GPT-4.5 vs Gemini 2.5 Pro: What is the differences?
GPT-4.5 and Gemini 2.5 Pro represent two of the most advanced large language models (LLMs) available today, each showcasing distinct approaches to scaling AI capabilities. Launched by OpenAI and Google DeepMind respectively, they set new benchmarks for performance in reasoning, multimodal understanding, and real-world application. This article examines their origins, architectures, capabilities, and practical trade-offs, providing a comprehensive comparison between GPT-4.5 and Gemini 2.5 Pro.
What is GPT-4.5?
GPT-4.5 is introduced as OpenAI’s largest, most capable chat-optimized model, available initially as a research preview to Pro users. Released on February 27, 2025, it expands on GPT-4 by scaling both pre-training data and optimization techniques, resulting in improved pattern recognition, reduced hallucinations, and a broader base of general knowledge. Early testers report that interactions feel more natural and intuitive, showcasing enhanced “EQ” that bolsters tasks such as writing assistance, code generation, and problem solving. OpenAI’s safety evaluations highlight fewer instances of unsafe outputs, positioning GPT-4.5 as a step toward more robust alignment with human intent.
Despite being the most sophisticated unsupervised model in OpenAI’s lineup, GPT-4.5 was released as a research preview to gather feedback on its strengths and limitations. Early evaluations highlighted its improved ability to follow user intent, generate nuanced responses, and reduce factual errors—addressing some limitations observed in GPT-4 before it. However, OpenAI clearly stated that GPT-4.5 does not “think before it responds,” emphasizing that reasoning-centric models (like their o1 and o3-mini variants) remain distinct research paths.
What is Gemini 2.5 Pro
Google’s Gemini 2.5 Pro debuted at Google I/O 2025 (May 20, 2025), heralded as “our most advanced Gemini model” with native multimodal support, reasoning capabilities, and a brand-new “Deep Think” mode for complex tasks. Building upon prior Gemini releases (e.g., Gemini 2.0 Flash and Pro in early 2025), Google DeepMind integrated Mixture-of-Experts (MoE) architecture to activate relevant neural pathways based on input types—text, audio, images, video, or code—thereby optimizing both efficiency and accuracy.
Unlike GPT-4.5’s unsupervised emphasis, Gemini 2.5 Pro was engineered specifically to excel at reasoning benchmarks, outperforming competitors on tasks spanning mathematics, coding, factual retrieval, and multimodal understanding. It also features a massive context window—1 million tokens by default, extendable to 2 million—enabling the model to process entire code repositories, long documents, or multihour audio transcripts in a single session. General availability for Gemini 2.5 Pro was slated for June 2025, with free access provided to all users, while Google One AI Premium subscribers enjoy higher rate limits and extended feature sets.
Quick comparison
| Attribute | GPT-4.5 | Gemini 2.5 Pro |
|---|---|---|
| Model Name | GPT-4.5 | Gemini 2.5 Pro |
| Developer | OpenAI | Google DeepMind |
| Release Date | February 27, 2025 | May 20, 2025 |
| Architecture Type | Transformer-based unsupervised scaled model | Mixture-of-Experts (MoE) multimodal architecture |
| Multimodal Support | Limited (text with some image input in ChatGPT) | Full (text, audio, images, video, code) |
| Context Window | 32,000 tokens | 1,000,000 tokens (extendable to 2,000,000 tokens) |
| Pricing/Access | ChatGPT Pro ($20/month), API: $75/$150 per million tokens | Free basic access; AI Premium ($19.99/month), API via Google AI Studio & Vertex AI |
| Key Strengths | High conversational fluency, emotional intelligence, broad knowledge | Deep reasoning, massive memory context, strong multimodal processing |
GPT-4.5 vs Gemini 2.5 Pro: Architecture & Training methodologies
GPT-4.5 training and architecture
OpenAI’s GPT-4.5 builds on two complementary paradigms: scaling unsupervised learning and preparing for future reasoning capabilities. The pre-training dataset and compute budgets were significantly expanded, leveraging Microsoft Azure AI supercomputers. While GPT-4 prioritized a mix of unsupervised learning and reinforcement learning with human feedback (RLHF), GPT-4.5 emphasizes more extensive unsupervised pre-training to capture nuanced world models. Post-training fine-tuning focuses on human preferences, enhancing empathetic and collaborative behaviors. Although GPT-4.5 does not perform explicit chain-of-thought reasoning at inference, its larger parameter count and data diversity lead to more coherent, context-aware outputs in creative and conversational settings .
