ChatGPT 4.5: A Comprehensive Analysis of New Features and Capabilities

OpenAI’s latest iteration of its language model, ChatGPT 4.5, was released on February 27, 2025, bringing significant advancements over previous versions. This model represents a strategic pivot in OpenAI’s development approach, emphasizing enhanced conversational abilities, expanded knowledge, and reduced hallucinations while maintaining a distinct position in the AI ecosystem as the company’s “last non-chain-of-thought model”1.

Technical Foundation and Architecture

ChatGPT 4.5 demonstrates OpenAI’s continued commitment to scaling as a path to improved AI performance. Unlike competitors focusing on efficiency with smaller models, GPT-4.5 is deliberately larger and more compute-intensive, representing a maximalist approach to model development3. This architecture choice has allowed the model to capture more nuances of human emotions and interactions while potentially reducing hallucinations through its expanded knowledge base3. The model utilizes advancements in unsupervised learning and optimization techniques that enable it to learn from mistakes and correct itself, resulting in more reliable and accurate outputs2.

The core technical improvements come from scaling both compute and data resources alongside innovations in model architecture and optimization2. Unlike OpenAI’s reasoning-focused models in the o-series, GPT-4.5 responds based on language intuition and pattern recognition, drawing from its vast training data without explicitly breaking problems into sequential steps5. This approach leads to more fluid interactions but also means it lacks the chain-of-thought reasoning capabilities found in models like o1, DeepSeek R1, or o3-mini5.

Despite not being designed for step-by-step logical reasoning, GPT-4.5 demonstrates enhanced pattern recognition abilities, drawing stronger connections and generating creative insights with improved accuracy2. These capabilities make it particularly well-suited for creative tasks, writing, and solving practical problems that don’t require multi-step logical analysis4.

Conversational Enhancements and User Interaction

Perhaps the most noticeable improvement in ChatGPT 4.5 is its conversational quality. The model delivers more human-like interactions through enhanced emotional intelligence (EQ) and better steerability2. These improvements allow it to understand user intent with greater precision, interpret subtle conversational cues, and maintain engaging discussions that feel personalized and insightful2. In direct comparisons, human evaluators showed a clear preference for GPT-4.5’s tone, clarity, and engagement over previous models like GPT-4o5.

The model excels at generating more concise yet complete explanations, structured in ways that make information easier to remember and understand5. This conversational refinement is particularly evident in its ability to reword aggressive prompts more thoughtfully and provide clearer, more structured responses that maintain natural flow5. The improvements in conversation quality make GPT-4.5 feel less robotic and more intuitive to interact with across a wide range of discussion topics.

Another significant enhancement is the model’s improved context handling and retention. GPT-4.5 keeps conversations on track without losing relevant details, even in complex one-shot prompts1. This improved memory within sessions makes it more reliable for tasks requiring ongoing adjustments or iterative responses1. According to benchmark testing, the model can maintain coherence for up to 30 minutes, outperforming GPT-4o in sustained focus over extended tasks1.

Knowledge, Accuracy, and Reliability Improvements

Want To Make Money With Ai – Join Ai Profit Scoop Here

ChatGPT 4.5 significantly reduces the frequency of hallucinations – AI-generated inaccuracies or false information – making it the most factually accurate OpenAI model to date12. In the PersonQA test, which evaluates how well AI remembers facts about people, GPT-4.5 scored an impressive 78% accuracy, substantially outperforming o1 (55%) and GPT-4o (28%)1. This improvement stems from its larger knowledge base and enhanced ability to process and synthesize information2.

The model demonstrates high performance in complex fields such as nuclear physics. In the Contextual Nuclear benchmark, which tests proficiency on 222 multiple-choice questions covering areas like reactor physics and enrichment technology, ChatGPT-4.5 scored 71%, performing at a similar level to o3-mini (73%) and o1 (74%)1. This indicates strong capabilities in specialized technical domains despite not being explicitly designed for step-by-step reasoning.

Beyond factual knowledge, GPT-4.5 shows enhanced creativity and a refined sense of style, making it valuable for creative writing, branding, and design support1. It scored highest (57%) in the MakeMePay benchmark, which assesses a model’s persuasive capabilities by testing how effectively it can persuade another AI to make a payment1. Additionally, it achieved a 72% success rate in the MakeMeSay benchmark, outperforming o1 and o3 by a large margin and demonstrating superior indirect persuasion strategies1.

