Gemini 2.5 Pro vs GPT-5.5: API Cost Comparison
Compare the API pricing, context windows, features, and real-world cost projections for Gemini 2.5 Pro (Google) and GPT-5.5 (OpenAI). Use the interactive calculator below to compute your exact monthly cost based on your token usage and request volume.
Prices verified Apr 30, 2026
Interactive Cost Calculator
Fills in typical token counts for a workload type
Tokens in each prompt sent to the model
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Showing costs for 2 models. Cheapest: Gemini 2.5 Pro at $62.50/month.
| Alert | |||||||
|---|---|---|---|---|---|---|---|
BestGemini 2.5 Pro | $62.50 | $0.006250 | $12.50 | $50.00 | 68.8% | Alerts coming soon | |
GPT-5.5 | OpenAI | $200.00 | $0.020000 | $50.00 | $150.00 | — | Alerts coming soon |
Monthly Cost Comparison
Price Comparison at a Glance
All prices are in USD per 1 million tokens ($/M tokens). Lower is cheaper.
| Pricing Type | Gemini 2.5 Pro | GPT-5.5 | Cheaper |
|---|---|---|---|
| Input (standard) | $1.25/M | $5.00/M | Gemini 2.5 Pro |
| Output | $10.00/M | $30.00/M | Gemini 2.5 Pro |
| Cached input | $0.13/M | N/A | — |
| Batch input | $0.63/M | N/A | — |
| Batch output | $5.00/M | N/A | — |
Prices last verified: 2026-03-24 – 2026-04-30
Cost Breakdown by Usage Volume
Estimated monthly costs at different request volumes, assuming 1,000 input tokens and 500 output tokens per request. Adjust in the calculator above for your specific use case.
| Volume | Gemini 2.5 ProMonthly | GPT-5.5Monthly | Gemini 2.5 ProPer request | GPT-5.5Per request |
|---|---|---|---|---|
| 1K requests/mo | $6.25 | $20.00 | $0.006250 | $0.020000 |
| 10K requests/mo | $62.50 | $200.00 | $0.006250 | $0.020000 |
| 100K requests/mo | $625.00 | $2,000.00 | $0.006250 | $0.020000 |
| 1M requests/mo | $6,250.00 | $20,000.00 | $0.006250 | $0.020000 |
Green values indicate the lower-cost option at each volume tier. Cost per request is calculated at 1,000 input + 500 output tokens using standard (non-batch, non-cached) pricing.
Price History
Input price per 1M tokensWhen to Choose Gemini 2.5 Pro
by Google
- Document summarization
- RAG / Semantic search
- Code generation
Input / 1M tokens
$1.25/M
Output / 1M tokens
$10.00/M
Context window
1,048,576
Tier
premium
When to Choose GPT-5.5
by OpenAI
- General chatbot
Input / 1M tokens
$5.00/M
Output / 1M tokens
$30.00/M
Context window
1,050,000
Tier
premium
Key Differences Beyond Price
Cost is only one factor in choosing an AI model. Context window size, rate limits, supported features, and latency all affect whether a model fits your use case.
| Capability | Gemini 2.5 Pro | GPT-5.5 |
|---|---|---|
| Context window | 1,048,576 tokens | 1,050,000 tokens |
| Max output tokens | 65,536 tokens | 128,000 tokens |
| Performance tier | Premium | Premium |
| Vision / image input | Yes | Yes |
| Function calling | Yes | Yes |
| JSON mode | Yes | Yes |
| Prompt caching | Yes | No |
| Batch API (50% discount) | Yes | No |
| Extended reasoning | Yes | Yes |
| Fine-tuning | No | No |
| Rate limit (req/min) | 1,000 | Not published |
Gemini 2.5 Pro notes
Tiered pricing: prompts over 200K tokens billed at $2.50 input / $15.00 output. Thinking tokens available.
Frequently Asked Questions
Is Gemini 2.5 Pro cheaper than GPT-5.5?
At standard usage (1,000 input tokens, 500 output tokens, 100,000 requests/month), Gemini 2.5 Pro costs $625.00/month versus $2,000.00/month for GPT-5.5 — a 69% saving. Your actual savings will vary based on your token profile; output-heavy workloads amplify differences in output pricing.
Which model has a larger context window, Gemini 2.5 Pro or GPT-5.5?
GPT-5.5 has a larger context window at 1,050,000 tokens, compared to 1,048,576 tokens for Gemini 2.5 Pro. A larger context window is important for processing long documents, multi-turn conversations, or large codebases without truncation.
Do Gemini 2.5 Pro and GPT-5.5 support the Batch API?
Gemini 2.5 Pro supports the Batch API (50% discount for async processing), while GPT-5.5 does not. If your workload tolerates up to 24-hour latency, routing to Gemini 2.5 Pro with batch pricing could significantly cut costs versus GPT-5.5's standard rate.
Which model offers better prompt caching?
Gemini 2.5 Pro supports prompt caching at $0.13/M for cached input, while GPT-5.5 does not offer prompt caching. For RAG applications or chatbots with large, repeated context, Gemini 2.5 Pro's caching capability can substantially reduce effective costs.
What are the best use cases for Gemini 2.5 Pro vs GPT-5.5?
Gemini 2.5 Pro is best suited for Document summarization, RAG / Semantic search, Code generation, while GPT-5.5 is optimized for General chatbot. Choose based on which use case matches your primary workload — and validate with the cost calculator above to confirm the total monthly spend fits your budget.
What is the cost per request for Gemini 2.5 Pro vs GPT-5.5?
At 1,000 input tokens and 500 output tokens per request — a typical conversational workload — Gemini 2.5 Pro costs $0.006250 per request and GPT-5.5 costs $0.020000 per request. At 100,000 requests/month, that translates to $625.00 and $2,000.00 respectively. Use the interactive calculator to adjust these parameters for your actual workload.
Gemini 2.5 Pro vs GPT-5.5: Summary
When comparing Gemini 2.5 Pro and GPT-5.5 for API cost, the right choice depends on your workload's token profile, required features, and tolerance for latency. Gemini 2.5 Pro offers lower total cost at standard usage volumes (1,000 input + 500 output tokens per request at 100,000 requests/month) at $625.00/month, compared to $2,000.00/month for GPT-5.5.
Both models are priced in USD per million tokens, the standard unit across all major AI API providers. Gemini 2.5 Pro charges $1.25/M for input tokens and $10.00/M for output tokens. GPT-5.5 charges $5.00/M input and $30.00/M output. If your workload is output-heavy (more tokens generated than consumed as input), the model with the lower output price compounds cost savings significantly at scale.
Prompt caching is supported by Gemini 2.5 Pro but not GPT-5.5. For workloads with large, repeated system prompts or document context — such as RAG pipelines or multi-turn conversations with a fixed knowledge base — prompt caching can reduce effective input costs by 60–90%, which may change the cost ranking between these two models at your specific usage pattern.
Context window capacity differs between the two: GPT-5.5 supports up to 1,050,000 tokens in a single request, versus 1,048,576 tokens for Gemini 2.5 Pro. A larger context window is essential for document summarization, large codebase analysis, and multi-document retrieval-augmented generation (RAG) applications.
Use the interactive calculator at the top of this page to enter your actual token usage and monthly request volume for a precise cost comparison tailored to your workload. Adjust for batch API discounts and prompt caching to find the most cost-effective option for your specific deployment.
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