GPT 5.5 vs GPT 5.4: same window, 2× the rate

What a generation apart did not change

GPT 5.4 was released 2026-03-15 and GPT 5.5 on 2026-05-01, about six weeks later. On paper the two entries are close to interchangeable: both take a 272,000-token context, both cap output at 64,000 tokens, both support text, tools and thinking, and both answer on /v1/responses.

Both are billed at the 0.1× multiplier. The list rates differ by exactly a factor of two — $5 / $30 per million for GPT 5.5 against $2.50 / $15 for GPT 5.4 — which after the discount is $0.50 / $3.00 against $0.25 / $1.50.

That symmetry is worth noticing because it makes the comparison unusually clean. There is no context trade to weigh, no capability the older id lacks, and no route change to absorb. The newer generation costs twice as much per token and everything the catalog records is otherwise the same.

The 272k ceiling both share

The constraint the two share matters more than the price gap for some workloads. 272,000 tokens is the smallest context in the OpenAI text lineup here: the GPT 5.6 ids carry 372,000 and stable-gpt-6-astra carries 1,050,000.

Output is capped at 64,000 tokens on both, half the 128,000 that gpt-5.6-sol, gpt-5.6-terra, gpt-5.6-luna and stable-gpt-6-astra allow. If a single response has to exceed 64,000 tokens, neither generation of GPT 5.4/5.5 is the id to reach for, and the price question never comes up.

So the useful first question is not which of the two, but whether either fits. Where 272k and 64k are comfortable, the choice is a straight price-against-output comparison; where they are not, the decision moves to a different id entirely.

for MODEL in gpt-5.4 gpt-5.5; do
  echo "=== $MODEL ==="
  curl -sS https://token-share.app/v1/responses \
    -H "Authorization: Bearer $TOKEN_SHARE_KEY" \
    -H "Content-Type: application/json" \
    -d "{
      \"model\": \"$MODEL\",
      \"input\": \"Refactor this function and explain the risk in the change.\"
    }"
done

Testing whether the newer id earns 2×

The catalog records no quality difference between the two — a release date six weeks apart is not evidence about your prompts. Since both take an identical request on the same route, running a sample through each costs one extra call per prompt.

Pick a batch of prompts that reflects the work you actually send, not a set of puzzles, and compare outputs side by side. The doubling is easier to justify on long reasoning chains, where an early mistake compounds through every later step, and on work where a wrong answer costs more than the tokens — but whether your prompts are that kind of work is not something a spec table can tell you.

One more thing worth checking while you have both running: cached input is billed separately from fresh input, at $0.50 per million official for GPT 5.5 and $0.25 for GPT 5.4. If your prompts share a long stable prefix, the effective gap over a session is smaller than the headline 2× suggests.

Common questions