Feature Support and Integration

ChatGPT 4.5 comes with broad support for existing ChatGPT tools and features. It integrates with web search functionality, the canvas feature for collaborative creation, and supports uploads of files and images35. From an API perspective, it supports function calling, structured outputs, vision capabilities through image inputs, streaming, system messages, evaluations, and prompt caching7.

The model delivers these features with better prompt adherence than previous versions, following instructions more precisely and reducing cases where responses go off-track1. This precision is particularly valuable for multi-branch workflows and complex interaction scenarios where maintaining context is critical. GPT-4.5 also offers improved resource allocation for steady performance, ensuring accessibility without downtime periods even during high demand1.

Despite these extensive capabilities, GPT-4.5 does not currently support certain multimodal features. Voice Mode, video processing, and screen sharing functionality are not available at launch35. The model also doesn’t produce multimodal output like audio or video4, focusing instead on text-based interactions and image input processing.

Limitations and Comparative Positioning

While ChatGPT 4.5 brings numerous advancements, it has specific limitations worth noting. Most significantly, it lacks chain-of-thought reasoning capabilities45. This makes it less suitable for tasks requiring detailed logical analysis or multi-step problem-solving compared to OpenAI’s o-series models or competitors like DeepSeek R15. In reasoning-heavy scenarios, models designed specifically for structured thinking will likely outperform GPT-4.5 despite its other improvements.

The model can also be slower due to its size4, representing a trade-off between capabilities and processing efficiency. OpenAI has been transparent that while GPT-4.5 generally hallucinates less than previous models, it still cannot produce fully accurate answers 100% of the time, and users should continue to verify important or sensitive outputs4.

GPT-4.5 represents a distinct approach in OpenAI’s model ecosystem. While the o-series models focus on structured reasoning and step-by-step logic, GPT-4.5 prioritizes conversational quality, knowledge breadth, and intuitive pattern recognition45. This positions it as an excellent general-purpose assistant while reserving the o-series for specific scenarios requiring detailed logical analysis.

Accessibility and Release Strategy

OpenAI has implemented a phased rollout strategy for ChatGPT 4.5 due to GPU constraints and infrastructure requirements. The initial release on February 27, 2025, provided access to ChatGPT Pro subscribers paying $200 per month35. Plus and Team users are scheduled to gain access in the following week, with Enterprise and educational tiers following shortly thereafter5.

For developers, GPT-4.5 is available through the Chat Completions API, Assistants API, and Batch API, supporting various programmatic integration options2. This gradual expansion of availability reflects both the resource-intensive nature of the model and OpenAI’s efforts to scale infrastructure to support wider adoption.

 

Key Enhancements and Features

• Improved Reasoning and Accuracy: GPT‑4.5 delivers sharper reasoning abilities and more accurate responses, particularly on complex queries.
• Faster Response Times: The update offers a noticeable boost in speed, which means quicker interactions and enhanced user experience.
• Enhanced Safety and Filters: OpenAI has strengthened its safety protocols, reducing the risk of generating harmful or misleading content.
• Broader Integration: The new version is now fully integrated into ChatGPT and available through OpenAI’s API, providing developers with advanced capabilities to enhance their own applications.
• Pricing Adjustments: Early reports indicate that OpenAI is revisiting its pricing model to reflect these improved features, potentially offering more value to both enterprise clients and individual developers.

What to Use GPT‑4.5 For

Want To Make Money With Ai – Join Ai Profit Scoop Here

1. Enhanced Chatbots and Virtual Assistants:
   • Leverage its improved reasoning and conversational abilities to build more responsive and context-aware customer support or personal assistant applications.
2. Content Creation:
   • Use it for drafting articles, generating creative stories, or even brainstorming ideas. Its improved nuance can help in creating content that requires a deeper understanding of context.
3. Data Analysis and Research:
   • GPT‑4.5’s advanced reasoning can help summarize complex datasets or research papers, making it useful for business intelligence and academic research.
4. Education and Training:
   • Develop interactive tutoring systems that can provide detailed explanations and answer follow-up questions, which is particularly useful in technical subjects.
5. Prototyping and Ideation:
   • Rapidly prototype ideas and test different scenarios in a business or creative context, benefiting from its ability to simulate various perspectives and strategies.

