comparison
GPT-5.5 vs Gemini 2.5 Pro
Token pricing, context window and real monthly cost, side by side. Gemini 2.5 Pro is the cheaper of the two for a typical workload — about 3.3× less.
Positioned by published specs — size, context and modality — not measured performance; a smaller model can sometimes outperform a larger one on your task.
Gemini 2.5 Pro and GPT-5.5 are the same class (Flagship) on size & context, so they're plausible substitutes — decide on price, modality and provider fit.
| metric | GPT-5.5 | Gemini 2.5 Pro |
|---|---|---|
| Input / 1M | $5.00 | $1.25 |
| Output / 1M | $30.00 | $10.00 |
| Context | 1.1M | 1.0M |
| Technical class | Flagship | Flagship |
| Cost @ typical workload | $4,500/mo | $1,375/mo |
| Modality | text + image | text + image + audio + video |
| Price source | list | list |
| Provider | OpenAI |
Snapshot . Cost uses a typical workload; tune it in the calculator. How we measure →
Which should you pick?
On a typical workload, Gemini 2.5 Pro costs $1,375/mo against GPT-5.5's $4,500/mo — roughly 3.3× cheaper. But the ranking depends on your output-to-input ratio: output is the pricier direction for both, so an output-heavy job (code generation, long answers) widens the gap while an input-heavy one (summarization, retrieval) narrows it. If you need to fit more in a single prompt, GPT-5.5 has the larger 1.1M-token window (~1,575 pages). By technical class — a spec read of size and context, not measured capability — both are Flagship, so this is a like-for-like price decision.
These are list and routed market prices, not measured outcomes. Two models at the same rate can still cost different amounts to finish the same task, because verbose or reasoning-heavy models emit more tokens. That gap is exactly what measured cost-per-task captures. The technical-class read above is likewise spec-based — size, context and modality, not measured performance — so a smaller model can still outperform a larger one on your specific task.
Frequently asked questions
Is GPT-5.5 or Gemini 2.5 Pro cheaper?
For a typical workload (1,500 input + 500 output tokens × 200,000 requests/month), Gemini 2.5 Pro costs $1,375/mo versus $4,500/mo for GPT-5.5 — about 3.3× less. Because output is priced higher than input, the winner can flip if your workload writes much more or less than this; check your own numbers in the calculator.
What's the main difference between GPT-5.5 and Gemini 2.5 Pro?
On price, GPT-5.5 is $5.00/$30.00 per 1M (in/out) and Gemini 2.5 Pro is $1.25/$10.00. By technical class (size & context) they're the same — both Flagship. GPT-5.5 has the larger context window at 1.1M tokens.
Why is Gemini 2.5 Pro so much cheaper than GPT-5.5?
Gemini 2.5 Pro has a much lower per-token rate — $10.00/1M output versus $30.00. The headline rate isn't the whole story, though: a verbose model can cost more to finish a task than its rate implies — that's what measured cost-per-task captures.
More comparisons
- GPT-5.5 vs GPT-5.4
- GPT-5.5 vs GPT-5.4 mini
- GPT-5.5 vs GPT-5.4 nano
- GPT-5.5 vs gpt-oss-120b
- Claude Fable 5 vs GPT-5.5
- GPT-5.5 vs Claude Opus 4.8
Related
- GPT-5.5 and Gemini 2.5 Pro — full specs and price history.
- API cost calculator — compare on your own workload.
- All comparisons — the full head-to-head index.