OpenAI Unveils GPT-5.1: Smarter, Faster, and More Conversational

Specific benchmark results indicate a MMLU score of 92.5%, a HumanEval pass rate of 94.2%, and a SWE-bench score of 88.7%. These numbers represent a substantial jump over the previous GPT-5.0 iteration. The model's ability to handle long-context reasoning without degradation is particularly noteworthy, ensuring that users can process vast amounts of data without losing coherence.

• MMLU Score: 92.5%
• HumanEval Pass Rate: 94.2%
• SWE-bench Score: 88.7%

API Pricing

OpenAI has structured the pricing for GPT-5.1 to reflect its efficiency gains. The cost per million tokens has been optimized to provide better value for developers compared to previous generations. This pricing model encourages experimentation and integration into production environments without prohibitive costs.

Developers can access the model via the standard API with competitive rates. The pricing is tiered based on usage, ensuring that high-volume applications remain cost-effective. A free tier is also available for testing purposes, allowing new users to evaluate the model's capabilities before committing to paid plans.

• Input Price: $0.0025 per million tokens
• Output Price: $0.0100 per million tokens
• Free tier available for testing

Comparison Table

To understand the market position of GPT-5.1, it is essential to compare it against its closest competitors. The following table outlines the key specifications, including context window, output limits, and pricing, which are critical factors for enterprise decision-makers.

This comparison highlights GPT-5.1's balance between cost and capability. While competitors may offer larger context windows, GPT-5.1 focuses on speed and reasoning accuracy, which are often more valuable for interactive applications.

• Direct comparison with GPT-5.4 and GPT-5.3
• Focus on cost-per-token efficiency
• Analysis of context window utility

Use Cases

GPT-5.1 is best suited for a variety of high-stakes applications where accuracy and speed are paramount. Developers can leverage the model for advanced coding assistance, where it can generate and debug code with minimal human intervention. The improved reasoning capabilities make it ideal for complex data analysis and scientific research.

Additionally, the model excels in customer support and conversational agents, providing a more natural and empathetic interaction. Its ability to handle long-context RAG (Retrieval-Augmented Generation) tasks allows for building sophisticated knowledge bases that retain information over extended interactions.

• Advanced Coding and Debugging
• Customer Support Agents
• Complex RAG Systems

Getting Started

Accessing GPT-5.1 is straightforward for developers familiar with the OpenAI API. The model is available immediately via the standard endpoint, ensuring minimal disruption to existing workflows. Documentation is available for quick integration, with SDKs provided for Python, JavaScript, and other popular languages.

To begin, developers should navigate to the official API dashboard and select the GPT-5.1 model version. Authentication is handled via standard API keys, and rate limits are generous for new users. For enterprise clients, dedicated support is available to optimize performance and security configurations.

• Available via standard API endpoint
• SDKs for Python and JavaScript
• Dedicated enterprise support available

Comparison

API Pricing — Input: 1.25 / Output: 10 / Context: 256k

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