Claude Haiku 4.5 vs o3 (Azure): API Cost Comparison
Compare the API pricing, context windows, features, and real-world cost projections for Claude Haiku 4.5 (Anthropic) 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 24, 2026
Interactive Cost Calculator
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Showing costs for 2 models. Cheapest: Claude Haiku 4.5 at $35.00/month.
| Alert | |||||||
|---|---|---|---|---|---|---|---|
BestClaude Haiku 4.5 | Anthropic | $35.00 | $0.003500 | $10.00 | $25.00 | 41.7% | 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 | Claude Haiku 4.5 | o3 (Azure) | Cheaper |
|---|---|---|---|
| Input (standard) | $1.00/M | $2.00/M | Claude Haiku 4.5 |
| Output | $5.00/M | $8.00/M | Claude Haiku 4.5 |
| Cached input | $0.10/M | N/A | — |
| Batch input | $0.50/M | N/A | — |
| Batch output | $2.50/M | N/A | — |
Prices last verified: 2026-03-11 – 2026-03-24
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 | Claude Haiku 4.5Monthly | o3 (Azure)Monthly | Claude Haiku 4.5Per request | o3 (Azure)Per request |
|---|---|---|---|---|
| 1K requests/mo | $3.50 | $6.00 | $0.003500 | $0.006000 |
| 10K requests/mo | $35.00 | $60.00 | $0.003500 | $0.006000 |
| 100K requests/mo | $350.00 | $600.00 | $0.003500 | $0.006000 |
| 1M requests/mo | $3,500.00 | $6,000.00 | $0.003500 | $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 Claude Haiku 4.5
by Anthropic
- Customer support
- Text classification
- Data extraction
Input / 1M tokens
$1.00/M
Output / 1M tokens
$5.00/M
Context window
200,000
Tier
budget
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 | Claude Haiku 4.5 | o3 (Azure) |
|---|---|---|
| Context window | 200,000 tokens | 200,000 tokens |
| Max output tokens | 64,000 tokens | 100,000 tokens |
| Performance tier | Budget | 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 | Yes | Yes |
| Fine-tuning | No | No |
| Rate limit (req/min) | 4,000 | Not published |
Claude Haiku 4.5 notes
Improved Haiku with better accuracy. Slightly more expensive than Haiku 3.5.
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 Claude Haiku 4.5 cheaper than o3 (Azure)?
At standard usage (1,000 input tokens, 500 output tokens, 100,000 requests/month), Claude Haiku 4.5 costs $350.00/month versus $600.00/month for o3 (Azure) — a 42% 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, Claude Haiku 4.5 or o3 (Azure)?
Both Claude Haiku 4.5 and o3 (Azure) have the same context window: 200,000 tokens.
Do Claude Haiku 4.5 and o3 (Azure) support the Batch API?
Claude Haiku 4.5 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 Claude Haiku 4.5 with batch pricing could significantly cut costs versus o3 (Azure)'s standard rate.
Which model offers better prompt caching?
Claude Haiku 4.5 supports prompt caching at $0.10/M for cached input, while o3 (Azure) does not offer prompt caching. For RAG applications or chatbots with large, repeated context, Claude Haiku 4.5's caching capability can substantially reduce effective costs.
What are the best use cases for Claude Haiku 4.5 vs o3 (Azure)?
Both models are well-suited for Data extraction. Claude Haiku 4.5 is particularly strong for Customer support, Text classification. o3 (Azure) is favored for Code generation, 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 Claude Haiku 4.5 vs o3 (Azure)?
At 1,000 input tokens and 500 output tokens per request — a typical conversational workload — Claude Haiku 4.5 costs $0.003500 per request and o3 (Azure) costs $0.006000 per request. At 100,000 requests/month, that translates to $350.00 and $600.00 respectively. Use the interactive calculator to adjust these parameters for your actual workload.
Claude Haiku 4.5 vs o3 (Azure): Summary
When comparing Claude Haiku 4.5 and o3 (Azure) for API cost, the right choice depends on your workload's token profile, required features, and tolerance for latency. Claude Haiku 4.5 offers lower total cost at standard usage volumes (1,000 input + 500 output tokens per request at 100,000 requests/month) at $350.00/month, compared to $600.00/month for o3 (Azure).
Both models are priced in USD per million tokens, the standard unit across all major AI API providers. Claude Haiku 4.5 charges $1.00/M for input tokens and $5.00/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 Claude Haiku 4.5 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: Both models support 200,000 tokens per request. 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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Relevant Use Cases
See cost recommendations for workloads where Claude Haiku 4.5 or o3 (Azure) is recommended.