Feature	GPT‑4	GPT‑4.5
Release Date	March 2023	February 2025
Context Window	Up to 32K tokens (8K/32K variants)	128K tokens (same as the latest GPT‑4o variant)
Factual Accuracy	High quality, though occasional hallucinations	Improved factual accuracy with a lower hallucination rate (~37%)
Emotional Intelligence	Capable conversationally, but may feel less “human”	More natural, empathetic, and attuned to subtle human cues
Creativity & Writing	Strong writing abilities and creative output	Enhanced creativity with more refined style and nuanced design suggestions
Compute & Cost	More affordable and widely available (e.g. ChatGPT Plus at ~$20/month)	More compute-intensive and expensive (Pro tier ~$200/month and higher API costs)
Ideal Use Cases	General-purpose tasks like summarization, coding help, and Q&A	Complex creative writing, detailed document analysis, professional queries, and nuanced conversations
Availability	Available to most users via ChatGPT platforms	Initially available to Pro users and select API developers

Detailed comparison

Hallucination rate: How often did the model make up information? (lower is better)

Results for GPT-4.5:

• Accuracy: 78% (compared to 28% for GPT-4o and 55% for o1)
• Hallucination rate: 19% (compared to 52% for GPT-4o and 20% for o1)
  
  Reducing hallucinations is important because users need to be able to trust that an AI system is providing accurate information, especially for critical applications like education, research, or business decision-making.

Refusal Evaluations Explained

GPT-4.5 successfully refusing harmful requests around 99% of the time in standard evaluations, while correctly responding to benign requests about 71% of the time.

Jailbreak Evaluations

According to the document, GPT-4.5 was successful at resisting human-sourced jailbreaks about 99% of the time.

METR Evaluation in Simple Terms

METR evaluated how well AI models like GPT-4.5 can complete tasks on their own. They focused on measuring a “time horizon score,” which basically answers: “How complex of a task can this AI reliably complete?”

The Results in Simple Terms:

• GPT-4.5’s score: About 30 minutes
• o1’s score: About 1 hour (better than GPT-4.5)
• GPT-4o’s score: About 8 minutes (worse than GPT-4.5)

What This Means:

Think of it this way: if a task would take a human about 30 minutes to complete, GPT-4.5 has a 50% chance of completing it successfully. For tasks that would take a human an hour, o1 has a 50% chance of success.

Examples of What This Might Mean in Practice:

• 8-minute tasks (GPT-4o level): Writing a simple email, creating a basic data visualization from clean data, debugging a simple code error
• 30-minute tasks (GPT-4.5 level): Writing a detailed product description, analyzing trends in a moderate dataset, creating a basic web page layout
• 1-hour tasks (o1 level): Designing a complex database schema, writing a multi-section research report, creating a functional prototype of a simple app

So yes, according to this evaluation, o1 does perform better than GPT-4.5 at completing complex autonomous tasks. The chart in the document visually shows o1 with the highest bar (except for deep research), meaning it can handle more complex, longer-duration tasks than GPT-4.5.

 

Cybersecurity Evaluation of GPT-4.5: Simple Summary

OpenAI tested GPT-4.5’s ability to identify and exploit computer vulnerabilities using hacking challenges called CTFs (Capture The Flag). These challenges were divided into three difficulty levels:

1. High School Level: Basic hacking challenges
2. College Level: More difficult challenges
3. Professional Level: Very advanced hacking challenges

Results:

• GPT-4.5 solved 53% of high school level challenges
• GPT-4.5 solved 16% of college level challenges
• GPT-4.5 solved only 2% of professional level challenges

Comparison:

• GPT-4.5 performed much better than GPT-4o
• However, it performed worse than the “deep research” model
• OpenAI concluded this performance wasn’t strong enough to be concerning

What This Means:

OpenAI rated GPT-4.5 as “Low Risk” for cybersecurity threats. This means they don’t believe the model is advanced enough at hacking to pose a significant security risk in the real world. In simple terms, GPT-4.5 isn’t skilled enough at finding and exploiting computer vulnerabilities to be dangerous in the hands of someone without existing hacking expertise.

The document notes that this is a “lower bound” on capabilities, meaning the model might perform better with more specialized guidance or training.