Gemini 2.5 Pro training and architecture
Gemini 2.5 Pro represents a melding of base-model improvements with extensive post-training optimization—a shift referred to as “Gemini 2.5.” During pre-training, DeepMind increased parameter counts and multimodal alignment, enabling the model to ingest and reason over heterogeneous data types. The “Deep Think” mode, introduced in May 2025, augments Gemini’s architecture with an explicit reasoning pipeline: the model can generate intermediate “thought” steps to solve complex tasks, akin to chain-of-thought but integrated within the main inference. Post-training alignment employs human-in-the-loop evaluations to refine safety and factuality. The result is a model capable of analyzing large datasets, codebases, and media inputs concurrently, positioning it as a flexible tool for reasoning, coding, and multimedia generation.
GPT-4.5 vs Gemini 2.5 Pro: Reasoning, Coding, and Multimodal tasks?
Reasoning benchmarks
In pure reasoning tasks, Gemini 2.5 Pro consistently outperforms GPT-4.5. On Humanity’s Last Exam—a dataset designed to push the frontier of knowledge—Gemini 2.5 Pro achieves 18.8% pass@1 without tool use, while GPT-4.5 scores 6.4%. In Google’s internal evaluations, Gemini 2.5 Pro also leads other rivals like Claude 3.7 and Grok 3 Beta. GPT-4.5, by contrast, shows improvement over GPT-4 in reasoning benchmarks, but its focus remains on intuitive conversation rather than direct symbolic or logical tasks. Early tests indicate GPT-4.5 scores competitive marks (e.g., 71.4% on GPQA science), but still trail Gemini’s 84.0% on GPQA diamond .
Mathematical and scientific benchmarks
Gemini 2.5 Pro excels in mathematics: it achieves 92.0% on AIME 2024 and 86.7% on AIME 2025 (pass@1), whereas GPT-4.5 reaches only 36.7% on AIME 2024 and does not publicly report on AIME 2025. In science benchmarks, Gemini’s single-attempt GPQA diamond score is 84.0%, outpacing GPT-4.5’s 71.4%. This gap highlights Gemini’s advanced mathematical reasoning and scientific problem-solving capabilities, attributable to specialized training on STEM-focused datasets and the Deep Think reasoning mechanism. GPT-4.5’s improvements are notable compared to GPT-4 (from 53.6% to 71.4% on GPQA), yet it remains less optimal for rigorous academic tasks.
Coding and agentic tasks
On coding and agentic benchmarks, Gemini 2.5 Pro leads again. On SWE-Bench Verified—a standard for agentic code evaluations—Gemini attains 63.8% pass@1 with a custom agent setup, versus GPT-4.5’s 38.0%. Gemini also posts 74.0% whole/diff on Aider Polyglot for code editing, well above GPT-4.5’s 44.9% diff. In live coding challenges (LiveCodeBench v5), GPT-4.5’s performance isn’t publicly disclosed, but GPT-4 scored 44% on code editing tasks—suggesting GPT-4.5 may reach around 45–50%, still below Gemini’s 70.4%. The larger context window (1 million tokens) allows Gemini to process and edit large codebases natively. GPT-4.5, with a shorter context window, relies on chunking strategies for lengthy code, making its agentic capabilities more limited in scale .
Multimodal capabilities
Gemini 2.5 Pro inherently supports multimodal inputs (text, audio, images, video) and outperforms GPT-4.5 on visual reasoning benchmarks: on MMMU, Gemini scores 81.7% (single attempt), while GPT-4.5 registers 74.4%. On image understanding (Vibe-Eval), Gemini reaches 69.4%, while GPT-4.5 lack published performance. Gemini’s 1 million-token window enables it to concurrently analyze large media sequences; GPT-4.5 supports image inputs and file uploads but has no video or audio processing at launch. Gemini’s multimodal integration extends into native audio output and real-time video analysis in apps like Google AI Studio, giving it an edge in cross-modal reasoning and creative tasks involving complex inputs .
GPT-4.5 vs Gemini 2.5 Pro: Practical Applications and Use
GPT-4.5 applications: writing, programming, and collaboration
OpenAI emphasizes GPT-4.5’s strengths in creative collaboration and emotional intelligence. Early adopters use it for nuanced writing tasks—drafting marketing copy, refining literature, and generating creative storylines—because of its improved “EQ” and understanding of subtle cues. In programming, GPT-4.5 excels at guiding developers through debugging, offering code refactors, and providing explanations for algorithms; however, its performance trails Gemini on large codebases. GPT-4.5’s integration with ChatGPT allows seamless file and image uploads, enabling users to iterate on documents, design assets, and data analyses within the same chat interface. Use cases extend to customer support automation, tutoring, and personalized coaching, where its empathetic responses enhance user engagement .
