cap max tokens for verbose generation workloads.

Routing tags

frontierpremiumreasoningcodingagentslong-contextmultimodalcache-friendlycybersecuritylimited-availabilityrag

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