Skip to content
Blog
Survey Note: Exploring OpenAI's GPT-4.5 Release

Survey Note: Exploring OpenAI's GPT-4.5 Release

Antonio Di Nicola
Name
Antonio Di Nicola

Updated on

A survey note exploring OpenAI's GPT-4.5 release, codenamed Orion, covering technical specifications, benchmark performance, comparisons, and more.

Introduction

OpenAI, a leader in AI research and deployment, released GPT-4.5 in February 2025, codenamed Orion, as part of their ongoing efforts to advance large language models (LLMs). This release, announced on February 27, 2025, is positioned as the largest and most knowledgeable model to date, aiming to enhance user interaction and reduce inaccuracies. This survey note delves into its technical specifications, benchmark performance, and comparisons with previous models and competitors, providing a comprehensive overview for tech enthusiasts and professionals.

Background and Release Context

The release of GPT-4.5 comes at a time of rapid advancement in AI, with competitors like Anthropic and DeepSeek pushing the boundaries of reasoning and efficiency. OpenAI's announcement, initially shared through various tech news outlets like TechCrunch (opens in a new tab) and WIRED (opens in a new tab), highlighted its availability as a research preview for ChatGPT Pro subscribers at a $200 monthly fee, with plans to roll out to other paid tiers subsequently. This move reflects OpenAI's strategy to gather user feedback before wider deployment, as noted in an X post by josuenunez_ai (opens in a new tab).

Technical Specifications

GPT-4.5 is described as OpenAI's largest model yet, though specific details such as parameter count and training dataset size are not publicly disclosed, aligning with OpenAI's practice to safeguard proprietary information, as seen in previous releases like GPT-4 (Wikipedia (opens in a new tab)). Key technical aspects include:

  • Context Window: A significant upgrade to 128,000 tokens, as mentioned in an X post by josuenunez_ai (opens in a new tab), enabling it to handle extensive conversations and documents, far surpassing GPT-4's capabilities.
  • Computational Efficiency: Reports suggest over 10x improvement over GPT-4, as noted in an X post by Iamtoxix (opens in a new tab), making it more resource-efficient despite its size.
  • Non-Frontier Model: OpenAI clarified that GPT-4.5 is not a frontier model, meaning it does not push the boundaries of AI capabilities in terms of potential risks, as stated in TechCrunch (opens in a new tab).

This lack of detailed technical disclosure, while common, leaves room for speculation, with some X posts like daniel_nguyenx (opens in a new tab) from 2023 mentioning multi-modal capabilities, though these seem speculative and not confirmed for the 2025 release.

Benchmark Performance

Benchmark results provide insight into GPT-4.5's capabilities, with several tests conducted and reported across tech platforms:

  • SimpleQA Accuracy and Hallucination: On SimpleQA, GPT-4.5 shows a hallucination rate of 37.1%, compared to 59.8% for GPT-4o and 80.3% for o3-mini, as reported by MIT Technology Review (opens in a new tab). This indicates improved factual accuracy, a critical factor for reliability.
  • Math and Science: It shows improvements of 27.4% in math and 17.8% in science over GPT-4o, according to Vellum (opens in a new tab), making it more reliable for factual reasoning tasks.
  • Coding and Multilingual Tasks: On SWE-Lancer Diamond, it outperforms o3-mini (32.6% vs. 23.3%), suggesting strong performance in agentic coding, as noted in the same Vellum (opens in a new tab) article. Multilingual performance sees a moderate gain of 3.6%.
  • Human Preference: Human testers, as per ZDNET (opens in a new tab), preferred GPT-4.5 for everyday, professional, and creative tasks, including poetry and ASCII art, indicating its conversational strengths.

However, it falls short in some specialized reasoning tasks compared to o3-mini, particularly in math and science benchmarks, as noted in WIRED (opens in a new tab). This suggests a trade-off between general-purpose and specialized capabilities.

Comparisons with Previous Models

To understand GPT-4.5's position, we compare it with previous OpenAI models:

  • GPT-4: GPT-4.5 offers deeper world knowledge and higher emotional intelligence, with a larger context window (128k vs. GPT-4's 32k or 8k, depending on version, as per Wikipedia (opens in a new tab)). It also has fewer hallucinations, aligning with OpenAI's focus on improving factual accuracy, as seen in TechTarget (opens in a new tab).
  • GPT-4o: While GPT-4o is multimodal, focusing on text, audio, and image inputs, GPT-4.5 seems to prioritize text-based interactions with enhanced knowledge. Benchmarks show GPT-4.5 outperforming GPT-4o in math and science, but specific multimodal comparisons are limited, as per Vellum (opens in a new tab).
  • Reasoning Models (o1, o3-mini): These models, designed for chain-of-thought reasoning, may outperform GPT-4.5 in specialized tasks like math and science, as noted in MIT Technology Review (opens in a new tab). However, GPT-4.5's general-purpose strength makes it more versatile for broad applications.

Comparisons with Competitors

Direct comparisons with competitor models are less detailed, but we can infer based on available information:

  • Anthropic's Claude: Claude models, like Claude 3.5 Sonnet, are strong in reasoning tasks, and Vellum (opens in a new tab) suggests they might be better for advanced problem-solving. Specific benchmarks against GPT-4.5 are not widely available, but its general-purpose focus could compete well in conversational settings.
  • Google's Gemini: Gemini 1.5 Pro, as per Bito (opens in a new tab), shows strengths in video understanding, but direct comparisons with GPT-4.5 are limited. GPT-4.5's larger context window and efficiency might give it an edge in text-heavy tasks.

Pricing and Accessibility

An unexpected detail is the high API cost, with developers charged $75 per million input tokens and $150 per million output tokens, as reported in TechCrunch (opens in a new tab). This is significantly higher than GPT-4o ($2.50 input, $10 output), raising questions about cost-effectiveness, especially given some benchmark limitations, as noted in an X post by optionsly (opens in a new tab).

Conclusion

GPT-4.5 is a robust addition to OpenAI's portfolio, offering enhanced knowledge, reduced hallucinations, and strong conversational abilities. Its 128,000-token context window and computational efficiency make it suitable for general-purpose tasks, though it may not match specialized reasoning models in all areas. Comparisons with previous models show clear improvements, while competitor analyses suggest it holds its own, particularly in text-based interactions. The high API cost, however, introduces a potential barrier, especially for developers, and its long-term viability is under evaluation by OpenAI, as mentioned in TechCrunch (opens in a new tab).

This release underscores OpenAI's focus on scaling up for broader knowledge, but also highlights the challenges of balancing performance with cost, a topic likely to evolve as more user feedback and benchmarks emerge.

Key Citations

📚
    Top 15 Open Source Data Visualization Tools for 2025