Gemini 2.5 Pro applications: advanced reasoning, multimedia, and enterprise AI
Gemini 2.5 Pro is positioned for high-end research, enterprise analytics, and advanced content creation. In financial analysis, for instance, its ability to parse entire earnings call transcripts (hundreds of pages) in one prompt helps generate comprehensive reports. In scientific research, users leverage its Deep Think mode for designing experiments and hypothesis testing. Its native video and audio understanding enables media companies to generate transcripts, edit multimedia content, and even create short films with synchronized audio. In coding teams, Gemini can ingest large code repositories, propose architectural refactors, and prototype new features—all in a single prompt. Enterprise customers using Vertex AI gain scalable access to these capabilities, integrating Gemini 2.5 Pro into workflows across Google Workspace, YouTube content generation, and AI-driven design tools like Imagen 4 and Veo 3 .
GPT-4.5 vs Gemini 2.5 Pro: Cost, Accessibility, Deployment Considerations
GPT-4.5 availability and pricing
GPT 4.5 launched initially as a research preview for ChatGPT Pro subscribers (\$200/month) starting February 2025. Rolling out to ChatGPT Plus, Team, Enterprise, and Edu users occurred in stages through March 2025. For developers, GPT-4.5 is accessible via the Chat Completions API, Assistants API, and Batch API—though usage is “more expensive” than GPT-4o, with rates of approximately \$75 per million input tokens and \$150 per million output tokens during the preview phase. Microsoft Azure’s OpenAI Service also offers GPT-4.5 in preview, but typically at enterprise-grade pricing tiers.
Because of its compute intensity, GPT 4.5 may not be cost-effective for routine tasks; organizations must weigh the benefit of its higher emotional intelligence and creativity against budget constraints. OpenAI has indicated that they are evaluating the model’s long-term viability in the API, depending on user feedback about unique use-cases where GPT 4.5 outperforms lighter models.
Gemini 2.5 Pro availability and pricing
Gemini 2.5 Pro Experimental initially launched on Google AI Studio and Gemini Advanced users in late March 2025, with general availability on Vertex AI and Google Cloud by June 2025. Gemini Advanced is bundled into the new “AI Ultra” subscription at $250/month, granting priority access to Gemini 2.5 Pro, Veo 3, Imagen 4, and Flow tools. Vertex AI customers can provision dedicated instances of Gemini 2.5 Pro, though pricing details depend on usage tiers and GPU/TPU allocations. Early indicators suggest enterprise contracts include volume discounts, but per-token costs may surpass GPT-4.5’s in high-throughput scenarios due to the larger context window and multimodal compute demands. Researchers can apply for free access under Google’s Academic Grants program, encouraging evaluation on complex tasks before full production deployment.
Getting Started
CometAPI provides a unified REST interface that aggregates hundreds of AI models—including ChatGPT family—under a consistent endpoint, with built-in API-key management, usage quotas, and billing dashboards. Instead of juggling multiple vendor URLs and credentials.
Developers can access latest chatgpt API GPT-4.5 API (model name: gpt-4.5-preview ;gpt-4.5)and Gemini 2.5 Pro API through CometAPI. To begin, explore the model’s capabilities in the Playground and consult the API guide for detailed instructions. Before accessing, please make sure you have logged in to CometAPI and obtained the API key. CometAPI offer a price far lower than the official price to help you integrate:
| Category | GPT-4.5 | gemini 2.5 pro |
| Price in CometAPI | Input Tokens: $60 / M tokens | Input Tokens: $1/ M tokens |
| Output Tokens: $120 / M tokens | Output Tokens: $8 / M tokens | |
| model name | gpt-4.5-preview ;gpt-4.5 | gemini-2.5-pro-preview-05-06 |
Conclusion:
As of June 2025, GPT-4.5 and Gemini 2.5 Pro stand at the forefront of AI research and application. GPT-4.5’s emphasis on natural, emotionally attuned collaboration advances AI’s role in creative industries, customer service, and education. It signals OpenAI’s commitment to gradually blending unsupervised learning with future reasoning capabilities, setting the stage for more versatile agents. Meanwhile, Gemini 2.5 Pro’s integrated reasoning (“Deep Think”), extended context windows, and multimodal processing showcase a vision of AI that can handle enterprise-scale tasks—from processing lengthy legal documents to generating multimedia content on demand.
Both models will likely influence each other: OpenAI may explore multimodal reasoning pipelines, while Google DeepMind could emphasize improved conversational empathy. The competition accelerates innovation across benchmarks, cost optimizations, and safety frameworks. As enterprises and developers adopt these technologies, real-world feedback will shape the next iterations—GPT-5 and Gemini 3.0—focusing on scalable reasoning, lowered deployment costs, and deeper alignment. Ultimately, the GPT-4.5 vs. Gemini 2.5 Pro era underscores a broader shift toward AI systems designed not only for accuracy but for seamless integration into human workflows and creative processes, heralding an increasingly collaborative future between humans and machines.
