GPT-4.5 Released: OpenAI’s Research Preview Excels in Reasoning and Conversation

OpenAI has released GPT-4.5 as a research preview—their largest and best model for chat yet, designed to better understand its strengths and limitations. This significant release marks a strategic shift in OpenAI’s approach, prioritizing conversational intelligence and emotional understanding over pure reasoning capabilities.

GPT-4.5 is available as a research preview to Pro users and developers worldwide, representing what OpenAI claims is the largest model they had ever built at the time. The model introduces breakthrough improvements in natural conversation while maintaining strong performance across diverse business applications.

GPT-4.5 demonstrates better understanding of what humans mean and interprets subtle cues or implicit expectations with greater nuance and “EQ”. This emotional intelligence translates into more natural interactions that feel less robotic and more collaborative.

Early testing shows that interacting with GPT-4.5 feels more natural, with its broader knowledge base, improved ability to follow user intent, and greater “EQ” making it useful for tasks like improving writing, programming, and solving practical problems.

OpenAI expects GPT-4.5 to hallucinate less than previous models, a critical improvement for business applications requiring accuracy. GPT-4.5 demonstrated a lower hallucination rate than OpenAI’s GPT-4o and o1 models in testing, making it more reliable for factual information retrieval and knowledge-based applications.

GPT-4.5 has access to up-to-date information with search, supports file and image uploads, and is available through the Chat Completions API, Assistants API, and Batch API to developers. The model supports key features like function calling, Structured Outputs, streaming, system messages, and vision capabilities through image inputs.

GPT-4.5 leads multilingual understanding at 85.1%, followed closely by GPT-4o at 81.5% and OpenAI o3-mini at 81.1%, making it ideal for global clients or projects requiring multiple languages.

The SWE-Lancer benchmark shows GPT-4.5 significantly outperforming not just GPT-4o but also o3-mini, evaluating the ability to understand client requirements, interpret ambiguous instructions, and deliver solutions that satisfy human needs.

GPT-4.5 focuses on conversational abilities and emotional intelligence, while o3-mini excels at step-by-step reasoning for complex problems. GPT-4.5 has better knowledge retrieval and lower hallucination rates, but o3-mini performs better on math, science, and structured coding tasks.

GPT-4.5 is very expensive at $75.00 per million input tokens and $150/million for output, compared to o1 at $15/$60 and GPT-4o at $2.50/$10. GPT-4o mini costs $0.15/$0.60, making OpenAI’s least expensive model 500x cheaper than GPT-4.5 for input and 250x cheaper for output.

A workload with 750k input tokens and 250k output tokens costs around $147—roughly 30–34× more expensive than earlier models like GPT-4o. This pricing structure requires careful evaluation of use cases where GPT-4.5’s capabilities justify the premium.

GPT-4.5 excels in customer-facing chatbots and assistants with improved conversational abilities and emotional intelligence, content generation where tone and style matter, knowledge-based applications for factual information retrieval with lower hallucination rates, and multilingual applications.

GPT-4.5 excelled at math questions embedded in business documents and was better at answering questions about financial documents that required reasoning over data and performing calculations.

GPT-4.5 showed improved performance at extracting information from unstructured data, with 19% better accuracy than GPT-4o when extracting fields from hundreds of legal documents.

Given its improved world knowledge, GPT-4.5 can create high-level plans for complex tasks, with broken-down steps then handed over to smaller but more efficient models to elaborate and execute, showing strong capabilities in agentic planning and execution.

The release of GPT-4.5 underscores the importance of multi-model AI platforms for businesses. With such dramatic pricing differences between models—GPT-4o mini being 500x cheaper than GPT-4.5 for input tokens—organizations need flexible access to choose the right model for each specific task.

A unified AI chat interface becomes essential when the choice depends on your use case—for user-facing applications where conversation quality matters, the improvement may justify the cost, but for most technical applications, GPT-4o offers better value.

Team collaboration becomes crucial when managing such diverse model capabilities and pricing structures. Having transparent, pay-as-you-go pricing based on actually consumed tokens across the entire team—rather than per-user pricing—helps organizations optimize their AI costs while accessing the full spectrum of available models.

OpenAI is still exploring what GPT-4.5 is capable of and is eager to see how people use it in ways they might not have expected. However, OpenAI doesn’t seem to have enormous confidence in the model themselves, noting it’s “more expensive than and not a replacement for GPT-4o” and they’re “evaluating whether to continue serving it in the API long-term”. The mixed reception highlights a critical inflection point in AI development. While GPT-4.5 represents impressive advances in conversational AI and emotional intelligence, its premium pricing and specialized use cases suggest the future lies not in single, monolithic models but in strategic model selection based on specific business needs. For organizations navigating this complex landscape, the key lies in having access to multiple models through unified platforms that enable intelligent routing, cost optimization, and team-wide collaboration—ensuring you get maximum value from your AI investments without being locked into any single provider’s pricing structure.