GPT-4.1 vs o3 (Azure): API Cost Comparison
Compare the API pricing, context windows, features, and real-world cost projections for GPT-4.1 (OpenAI) and o3 (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
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Showing costs for 2 models. Cheapest: GPT-4.1 at $60.00/month.
| Alert | |||||||
|---|---|---|---|---|---|---|---|
BestGPT-4.1 | OpenAI | $60.00 | $0.006000 | $20.00 | $40.00 | — | Alerts coming soon |
o3 (Azure) | Azure OpenAI | $60.00 | $0.006000 | $20.00 | $40.00 | — | Alerts coming soon |
Monthly Cost Comparison
Price Comparison at a Glance
All prices are in USD per 1 million tokens ($/M tokens). Lower is cheaper.
| Pricing Type | GPT-4.1 | o3 (Azure) | Cheaper |
|---|---|---|---|
| Input (standard) | $2.00/M | $2.00/M | — |
| Output | $8.00/M | $8.00/M | — |
| Cached input | $0.50/M | N/A | — |
| Batch input | $1.00/M | N/A | — |
| Batch output | $4.00/M | N/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.
| Volume | GPT-4.1Monthly | o3 (Azure)Monthly | GPT-4.1Per request | o3 (Azure)Per request |
|---|---|---|---|---|
| 1K requests/mo | $6.00 | $6.00 | $0.006000 | $0.006000 |
| 10K requests/mo | $60.00 | $60.00 | $0.006000 | $0.006000 |
| 100K requests/mo | $600.00 | $600.00 | $0.006000 | $0.006000 |
| 1M requests/mo | $6,000.00 | $6,000.00 | $0.006000 | $0.006000 |
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 GPT-4.1
by OpenAI
- RAG / Semantic search
- Document summarization
- Code generation
Input / 1M tokens
$2.00/M
Output / 1M tokens
$8.00/M
Context window
1,047,576
Tier
premium
When to Choose o3 (Azure)
by Azure OpenAI
- Code generation
- Data extraction
- Summarization
Input / 1M tokens
$2.00/M
Output / 1M tokens
$8.00/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.
| Capability | GPT-4.1 | o3 (Azure) |
|---|---|---|
| Context window | 1,047,576 tokens | 200,000 tokens |
| Max output tokens | 32,768 tokens | 100,000 tokens |
| Performance tier | Premium | Reasoning |
| 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 | No | Yes |
| Fine-tuning | No | No |
| Rate limit (req/min) | 10,000 | Not published |
GPT-4.1 notes
1M token context window enables entire codebases in context.
o3 (Azure) notes
o3 reasoning model via Azure OpenAI Service. Best for complex analytical tasks requiring deep reasoning. Azure deployment adds enterprise security and compliance.
Frequently Asked Questions
Is GPT-4.1 cheaper than o3 (Azure)?
GPT-4.1 and o3 (Azure) cost the same at standard usage (1,000 input + 500 output tokens, 100K requests/month): $600.00/month each. For different token ratios, use the calculator above.
Which model has a larger context window, GPT-4.1 or o3 (Azure)?
GPT-4.1 has a larger context window at 1,047,576 tokens, compared to 200,000 tokens for o3 (Azure). A larger context window is important for processing long documents, multi-turn conversations, or large codebases without truncation.
Do GPT-4.1 and o3 (Azure) support the Batch API?
GPT-4.1 supports the Batch API (50% discount for async processing), while o3 (Azure) does not. If your workload tolerates up to 24-hour latency, routing to GPT-4.1 with batch pricing could significantly cut costs versus o3 (Azure)'s standard rate.
Which model offers better prompt caching?
GPT-4.1 supports prompt caching at $0.50/M for cached input, while o3 (Azure) does not offer prompt caching. For RAG applications or chatbots with large, repeated context, GPT-4.1's caching capability can substantially reduce effective costs.
What are the best use cases for GPT-4.1 vs o3 (Azure)?
Both models are well-suited for Code generation. GPT-4.1 is particularly strong for RAG / Semantic search, Document summarization. o3 (Azure) is favored for Data extraction, Summarization. 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 GPT-4.1 vs o3 (Azure)?
At 1,000 input tokens and 500 output tokens per request — a typical conversational workload — GPT-4.1 costs $0.006000 per request and o3 (Azure) costs $0.006000 per request. At 100,000 requests/month, that translates to $600.00 and $600.00 respectively. Use the interactive calculator to adjust these parameters for your actual workload.
GPT-4.1 vs o3 (Azure): Summary
When comparing GPT-4.1 and o3 (Azure) for API cost, the right choice depends on your workload's token profile, required features, and tolerance for latency. Both models cost the same at standard usage volumes (1,000 input + 500 output tokens per request at 100,000 requests/month) at $600.00/month.
Both models are priced in USD per million tokens, the standard unit across all major AI API providers. GPT-4.1 charges $2.00/M for input tokens and $8.00/M for output tokens. o3 (Azure) charges $2.00/M input and $8.00/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 GPT-4.1 but not o3 (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: GPT-4.1 supports up to 1,047,576 tokens in a single request, versus 200,000 tokens for o3 (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.
Related Comparisons
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Relevant Use Cases
See cost recommendations for workloads where GPT-4.1 or o3 (Azure) is recommended.