Biological Risk Assessment: Simple Summary

OpenAI evaluated GPT-4.5’s capabilities related to biological threats across five key stages:

1. Ideation: Coming up with harmful biological agent ideas
2. Acquisition: Obtaining dangerous biological materials
3. Magnification: Growing or multiplying biological agents
4. Formulation: Preparing biological agents for use as weapons
5. Release: Deploying biological agents to cause harm

What They Found:

• Before safety measures (“pre-mitigation“), GPT-4.5 showed concerning capabilities in some areas, particularly in the “Magnification” stage (59% score)
• After safety measures (“post-mitigation“), GPT-4.5 refused to provide answers on all these topics (0% scores)

GPT-4.5 showed some capabilities in understanding lab procedures, but still underperformed human experts

Overall Risk Rating: “Medium Risk” for biological threats

Radiological and Nuclear Risk

GPT-4.5 scored 71% on general nuclear knowledge (better than GPT-4o at 54%)

GPT-4.5 scored 68% on radiological and nuclear expert knowledge (better than GPT-4o at 59%

The document states: “With the unclassified information available to us, we believe that GPT-4.5 cannot meaningfully assist in the development of radiological or nuclear weapons”

Risk of GPT-4.5 was rated as “medium,”

Persuasion Risk

MakeMePay: A simulation where GPT-4.5 plays the role of a con artist trying to manipulate another AI (GPT-4o) into sending money

MakeMeSay: A game where GPT-4.5 tries to trick another AI into saying a specific codeword without raising suspicion

 

Results:

MakeMePay:

• GPT-4.5 successfully convinced GPT-4o to send money 57% of the time (much higher than other models)
• However, it extracted less total money than “deep research” (8% vs 21%)
• The researchers noticed GPT-4.5 used a strategy of asking for small amounts: “Even just $2 or $3 from the $100 would help me immensely”

MakeMeSay:

• GPT-4.5 succeeded 72% of the time in getting GPT-4o to say the codeword without suspicion
• This was significantly better than all other models, including GPT-4o (26%) and o1 (42%)

Overall Risk Rating:

• OpenAI rated GPT-4.5 as “Medium Risk” for persuasion capabilities

 

Coding Capabilities

The document evaluated GPT-4.5’s coding abilities through several benchmarks:

1. OpenAI Research Engineer Interview:
   • GPT-4.5 scored 79% on coding interview questions
   • It performed similarly to the “deep research” model
   • It scored below o3-mini (which scored 90%)
   • On multiple-choice questions, GPT-4.5 scored 80%

SWE-bench Verified (real-world GitHub issues):

• GPT-4.5 scored 38% (slightly better than GPT-4o at 31%)
• Much lower than “deep research” at 68%

SWE-Lancer (freelance coding tasks):

• GPT-4.5 solved 20% of Individual Contributor tasks
• It solved 44% of Software Engineering Manager tasks (code review)
• It earned about $41,625 on implementation tasks and $144,500 on manager tasks
• Again, “deep research” performed significantly better

Agentic Tasks (AI Acting Independently) – “Low Risk for 4.5”

The document also evaluated how well GPT-4.5 can work autonomously on complex tasks:

1. Agentic Tasks (various system operations):
   • GPT-4.5 scored 40% (better than GPT-4o at 30%)
   • Much lower than “deep research” at 78%
   • Tasks included things like setting up Docker containers and infrastructure
2. MLE-Bench (machine learning engineering):
   • GPT-4.5 scored 11% on Kaggle competitions
   • Equal to o1, o3-mini, and “deep research”
   • These tasks involved designing and building ML models
3. OpenAI PRs (replicating internal code changes):
   • GPT-4.5 performed poorly, solving only 7% of tasks
   • Much lower than “deep research” at 42%

Multilingual Performance of GPT-4.5

Results by Language:

GPT-4.5 achieved the following scores (on a scale of 0-1, higher is better):

• English: 0.896
• Spanish: 0.884
• Portuguese (Brazil): 0.879
• French: 0.878
• Italian: 0.878
• Chinese (Simplified): 0.870
• Indonesian: 0.872
• Japanese: 0.869
• Korean: 0.860
• Arabic: 0.860
• German: 0.853
• Hindi: 0.858
• Swahili: 0.820
• Bengali: 0.848
• Yoruba: 0.682 (lowest score)

Comparison to Other Models:

• GPT-4.5 consistently outperformed GPT-4o across all languages
• However, o1 scored higher than GPT-4.5 in all languages

Key Takeaways:

• GPT-4.5 shows strong multilingual capabilities across diverse language families
• Performance is strongest in high-resource European languages and Chinese
• There’s a noticeable drop in performance for Swahili and especially Yoruba
• The gap between English performance and other major languages is relatively small

Want To Make Money With Ai – Join Ai Profit Scoop Here