OpenAI

GPT-5.2

OpenAI

GPT-5.2 is OpenAI's flagship frontier model series designed for professional knowledge work, advanced coding, and agentic workflows. Released in December 2025 as a response to competitive pressures, it features a massive 400,000-token context window and a 128,000-token maximum output capacity. The model utilizes a Mixture-of-Experts (MoE) architecture to balance inference efficiency with deep reasoning capabilities. It is available in three variants—Instant, Thinking, and Pro—each optimized for different points on the latency-intelligence curve. GPT-5.2 demonstrates state-of-the-art performance in tool calling reliability (98.7%), coding (SWE-Bench Verified 80.0%), and long-context retrieval.

GPT-5.1

OpenAI

GPT-5.1 is a frontier-grade multimodal language model family released by OpenAI in November 2025. It introduces a unified system architecture featuring a 'Smart Router' that dynamically allocates compute resources between two primary modes: 'Instant' (optimized for low latency and conversational warmth) and 'Thinking' (optimized for deep, adaptive reasoning). The model utilizes a Sparse Mixture-of-Experts (MoE) architecture with a central language backbone and attachable modules, allowing it to process text, audio, image, and video inputs natively. Key capabilities include adaptive test-time compute, where the model adjusts its reasoning depth based on query complexity, and enhanced personalization options with distinct personality presets. It demonstrates significant improvements in instruction following, coding (via the Codex variants), and mathematical reasoning compared to its predecessor, GPT-5.

GPT-OSS-120B

OpenAI

GPT-OSS-120B is a state-of-the-art open-weight language model that delivers strong real-world performance at low cost. This 120 billion parameter mixture-of-experts model achieves near-parity with OpenAI o4-mini on core reasoning benchmarks while running efficiently on a single 80 GB GPU. It was trained using reinforcement learning and techniques informed by OpenAI's most advanced internal models, including o3 and other frontier systems.

GPT-OSS-20B

OpenAI

GPT-OSS-20B is a medium-sized open-weight language model that delivers similar results to OpenAI o3‑mini on common benchmarks and can run on edge devices with just 16 GB of memory. This makes it ideal for on-device use cases, local inference, or rapid iteration without costly infrastructure. Despite its smaller size, it demonstrates strong performance on reasoning tasks, tool use, and competition mathematics.

o3

OpenAI

OpenAI's most powerful reasoning model that pushes the frontier across coding, math, science, visual perception, and more. Sets new state-of-the-art on benchmarks including Codeforces, SWE-bench, and MMMU. Features full tool access and can agentically use and combine every tool within ChatGPT.

o4-mini

OpenAI

A smaller model optimized for fast, cost-efficient reasoning. Achieves remarkable performance for its size and cost, particularly in math, coding, and visual tasks. It is the best-performing benchmarked model on AIME 2024 and 2025, with significantly higher usage limits than o3.

GPT-4.1

OpenAI

Flagship GPT model for complex tasks. It is well suited for problem solving across domains. Features major improvements in coding, instruction following, and long context comprehension.

GPT-4.1 mini

OpenAI

Smaller version of GPT-4.1 optimized for coding and instruction following while maintaining the 1M token context window. Designed for applications requiring strong coding capabilities with better efficiency.

GPT-4.1 nano

OpenAI

Most compact version of GPT-4.1 family, optimized for efficiency while maintaining strong coding and instruction following capabilities. Designed for applications requiring low latency and cost.

GPT-4.5

OpenAI

A research preview of OpenAI's largest and most capable GPT model to date. GPT-4.5 represents a significant advancement in scaling unsupervised learning, delivering broader world knowledge, dramatically reduced hallucinations (37.1% vs 61.8% for GPT-4o), and enhanced emotional intelligence for more natural human collaboration. Excels at creative tasks, writing assistance, and complex problem-solving with improved factual accuracy and nuanced understanding of user intent.

o1-mini

OpenAI

Faster, cost-efficient reasoning model optimized for coding and agentic applications. 80% cheaper than o1-preview with strong capabilities for complex problem-solving in tasks where context is provided within the prompt.

o1-preview

OpenAI

Large reasoning model with strong capabilities for solving hard problems through extended thinking. Designed to spend more time reasoning before responding, with enhanced performance in science, coding, and math.

o1

OpenAI

The o1 model series is trained with large-scale reinforcement learning to reason using chain-of-thought. OpenAI o1 is the next model in this series (previously OpenAI o1-preview), with advanced reasoning capabilities that provide new avenues for improving safety and robustness. The model can reason about safety policies in context when responding to potentially unsafe prompts, through deliberative alignment.

GPT-4o

OpenAI

GPT-4o ('o' for 'omni') is a step towards much more natural human-computer interaction—it accepts as input any combination of text, audio, image, and video and generates any combination of text, audio, and image outputs. It can respond to audio inputs in as little as 232 milliseconds, with an average of 320 milliseconds, which is similar to human response time in a conversation. It matches GPT-4 Turbo performance on text in English and code, with significant improvement on text in non-English languages, while also being much faster and 50% cheaper in the API. GPT-4o is especially better at vision and audio understanding compared to existing models.

GPT-4 Turbo

OpenAI

Improved version of GPT-4 with significantly expanded context window, more recent knowledge cutoff, and optimized performance. Designed for production applications with better cost efficiency than the base GPT-4.

GPT-3.5 Turbo 16K

OpenAI

Extended context version of GPT-3.5 Turbo with a 16K token context window. Optimized for chat applications with improved instruction following and reduced hallucinations compared to base GPT-3.5.

GPT-4

OpenAI

Fourth-generation GPT model, with greatly improved reasoning and multimodal capabilities (accepts text and images). Model size not publicly disclosed (rumored ~1.7 trillion parameters). Achieved human-level performance on many academic and professional benchmarks.

GPT-3.5 Turbo

OpenAI

OpenAI's public conversational AI based on GPT-3.5. Fine-tuned for dialogue via RLHF, leading to widespread adoption in late 2022. Marked the first widely accessible GPT-powered chatbot.

InstructGPT/GPT-3.5

OpenAI

Instruction-tuned version of GPT-3 (a.k.a GPT-3.5) refined via Reinforcement Learning from Human Feedback (RLHF). Powers the initial version of ChatGPT (Dec 2022). Optimized for following user instructions safely.

Codex

OpenAI

A GPT-3-descendent model fine-tuned on billions of lines of source code from publicly available sources, including code in public GitHub repositories. Powers GitHub Copilot for code autocompletion and demonstrated strong coding ability (solving ~28% of HumanEval at 12B params). Most capable in Python, but proficient in over a dozen languages including JavaScript, Go, Perl, PHP, Ruby, Swift, TypeScript, and Shell.

GPT-3

OpenAI

175B-parameter GPT series model that set new benchmarks in few-shot learning and text generation. Demonstrated impressive zero-shot capabilities across NLP tasks.

GPT-2

OpenAI

Generative Pre-trained Transformer 2 (GPT-2) is a large language model by OpenAI and the second in their foundational series of GPT models. It was pre-trained on a dataset of 8 million web pages (WebText) and was a direct scale-up of GPT-1 with a ten-fold increase in both parameter count and training dataset size. Initially partially withheld due to concerns about potential misuse, the full model was released in November 2019.

GPT-1

OpenAI

Generative Pre-trained Transformer 1 (GPT-1) was the first of OpenAI's large language models, demonstrating unsupervised pre-training with a 12-layer decoder-only Transformer. It introduced a two-stage training process leveraging the BookCorpus dataset and achieved improvements across various NLP tasks.