Quick Verdict
| Need | Better first pick | Why |
|---|---|---|
| Lowest raw token cost | GPT-5.6 Luna | OpenAI’s July 30 cut made Luna the clear volume route |
| Coding and code review | Claude Sonnet 5 | The premium can pay back when it reduces failed patches or review time |
| Balanced OpenAI agent work | GPT-5.6 Terra | More capability than Luna without defaulting to Sol |
| Broad GPT ecosystem | GPT-5.6 | Best fit for teams already standardized on OpenAI tools and model behavior |
| Cost-control architecture | Both | Route routine work to Luna and escalate only the requests that need Sonnet |
The live table, chart, and calculator above use the current pricing.json rates. They replace the stale GPT-5.4 comparison that previously occupied this page.
What Changed
OpenAI cut GPT-5.6 Luna’s standard API rates by 80% on July 30, 2026, while leaving Sol unchanged and reducing Terra’s standard rates by 20%. That moved Luna from a modestly cheaper GPT route to a volume model that should be tested against utility and mid-tier APIs, not only against previous OpenAI flagships.
Claude Sonnet 5 remains on introductory pricing through August 31, with standard pricing scheduled to begin September 1. Teams comparing the two models should therefore save a second cost scenario using the future Sonnet rates before committing to a long-running workload.
See the OpenAI pricing guide for the full GPT ladder and the Anthropic pricing page for current Claude rates.
Capability and Cost Tradeoffs
| Factor | GPT-5.6 Luna | Claude Sonnet 5 | Why it matters |
|---|---|---|---|
| Raw token economics | Clear advantage | Premium route | High-volume traffic magnifies the gap |
| Context window | Large-context route | Large-context route | Retrieval quality matters more than headline capacity |
| Coding and review | Suitable when outputs are easy to verify | Strong candidate for harder coding work | Developer correction time can outweigh token spend |
| Escalation path | Terra, then Sol | Opus 5 | A router avoids paying flagship rates on every call |
| Ecosystem | OpenAI SDKs and product integrations | Claude-oriented coding and document workflows | Migration effort belongs in total cost |
Sticker price is only the first filter. The useful metric is cost per accepted result: tokens, retries, tool calls, latency, and human correction combined. Luna wins when the workflow is defined and cheap to verify. Sonnet can win when a failed output is expensive.
Workload Guidance
| Workload | First route | Escalation route |
|---|---|---|
| Classification or extraction | GPT-5.6 Luna | GPT-5.6 Terra |
| Support draft | GPT-5.6 Luna | Claude Sonnet 5 |
| Code generation with strong tests | GPT-5.6 Luna | Claude Sonnet 5 |
| Repository-scale code review | Claude Sonnet 5 | Claude Opus 5 or GPT-5.6 Sol |
| Multi-step OpenAI agent | GPT-5.6 Terra | GPT-5.6 Sol |
| Long-document synthesis | Run an A/B evaluation | Keep the model with lower correction cost |
Start with a representative test set, not a few impressive prompts. Record accepted outputs, retries, output length, tool failures, latency, and reviewer minutes for every route.
Cost Controls Before You Switch
Keep stable instructions and tool schemas at the beginning of the prompt so cached reads can reduce repeat-input cost. Retrieve only the document or code sections needed for the current step instead of repeatedly sending the full context window.
Pin model IDs, cap output tokens, and define escalation rules before production rollout. A cheap default model can still become expensive if it generates long answers or triggers repeated tool loops.
Use the token cost calculator to model your own input/output mix, then compare the broader vendor tradeoff in OpenAI vs Anthropic API pricing. Current OpenAI rates are also available on the OpenAI pricing page.
If direct GPT or Claude pricing is still too high for routine traffic, compare open-model routes on Novita AI before sending low-risk work to a premium model.
FAQ
Is GPT-5.6 Luna cheaper than Claude Sonnet 5?
Yes on current raw API rates. Luna’s advantage is largest in high-volume, repeatable workflows where its outputs are easy to verify.
Is Claude Sonnet 5 still worth testing?
Yes. For coding, review, and complex tool use, fewer retries or less human correction can repay a higher token bill.
What happens when Sonnet 5 introductory pricing ends?
Anthropic says standard pricing begins September 1, 2026. Model both the current and scheduled rates before signing off on a workload budget.
Should I use GPT-5.6 Terra instead of Luna?
Use Terra when Luna misses quality targets but you do not need the maximum-cost Sol route. It is the natural OpenAI escalation step for production agents.
Does prompt caching change the winner?
It can narrow or widen the real bill depending on your repeated context. Measure cache hit rate alongside retries and output length.
Bottom Line
GPT-5.6 Luna is the raw-price winner after the July 30 cut. Claude Sonnet 5 remains the quality-first challenger for workloads where better outputs reduce expensive retries and review. The practical setup is Luna by default, Sonnet or Terra on escalation, and task-level evaluation deciding the route.
Sources: OpenAI’s GPT-5.6 price-performance announcement and Anthropic’s Claude API pricing documentation.
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