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Claude Sonnet 4.5 vs GPT-5.6 Luna

Detailed pricing comparison and cost analysis.

Updated September 2026

Cost Simulator

Claude Sonnet 4.5 Cost
$6.00
GPT-5.6 Luna Cost
$0.44
GPT-5.6 Luna is 93% cheaper
FeatureClaude Sonnet 4.5GPT-5.6 Luna
ProviderAnthropicOpenAI
Input Price (1M)$3.00$0.20
Output Price (1M)$15.00$1.20
Context Window200,0001,000,000

Verdict

Claude Sonnet 4.5 costs $3.00 per 1M input tokens and $15.00 per 1M output tokens. GPT-5.6 Luna costs $0.20 per 1M input tokens and $1.20 per 1M output tokens. GPT-5.6 Luna is 93% cheaper on input tokens than Claude Sonnet 4.5. For output tokens, GPT-5.6 Luna is the more affordable option at $1.20/1M vs $15.00.

On context window, GPT-5.6 Luna supports 1,000,000 tokens — meaning it can fit more conversation history, documents, or code in a single request. This matters for RAG pipelines, long document analysis, and agentic workflows where context builds up over many turns.

When to choose Claude Sonnet 4.5

  • ✓ You are already integrated with Anthropic

When to choose GPT-5.6 Luna

  • ✓ You need the lowest input token cost ($ 0.20/1M)
  • ✓ Your workload is output-heavy — GPT-5.6 Luna generates text cheaper
  • ✓ You need a larger context window (1,000,000 tokens)
  • ✓ You are already integrated with OpenAI

Use the calculator above to simulate your specific workload and find the exact break-even point. For most applications, the cheapest model is the one that minimises your total monthly bill given your input-to-output token ratio.

Frequently Asked Questions

Is Claude Sonnet 4.5 cheaper than GPT-5.6 Luna?

GPT-5.6 Luna is cheaper on input tokens at $0.20/1M vs $3.00/1M for Claude Sonnet 4.5 — a 93% saving.

What is the context window of Claude Sonnet 4.5 vs GPT-5.6 Luna?

Claude Sonnet 4.5 has a 200,000-token context window. GPT-5.6 Luna has a 1,000,000-token context window. GPT-5.6 Luna supports the larger context, suitable for longer documents and agentic workflows.

Which model is better: Claude Sonnet 4.5 or GPT-5.6 Luna?

The best choice depends on your use case. For cost efficiency on input tokens, GPT-5.6 Luna is the cheaper option. For maximum context length, GPT-5.6 Luna supports 1,000,000 tokens. Use the comparison table above to find the right fit for your workload.