Verified October 2026

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GPT-5.5 vs Gemini 2.5 Pro

A straight cost comparison of GPT-5.5 (OpenAI) and Gemini 2.5 Pro (Google Gemini), per 1,000,000 tokens, verified October 2026.

$5GPT-5.5 input / 1M
$1.25Gemini 2.5 Pro input / 1M
70%Blended price gap
Gemini 2.5 ProCheaper blended

Rate-by-rate comparison

USD per 1M tokens · October 2026
MetricGPT-5.5Gemini 2.5 ProWinner
Input / 1M$5$1.25Gemini 2.5 Pro
Cached input / 1M$0.50$0.125Gemini 2.5 Pro
Cache write / 1M——Tie
Output / 1M$30$10Gemini 2.5 Pro
Context window1,050,0001,000,000GPT-5.5
Batch APIYesYesTie
Long-context tier> 272,000> 200,000—

For per-token metrics, the lower number wins. For context window and batch support, the higher or broader option wins. A dash means the provider does not publish that rate: a missing cache-write fee means writes are not billed per token, while a missing cached-input rate means cache hits bill at the full input rate.

Blended cost: 1M input + 250K output

ModelBlended costDifference
GPT-5.5$12.50+$8.75
Gemini 2.5 Pro$3.75Cheaper

Ten workloads, two bills

The same two models, priced across ten workloads that differ only in their input:output ratio. Nothing else changes — no retries, no system prompt, no middleware.

WorkloadGPT-5.5Gemini 2.5 ProWinner
Classification
100K reqs · 500 in / 10 out
$280$72.50Gemini 2.5 Pro
Data extraction
10K reqs · 2K in / 200 out
$160$45Gemini 2.5 Pro
Support chat
1K reqs · 4K in / 600 out
$38$11Gemini 2.5 Pro
Code review
2K reqs · 8K in / 1.5K out
$170$50Gemini 2.5 Pro
Summarisation
1K reqs · 20K in / 1K out
$130$35Gemini 2.5 Pro
Agent loop
5K reqs · 12K in / 2K out
$600$175Gemini 2.5 Pro
Translation
500 reqs · 15K in / 15K out
$263$84.38Gemini 2.5 Pro
Long-document QA
200 reqs · 120K in / 800 out
$125$31.60Gemini 2.5 Pro
Cached RAG
1K reqs · 50K in (45K cached) / 1K out
$77.70$21.93Gemini 2.5 Pro
Nightly batch
10K reqs · 10K in / 2K out
$550$163Gemini 2.5 Pro

GPT-5.5 wins 0 of 10, Gemini 2.5 Pro wins 10 of 10. The winner is set by the token mix, not by the headline rate.

Where the two bills cross over

Gemini 2.5 Pro is cheaper on both sides of the mix: $1.25 vs $5 per million input tokens, and $10 vs $30 per million output. No input:output ratio reverses that, so on price alone the other model never becomes the better choice — it has to win on context, latency or output quality.

Cost at four scales

The same support-chat workload (4K input, 600 output per request) at four monthly volumes.

Requests / monthGPT-5.5Gemini 2.5 ProDifference
100$3.80$1.10Gemini 2.5 Pro cheaper by $2.70
1,000$38$11Gemini 2.5 Pro cheaper by $27
10,000$380$110Gemini 2.5 Pro cheaper by $270
100,000$3,800$1,100Gemini 2.5 Pro cheaper by $2,700

What caching does to each bill

Caching only helps the part of the prompt that repeats. This is the support-chat workload (1,000 requests, 4,000 input tokens each) with an increasing share of that prompt served from a warm cache, written once on the first request.

Cached share of the promptGPT-5.5Gemini 2.5 ProWinner
0%$38$11Gemini 2.5 Pro
50%$29.01$8.75Gemini 2.5 Pro
80%$23.61$7.40Gemini 2.5 Pro
95%$20.92$6.73Gemini 2.5 Pro

Both models publish a cached-read rate, so the discount is comparable: GPT-5.5 reads cache at $0.50 per million, Gemini 2.5 Pro at $0.125.

Which one should you pick?

GPT-5.5 wins on none of the ten workloads above, while Gemini 2.5 Pro wins on classification, data extraction, support chat, code review, summarisation, agent loop, translation, long-document qa, cached rag, nightly batch.

Beyond price, the two differ on input rate ($5 vs $1.25); output rate ($30 vs $10); cached-input rate ($0.50 vs $0.125); context window (1,050,000 vs 1,000,000).

Batch mode is available on GPT-5.5 and Gemini 2.5 Pro, which halves the nightly job. Both publish cached-input discounts, so a stable system prompt is worth caching on either.

FAQ

Is GPT-5.5 cheaper than Gemini 2.5 Pro?

On a blended 1M-input-plus-250K-output workload, Gemini 2.5 Pro is cheaper by 70% ($3.75 vs $12.50). The gap changes for cache-heavy prompts and for batch jobs, as the workload table shows.

Which handles longer prompts, GPT-5.5 or Gemini 2.5 Pro?

GPT-5.5 has the larger context window (1,050,000 vs 1,000,000 tokens). Watch the long-context threshold on GPT-5.5 and Gemini 2.5 Pro: rates rise once input passes it.

Do both models support prompt caching?

GPT-5.5 bills cached reads at $0.50 per 1M; Gemini 2.5 Pro at $0.125.

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