Cost worksheet

Opus 5 vs GPT 5.6 pricing

Pricing comparisons are easy to distort because a model's invoice is not only its list price. Input length, output length, cache behavior, retries, rejected answers, and human review time all matter. The Opus 5 side has a documented list-price anchor; the GPT 5.6 side should be filled from your current provider account.

Use Opus 5 when the higher-quality answer reduces rework enough to justify the token cost. Use GPT 5.6 when it solves the task with lower latency and lower total spend. Always estimate cost per accepted result, not only cost per call.

Open the Opus 5.0 guide K3Nova homepage

Pricing worksheet — Input, output, cache, retries, and accepted work

Next step

Use the Opus 5.0 hub before you change routing.

Open the Opus 5.0 guide for the full evidence map, console link, and related model comparison pages before you make a routing or budget decision.

Open the Opus 5.0 guide Visit the K3Nova homepage

Confirmed starting points

Facts to keep on the table

Opus list price	Anthropic docs list $5 per million input tokens and $25 per million output tokens for Opus 5.
Hidden driver	Long code patches and reports can make output cost the larger part of the bill.
Budget rule	Track retries and rejected answers, not only successful calls.
Launch	Anthropic introduced Claude Opus 5 on July 24, 2026.
API name	Anthropic documentation lists the model ID as claude-opus-5.
Context	Anthropic documentation lists a 1M token context window and 128K maximum output.
Reasoning modes	Adaptive thinking is the default, while Fast mode is available when latency matters.

Start with separate input and output estimates

A long-context prompt may be expensive on input, but coding and research answers can also be output-heavy. Estimate the two sides separately. For Opus 5, use the documented Anthropic list-price anchor and then adjust for the platform you use. For GPT 5.6, use your live provider pricing page before entering any number.

Add cache and retry behavior

Cache rules can change the effective price for repeated context, while retries can quietly double spend. A fair comparison includes first-run prompts, repeated context, average answer length, retry rate, and the percentage of answers that survive review. This is especially important for code tasks where one accepted patch can be more valuable than many cheap attempts.

Compare total operating cost

A lower token price is not always the cheaper workflow if the answer needs heavy human repair. A higher token price is not always justified if the task is short and routine. The practical number is cost per accepted answer, accepted diff, resolved ticket, or reviewed decision.

Keep exact provider numbers current

This page gives the Opus anchor from the gathered material and shows the worksheet. It does not freeze GPT 5.6 prices because those depend on the current provider and account terms. Before using the page for a budget, refresh both provider pages and update the worksheet.

Evaluation worksheet

Use this before you choose a route

Input tokens	Long documents, repositories, policies, and prompt templates.
Output tokens	Patches, reports, tables, decision memos, and tests.
Retries	Follow-up prompts caused by missing constraints or rejected answers.
Accepted result	The unit that actually matters to your team or product.

Primary references

References used for this guide

Anthropic Docs: models overviewClaude family limits and list prices for current-model planning.
Anthropic Docs: What is new in Claude Opus 5Model ID, 1M context, 128K max output, adaptive thinking, Fast mode, and migration notes.
Anthropic launch announcementLaunch date, positioning, benchmark framing, pricing context, and system-card path.
Artificial Analysis model pageIndependent comparison signals for intelligence, cost, speed, and verbosity.
Decrypt benchmark and price coverageThird-party benchmark framing against Fable 5 and GPT-family models.

FAQ

Common follow-up questions

What Opus 5 price should I start with?

Use Anthropic's documented list price as the starting anchor, then check the platform you actually use for current billing and cache rules.

Why not compare only token price?

Because rejected answers, retries, and review time can change the real cost of completing the job.

What is the best budgeting unit?

Use cost per accepted result: accepted patch, completed report, resolved ticket, or reviewed answer.