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Gemini 3.1 Pro vs o4-mini (Azure): API Cost Comparison

Compare the API pricing, context windows, features, and real-world cost projections for Gemini 3.1 Pro (Google) and o4-mini (Azure) (Azure OpenAI). Use the interactive calculator below to compute your exact monthly cost based on your token usage and request volume.

Prices verified Mar 11, 2026

Interactive Cost Calculator

GoogleGemini 3.1 ProAzure OpenAIo4-mini (Azure)

Fills in typical token counts for a workload type

Tokens in each prompt sent to the model

Tokens generated in each response

Total API calls per month

Showing costs for 2 models. Cheapest: o4-mini (Azure) at $33.00/month.

Cheapest: o4-mini (Azure) at $33.00/mo — save 58.8% vs Gemini 3.1 Pro
Alert
Besto4-mini (Azure)
Azure OpenAI$33.00$0.003300$11.00$22.0058.8%Alerts coming soon
Gemini 3.1 Pro
Google$80.00$0.008000$20.00$60.00Alerts 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 TypeGemini 3.1 Proo4-mini (Azure)Cheaper
Input (standard)$2.00/M$1.10/Mo4-mini (Azure)
Output$12.00/M$4.40/Mo4-mini (Azure)
Cached input$0.20/MN/A
Batch input$1.00/MN/A
Batch output$6.00/MN/A

Prices last verified: 2026-03-08 – 2026-03-11

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.

VolumeGemini 3.1 ProMonthlyo4-mini (Azure)MonthlyGemini 3.1 ProPer requesto4-mini (Azure)Per request
1K requests/mo$8.00$3.30$0.008000$0.003300
10K requests/mo$80.00$33.00$0.008000$0.003300
100K requests/mo$800.00$330.00$0.008000$0.003300
1M requests/mo$8,000.00$3,300.00$0.008000$0.003300

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 tokens

When to Choose Gemini 3.1 Pro

by Google

  • Document summarization
  • RAG / Semantic search
  • Code generation

Input / 1M tokens

$2.00/M

Output / 1M tokens

$12.00/M

Context window

2,097,152

Tier

premium

When to Choose o4-mini (Azure)

by Azure OpenAI

  • Code generation
  • Text classification
  • Rag Retrieval

Input / 1M tokens

$1.10/M

Output / 1M tokens

$4.40/M

Context window

200,000

Tier

reasoning

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.

CapabilityGemini 3.1 Proo4-mini (Azure)
Context window2,097,152 tokens200,000 tokens
Max output tokens65,536 tokens100,000 tokens
Performance tierPremiumReasoning
Vision / image inputYesYes
Function callingYesYes
JSON modeYesYes
Prompt cachingYesNo
Batch API (50% discount)YesNo
Extended reasoningYesYes
Fine-tuningNoNo
Rate limit (req/min)1,000Not published

Gemini 3.1 Pro notes

Preview model. Tiered pricing: prompts over 200K tokens billed at $4.00 input / $18.00 output.

o4-mini (Azure) notes

o4-mini reasoning model via Azure OpenAI Service. Cost-efficient reasoning for enterprise workloads. Excellent for coding and analytical tasks at scale on Azure.

Frequently Asked Questions

Is Gemini 3.1 Pro cheaper than o4-mini (Azure)?

At standard usage (1,000 input tokens, 500 output tokens, 100,000 requests/month), o4-mini (Azure) costs $330.00/month versus $800.00/month for Gemini 3.1 Pro — a 59% 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 3.1 Pro or o4-mini (Azure)?

Gemini 3.1 Pro has a larger context window at 2,097,152 tokens, compared to 200,000 tokens for o4-mini (Azure). A larger context window is important for processing long documents, multi-turn conversations, or large codebases without truncation.

Do Gemini 3.1 Pro and o4-mini (Azure) support the Batch API?

Gemini 3.1 Pro supports the Batch API (50% discount for async processing), while o4-mini (Azure) does not. If your workload tolerates up to 24-hour latency, routing to Gemini 3.1 Pro with batch pricing could significantly cut costs versus o4-mini (Azure)'s standard rate.

Which model offers better prompt caching?

Gemini 3.1 Pro supports prompt caching at $0.20/M for cached input, while o4-mini (Azure) does not offer prompt caching. For RAG applications or chatbots with large, repeated context, Gemini 3.1 Pro's caching capability can substantially reduce effective costs.

What are the best use cases for Gemini 3.1 Pro vs o4-mini (Azure)?

Both models are well-suited for Code generation. Gemini 3.1 Pro is particularly strong for Document summarization, RAG / Semantic search. o4-mini (Azure) is favored for Text classification, Rag Retrieval. At the same quality level, the lower-cost model is usually preferable; use this page's calculator to compare total monthly spend at your volume.

What is the cost per request for Gemini 3.1 Pro vs o4-mini (Azure)?

At 1,000 input tokens and 500 output tokens per request — a typical conversational workload — Gemini 3.1 Pro costs $0.008000 per request and o4-mini (Azure) costs $0.003300 per request. At 100,000 requests/month, that translates to $800.00 and $330.00 respectively. Use the interactive calculator to adjust these parameters for your actual workload.

Gemini 3.1 Pro vs o4-mini (Azure): Summary

When comparing Gemini 3.1 Pro and o4-mini (Azure) for API cost, the right choice depends on your workload's token profile, required features, and tolerance for latency. o4-mini (Azure) offers lower total cost at standard usage volumes (1,000 input + 500 output tokens per request at 100,000 requests/month) at $330.00/month, compared to $800.00/month for Gemini 3.1 Pro.

Both models are priced in USD per million tokens, the standard unit across all major AI API providers. Gemini 3.1 Pro charges $2.00/M for input tokens and $12.00/M for output tokens. o4-mini (Azure) charges $1.10/M input and $4.40/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 3.1 Pro but not o4-mini (Azure). 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: Gemini 3.1 Pro supports up to 2,097,152 tokens in a single request, versus 200,000 tokens for o4-mini (Azure). 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.

Explore other model comparisons from the same providers or performance tiers.

Related Provider Pages

View complete pricing tables and model lineups for the providers behind these models.

Relevant Use Cases

See cost recommendations for workloads where Gemini 3.1 Pro or o4-mini (Azure) is recommended.