TokenPad

Claude Sonnet 5 vs GPT-5.4

Anthropic against OpenAI, on the three things that decide the bill: what each token costs, how many of them fit, and whether you can count them accurately before you send.

The default choice for most production traffic on either side, and the pair most teams are actually deciding between.

Claude Sonnet 5 and GPT-5.4 compared
 Claude Sonnet 5GPT-5.4
ProviderAnthropicOpenAI
Input, per 1M tokens$2.00$2.50
Cached input, per 1M$0.2000$0.2500
Output, per 1M tokens$10.00$15.00
Context window1M
Token countingEstimateExact
1K in + 500 out$0.007000$0.0100
Price verified2026-08-032026-08-03

Which one costs less

On a representative request of 1,000 input and 500 output tokens, Claude Sonnet 5 comes to $0.007000 against $0.0100 — a factor of 1.4.

Both support cached input, at $0.2000 and $0.2500 per million respectively. If your requests share a long stable prefix, that rate matters more to your bill than the headline input price does.

Context and token counting

Context windows are comparable here, so the decision comes down to price and output quality rather than capacity. Check your real context size in the context window calculator.

One practical asymmetry: token counts for GPT-5.4 can be computed exactly in a browser, while Claude Sonnet 5 has no public browser-capable tokenizer, so any pre-flight count for it is an estimate. That matters for cost forecasting and for anything that has to sit close to a context limit. The methodology page sets out what the estimate is based on.

The same two models at a million requests a month

One sample request settles nothing, because the two providers price input and output on different ratios. These are four representative workload shapes, each at a million requests a month, computed from the rates in the table.

Monthly cost at one million requests, by workload shape
WorkloadClaude Sonnet 5GPT-5.4Difference
Classification500 in · 50 out$1,500.00$2,000.00$500.00 (1.3×)
Chat turn1500 in · 300 out$6,000.00$8,250.00$2,250.00 (1.4×)
Document summary20.000 in · 800 out$48,000.00$62,000.00$14,000.00 (1.3×)
Code generation2000 in · 1500 out$19,000.00$27,500.00$8,500.00 (1.4×)

Claude Sonnet 5 is cheaper on all four shapes, by between 1.3× and 1.4×. The gap is widest on code generation and narrowest on document summary, so the saving is largest exactly where the volume usually is.

The absolute figures matter as much as the ratios. On code generation alone the difference is $8,500.00 a month — the kind of number that justifies an afternoon of measurement before the decision rather than after it.

What caching does to the answer

Most production traffic repeats a long stable prefix — a system prompt, tool definitions, a few fixed examples. On a chat turn with 1,200 of its 1,500 input tokens cached, the monthly figures become $3,840.00 for Claude Sonnet 5 and $5,550.00 for GPT-5.4. The ranking holds, but both figures fall sharply — which is the more useful lesson: enabling caching saves more on either model than switching between them does. Check whether your prompt is actually cacheable with the prompt cache checker; a single timestamp near the top invalidates the whole prefix.

What this comparison deliberately does not say

It does not say which one is better. Published benchmark scores are run on public sets that models may have seen, they are reported by parties with an interest in the result, and none of them are measured on your data. Repeating them here would add confident-sounding numbers with nothing behind them.

Price, context window and tokenizer availability are facts, with sources and dates attached. Quality is a measurement you have to take yourself — build an evaluation set with the eval dataset builder and run both models against your own cases. Thirty real examples will tell you more than any leaderboard.

If a migration between these two is what you are weighing, the model migration checklist covers what changes beyond price: tool calling formats, stop reasons, refusal behaviour and the re-tuning that prompts usually need.

Price your own workload

The table above uses representative shapes, not yours. Put your real request volume, prompt size and output length into the cost calculator, and measure a real prompt in the token counter first so the inputs are counted rather than guessed. Prices above were read from each provider’s documentation on August 3, 2026 and August 3, 2026; follow the source links to confirm before committing spend.

Questions

Is Claude Sonnet 5 always cheaper than GPT-5.4?

On every workload shape priced above, yes — Claude Sonnet 5 is cheaper, by between 1.3× and 1.4× depending on how output-heavy the work is. Price is not the only criterion, but on this pair it does not reverse.

Can I count tokens for Claude Sonnet 5 and GPT-5.4 before sending?

Only GPT-5.4. It has a published tokenizer that runs in a browser, so counts are exact. Claude Sonnet 5 does not, so any pre-flight figure for it is an estimate — which matters most when a prompt sits close to the context limit.

How current are these prices?

Claude Sonnet 5 was read from Anthropic's own pricing page on August 3, 2026 and GPT-5.4 from OpenAI's on August 3, 2026. Both source links are in the table above. Model prices fall without notice, so confirm at the source before committing to a volume decision.

Does the cheaper model produce worse answers?

Not necessarily, and this page does not claim to know. Published benchmark scores are not reproducible on your data, so the only honest measurement is your own evaluation set on your own cases. Price is the part that can be stated as fact; quality is the part you have to measure.

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