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`gpt-5.6-terra`vs`claude-sonnet-5`

Both are available on APICLAN through one OpenAI-compatible endpoint, so switching between them is a one-word change. Here is what each actually costs you, and how much the difference is worth at your volume.

gpt-5.6-terra

Input / 1M$0.400

Output / 1M$2.40

List price ~~$2.00 / $12.00~~

claude-sonnet-5

Input / 1M$0.450

Output / 1M$2.25

List price ~~$2.00 / $10.00~~

On a like-for-like token mix, claude-sonnet-5 runs about 4% cheaper than gpt-5.6-terra. Both models are from different families.

What the difference is worth to you

Percentages are easy to shrug off. Put your real monthly volume in and see the number in dollars.

Input tokens / month

Output tokens / month

gpt-5.6-terra

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claude-sonnet-5

—

You keep

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These two are priced almost the same, so price should not decide it

$10 versus $12 per million output tokens at list. After our group multipliers the gap narrows further. For most workloads the monthly difference between these two is smaller than the noise in your own traffic month to month.

Which means the usual comparison is useless here. Run both on twenty real inputs from your own product and read the outputs yourself. That takes an afternoon and tells you more than any benchmark table.

One practical difference that is not about the models at all: they come from different SDK lineages, and the base URL convention differs. The Anthropic SDK and Claude Code want https://apiclan.us with no /v1 — they append /v1/messages themselves. The OpenAI SDK wants https://apiclan.us/v1. Get it backwards and you receive a 404 that never appears in your logs, which looks exactly like the model not existing.

If you are switching between these two regularly, that detail will cost you more time than the price difference will cost you money.

Which one should you actually use?

We do not publish capability benchmarks, and you should be sceptical of anyone who does. Scores on public benchmarks rarely predict how a model behaves on your codebase, your prompts and your edge cases.

What we can tell you is exactly what each one costs. Run both against a real task from your own workload — switching takes one word — and let the cheaper one win unless it visibly fails.

A practical approach that works well in agent loops: route the bulk of calls to the cheaper model, and escalate to the more expensive one only when the first attempt fails a check. Most workloads are dominated by routine calls, so the blended cost lands close to the cheap model rather than the expensive one.

Switching between them

Same endpoint, same key, same request shape. Only the model string changes.

-    model="gpt-5.6-terra",
+    model="claude-sonnet-5",

If you have not connected yet, the quickstart takes about thirty seconds — you change your base URL and nothing else.

Full pricing for each

gpt-5.6-terra pricing → claude-sonnet-5 pricing →

Prices verified 2026-10-10 and regenerated automatically from live billing data. List prices change; this page follows them.