Claude Sonnet 5 vs GPT-5.6 Terra: which is cheaper for your workload
These two sit in the same price bracket and are the default mid-tier choice for most production agents. The interesting part is not the headline input rate It is how differently they price output, because output is where agent workloads spend most of their money.
Claude Sonnet 5 vs GPT-5.6 Terra: the numbers side by side
| Claude Sonnet 5 | GPT-5.6 Terra | |
|---|---|---|
| Gateway rate — input | $1 | $1 |
| Gateway rate — output | $5 | $6 |
| Official list — input | $2 | $2 |
| Official list — output | $10 | $12 |
| Blended at 1/3 output | $2.33 | $2.67 |
| Output : input price ratio | 5.0× | 6.0× |
USD per 1M tokens. Gateway rates checked 2026-11-01; official list prices as published by each vendor. Gateway rates move with upstream promotions, re-check before committing a budget.
What each costs per month
| Monthly tokens | Claude Sonnet 5 | GPT-5.6 Terra | Cheaper |
|---|---|---|---|
| 10M | $23.33 | $26.67 | Claude Sonnet 5 — 13% less |
| 100M | $233 | $267 | Claude Sonnet 5 — 13% less |
| 1000M | $2,333 | $2,667 | Claude Sonnet 5 — 13% less |
Assumes 1/3 of tokens are output and 2/3 input (roughly a chat or coding-agent mix). At a 100M tokens/month workload the gap is $33.33 a month, or $400 a year. Change the split in the calculator, output-heavy workloads widen the gap.
How much tokens each budget buys
| Budget | Claude Sonnet 5 | GPT-5.6 Terra | Extra tokens |
|---|---|---|---|
| $100 | 43M | 37M | Claude Sonnet 5 — 5M more |
| $1,000 | 429M | 375M | Claude Sonnet 5 — 54M more |
Tokens purchasable at the blended rate above. Output tokens cost more than input, so reading these figures as "all input" would overstate them.
Which one to pick
Both models land within a few cents of each other on blended cost, so the decision should not be made on price alone. Two questions settle it faster:
- Is your workload output-heavy? Long generations (multi-file code edits, long reports), chain-of-thought reasoning returned to you, amplify whichever model prices output higher. Check the output:input ratio row in the table above; the model with the lower ratio is the safer default for those workloads.
- Are you standardising on one vendor's tooling? If your team already runs Claude Code or the Anthropic SDK, the integration cost of switching is zero and the price difference is unlikely to justify moving. If you are greenfield, run your real token split through the calculator before choosing.
Do not pick on published list prices. Both models are discounted against list here, and the discounts are not identical, so the official-price ranking and the gateway-price ranking can differ. The table above shows both.
Where the answer flips: cost as the output share moves
Both prices above are blended at one third output. That assumption is doing more work than it looks like, because it is the only thing standing between you and the opposite answer. The table below holds volume constant and moves only the output share.
| Output share | Claude Sonnet 5 | GPT-5.6 Terra | Cheaper | Gap |
|---|---|---|---|---|
| 0% | $1 | $1 | GPT-5.6 Terra | $0 |
| 10% | $1.4 | $1.5 | Claude Sonnet 5 | $0.1 |
| 25% | $2 | $2.25 | Claude Sonnet 5 | $0.25 |
| 33% | $2.32 | $2.65 | Claude Sonnet 5 | $0.33 |
| 50% | $3 | $3.5 | Claude Sonnet 5 | $0.5 |
| 75% | $4 | $4.75 | Claude Sonnet 5 | $0.75 |
| 100% | $5 | $6 | Claude Sonnet 5 | $1 |
The two cross at roughly -0% output. Below that share GPT-5.6 Terra is cheaper; above it the other one is. If your real output share sits anywhere near -0%, a headline rate comparison is not a safe basis for this decision, measure your own split first.
Read the table as the reason not to trust a single number. Most published comparisons quote one blended figure, usually at an assumed ratio, and that figure is only valid at that ratio. The gap column is the one to watch: where it narrows towards zero, the decision should be made on something other than price.
What this comparison does not tell you
A price comparison answers one question and quietly implies several others it has not addressed. Before acting on the numbers above, these are the differences that a rate table cannot show:
- Cost per task, not cost per token. A model that needs half as many turns to finish the same job can be cheaper at a higher rate. The only way to know is to run one representative task on each and compare tokens consumed, not rates charged.
- Context window. A shorter window does not produce an error It produces truncation, which looks like a quality problem and gets misdiagnosed as one. Where your workload depends on long context, this outranks price entirely.
- Latency and throughput. Two models at similar rates can differ enough in response time to change whether a feature is usable. Measure it on your own payloads.
- Availability and rate limits. What you can actually sustain under concurrency is a property of the account and the route, not of the price.
- Capability differences. These pages compare price only. Where a capability difference is decisive, the vendor's own documentation is the source, we do not guess at it, and a cheaper model that cannot do the job is not cheaper.
The honest ordering: if the gap column above is small at your output share, stop optimising price and optimise for whichever of the five items above your workload actually depends on.
Switching between them
Both models are called through the same endpoint, so this is a model-ID change, not a migration. Setup references: OpenAI & Anthropic SDK · Claude Code · Cursor · reducing API cost.
Related comparisons: Opus 5 vs GPT-5.6 Sol · Claude vs Gemini · Three ways to pay for Claude
FAQ
Is Claude Sonnet 5 or GPT-5.6 Terra cheaper?
At current gateway rates Claude Sonnet 5 is cheaper for a mixed workload — $2.33 versus $2.67 per 1M tokens blended at one third output. The answer depends on your input/output split: output tokens are priced several times higher than input on both models (5x and 6x respectively), so an output-heavy workload widens the gap.
How much does Claude Sonnet 5 cost per month?
At $2.33 per 1M blended tokens: about $23.33 for 10M tokens a month, $233 for 100M, and $2,333 for 1B. That is pure token spend There is no subscription on either model.
How much does GPT-5.6 Terra cost per month?
At $2.67 per 1M blended tokens: about $26.67 for 10M tokens a month, $267 for 100M, and $2,667 for 1B.
Can I switch between them without rewriting my code?
Both are reached through the same gateway endpoint, so switching is a model-ID change in the request rather than a new integration. See the SDK guide for the one-line change, or the Claude Code setup if you are switching inside a coding agent.
Can I use both models in the same application?
Yes, and it is often the right answer. Route mechanical work to the cheaper of the two and keep the other for tasks where the difference matters to you. Both are reached through the same endpoint with the same key, so a fallback is a model-ID change rather than a second vendor relationship.
Which is cheaper for a coding agent, Claude Sonnet 5 or GPT-5.6 Terra?
Agent workloads are input-heavy. Roughly 500M input to 100M output a month, because every turn resends the whole context. At that shape Claude Sonnet 5 bills about $1,000.00 and GPT-5.6 Terra about $1,100.00, so Claude Sonnet 5 comes out ahead. The same model wins at both shapes, so this particular choice does not hinge on how output-heavy your workload turns out to be.
What is the price difference between Claude Sonnet 5 and GPT-5.6 Terra per 1M tokens?
On input it is $1 against $1 per 1M; on output, $5 against $6. Blended at one third output the gap is $0.3333 per 1M in favour of Claude Sonnet 5. Output carries a multiple of the input rate on both models, so the gap widens or narrows with your own token split rather than staying fixed — price it in the calculator with your real ratio before committing.