Claude vs OpenAI: Pricing Considerations
Compare Claude and GPT costs on AWS Bedrock and Azure OpenAI and see how pricing stacks up across models.
Updated February 27, 2026 to reflect recent updates.
A lot has changed since we first wrote this blog in 2024 when Anthropic announced Claude 3 and, in typical AI fashion, speculation broke out on how it stacked up against GPT-4. At the time Claude models were newer and people were just starting to view Claude as a serious competitor.
Several model generations later, the newest flagships are Claude Sonnet 4.6 and OpenAI's GPT-5.2. Benchmarks continue to show Claude as a serious competitor, and both providers now have full model families ranging from budget to premium, plus dedicated reasoning models. However, there are other factors to consider, such as price and functionality on a service and model level.
Note-we've previously touched on Claude vs OpenAI within our Amazon Bedrock vs Azure OpenAI blog but this blog will go more in-depth on Claude and OpenAI GPT models specifically. For a deeper look at pricing dimensions behind LLM costs, see our separate post.
Anthropic Claude
In 2023, Claude made waves by being the first to introduce the 100k context window during a time when the other prominent model limits were around 32k. Several generations later, the current models range from the lightweight Haiku 4.5 up to the flagship Opus 4.6, with context windows now at 200K tokens standard and up to 1M in beta. Claude models particularly excel at writing, coding, and agentic workflows.
One way to access the Claude models (that we will be focusing on in this blog) is through Amazon Bedrock. Bedrock is a marketplace of many API models from different providers, including Anthropic's Claude, where Amazon provides additional APIs and security.
Claude Models
Table of supported Claude models on Bedrock (as of 2/27/2026).
OpenAI GPT
OpenAI's GPT models remain widely used, however, competition has been quickly catching up. OpenAI's current lineup now spans from the cost-efficient GPT-4.1 family through the flagship GPT-5 series, plus the o-series reasoning models for complex multi-step analysis.
Azure and OpenAI are closely related. Microsoft has a strategic partnership with OpenAI, which includes Azure being the primary cloud provider for OpenAI's models and services. This close collaboration allows Azure to offer seamless integration and access to the latest OpenAI models (with additional features and security).
GPT Models
Table of supported GPT models on Azure (as of 2/27/2026).
Claude vs OpenAI GPT Models Functionality
See here for a service-level comparison of Azure and Bedrock documentation/community support and no-code playgrounds. See below for the model-level comparison:
- Max Tokens: Claude was the first to reach 100K tokens, then OpenAI leapfrogged with 128K, and Claude pushed to 200K. Now both are at or near 1M-Claude's latest models offer 200K standard with 1M in beta, while GPT-4.1 supports 1M natively and GPT 5.2 supports 400K tokens.
- Supported Regions: This applies specifically to Bedrock and Azure. Availability may be model and feature-specific and many regions are not accounted for. See Bedrock and Azure to see if your region is supported.
- Supported Languages: GPT models are optimized for English but can handle many other languages, though no official public list of supported languages exists. Claude supports multiple languages, including English, Spanish, and Japanese.
- Training Data Date: The Claude 4.x models have a training data cutoff of early 2025. OpenAI's GPT-5 series has a knowledge cutoff of September 2024, while GPT-4.1 and the o-series models cut off at June 2024.
Claude Pricing
With Bedrock, you have several options: On-Demand, Batch (50% discount), and Provisioned Throughput. Prompt caching is also available, offering up to 90% savings on cached input tokens. Prices are shown for the US East region.
On-Demand
The non-committal, pay-by-usage option. Charges are per input token processed and output token generated.
Claude On-Demand pricing table (updated 2/27/26).
Batch and Provisioned Throughput
Bedrock offers Batch inference at a 50% discount compared to on-demand pricing for large-scale predictions processed asynchronously. Provisioned Throughput is also available for large consistent inference workloads that need guaranteed throughput-contact your AWS account team for specific pricing. Additionally, prompt caching can significantly reduce costs for workloads with repetitive context, with cache read prices as low as $0.10 per 1M tokens for Haiku 4.5. We go deeper on these pricing mechanics in AI Cost Considerations Every Engineer Should Know.
OpenAI GPT Pricing
Charges for GPT models through Azure vary by deployment type: Global, Data Zone, and Regional. Prices below are shown for Global deployments.
Pay-As-You-Go
Charges vary for different model types. Cached input pricing is also available for supported models.
OpenAI GPT model pricing table (as of 2/27/2026).
Batch, Provisioned Throughput, and Fine-Tuning
Azure offers a Batch API at 50% off standard pricing for large-scale async workloads. Provisioned Throughput Units (PTUs) are available for consistent high-volume inference with guaranteed capacity-contact your Azure account team for pricing details. Cached input pricing is supported on many models, with cache read prices as low as $0.005 per 1M tokens for GPT-5-nano. Fine-tuning is available for the GPT-4.1 family, with training costs starting at $1.50 per 1M tokens for GPT-4.1 nano.
Pricing Comparison Claude vs OpenAI
Based on benchmarks, user feedback, and use cases the most comparable models are:
Claude Sonnet 4.6 vs GPT-5.2
These are the current flagships. GPT-5.2 is notably cheaper on input ($1.75 vs $3.00), but output pricing is comparable ($14.00 vs $15.00). GPT-5.2 has a 400K context window vs Sonnet's 200K standard (1M in beta). The tradeoff here is really about model strengths - Claude's agentic and coding capabilities vs GPT-5.2's reasoning depth.
Claude Haiku 4.5 vs GPT-4.1 mini
For high-volume, cost-sensitive workloads, GPT-4.1 mini is the more economical choice, with input tokens priced 60% lower and output tokens priced 68% lower than Haiku 4.5. Both models are fast and well-suited for chatbots, lightweight tasks, and real-time applications.
Claude Opus 4.6 vs o3
For complex reasoning tasks, these are both premium options. Opus 4.6 is notably more expensive-output tokens are more than 3x the cost of o3's ($25 vs $8 per 1M), and input tokens are 150% pricier. If you're doing heavy reasoning work on a budget, o3 wins on price.
Conclusion
The race to offer cheaper, more capable models is a good sign for end-users. Both providers now have options at every price point, from GPT-4.1 nano and Claude Haiku 4.5 all the way up to GPT-5.2 and Claude Opus 4.6. Add in prompt caching and batch discounts, and the actual cost picture gets more nuanced than the sticker prices above suggest. The choice largely comes down to your specific needs, context window, deployment region, agentic capabilities, and budget. For more strategies on keeping your AI spend in check, see our guide on how to save on AI costs.
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