Compare API pricing for 53 OpenAI models suited for coding: GPT-4o, o3, o1, GPT-4.1, and budget-friendly mini variants. See per-token costs, cost per coding request, context windows, and coding capabilities side by side.
Cost/Req = estimated cost per typical coding request (2,000 input + 1,000 output tokens). Prices via OpenRouter API.
GPT-5.4 Pro is OpenAI's most advanced model, building on GPT-5.4's unified architecture with enhanced reasoning capabilities for complex, high-stakes tasks. It features a 1M+ token context window (922K input, 128K output) with support for text and image inputs. Optimized for step-by-step reasoning, instruction following, and accuracy, GPT-5.4 Pro excels at agentic coding, long-context workflows, and multi-step problem solving.
GPT-5.4 is OpenAI’s latest frontier model, unifying the Codex and GPT lines into a single system. It features a 1M+ token context window (922K input, 128K output) with support for text and image inputs, enabling high-context reasoning, coding, and multimodal analysis within the same workflow. The model delivers improved performance in coding, document understanding, tool use, and instruction following. It is designed as a strong default for both general-purpose tasks and software engineering, capable of generating production-quality code, synthesizing information across multiple sources, and executing complex multi-step workflows with fewer iterations and greater token efficiency.
GPT-5.3-Codex is OpenAI’s most advanced agentic coding model, combining the frontier software engineering performance of GPT-5.2-Codex with the broader reasoning and professional knowledge capabilities of GPT-5.2. It achieves state-of-the-art results on SWE-Bench Pro and strong performance on Terminal-Bench 2.0 and OSWorld-Verified, reflecting improved multi-language coding, terminal proficiency, and real-world computer-use skills. The model is optimized for long-running, tool-using workflows and supports interactive steering during execution, making it suitable for complex development tasks, debugging, deployment, and iterative product work. Beyond coding, GPT-5.3-Codex performs strongly on structured knowledge-work benchmarks such as GDPval, supporting tasks like document drafting, spreadsheet analysis, slide creation, and operational research across domains. It is trained with enhanced cybersecurity awareness, including vulnerability identification capabilities, and deployed with additional safeguards for high-risk use cases. Compared to prior Codex models, it is more token-efficient and approximately 25% faster, targeting professional end-to-end workflows that span reasoning, execution, and computer interaction.
GPT-5.2-Codex is an upgraded version of GPT-5.1-Codex optimized for software engineering and coding workflows. It is designed for both interactive development sessions and long, independent execution of complex engineering tasks. The model supports building projects from scratch, feature development, debugging, large-scale refactoring, and code review. Compared to GPT-5.1-Codex, 5.2-Codex is more steerable, adheres closely to developer instructions, and produces cleaner, higher-quality code outputs. Reasoning effort can be adjusted with the `reasoning.effort` parameter. Read the [docs here](https://openrouter.ai/docs/use-cases/reasoning-tokens#reasoning-effort-level) Codex integrates into developer environments including the CLI, IDE extensions, GitHub, and cloud tasks. It adapts reasoning effort dynamically—providing fast responses for small tasks while sustaining extended multi-hour runs for large projects. The model is trained to perform structured code reviews, catching critical flaws by reasoning over dependencies and validating behavior against tests. It also supports multimodal inputs such as images or screenshots for UI development and integrates tool use for search, dependency installation, and environment setup. Codex is intended specifically for agentic coding applications.
GPT-5.2 Pro is OpenAI’s most advanced model, offering major improvements in agentic coding and long context performance over GPT-5 Pro. It is optimized for complex tasks that require step-by-step reasoning, instruction following, and accuracy in high-stakes use cases. It supports test-time routing features and advanced prompt understanding, including user-specified intent like "think hard about this." Improvements include reductions in hallucination, sycophancy, and better performance in coding, writing, and health-related tasks.
OpenAI coding models power many of the most popular AI development tools. Here is how they integrate with the leading coding assistants.
Uses GPT-4o and o3 as backend models for code completion, chat, and multi-file editing. OpenAI models are available via Cursor's Pro plan alongside Claude and other providers.
Best models for CursorBuilt on OpenAI models including GPT-4o and o3-mini. Copilot uses these models for inline suggestions, chat, and code review. Enterprise plans offer access to the latest reasoning models.
Anthropic's CLI coding agent uses Claude models natively, but OpenAI models serve as a useful comparison point. Many developers switch between Claude Code and OpenAI-powered tools depending on the task.
Open-source AI pair programming tool with native support for all OpenAI models. Aider's benchmarks show GPT-4o and o3 performing strongly on code editing tasks. Supports function calling for precise file modifications.
Estimated cost per coding request based on 2,000 input tokens (prompt + code context) and 1,000 output tokens (generated code). Sorted from cheapest to most expensive.
GPT-4o and GPT-4.1 are OpenAI's best general-purpose coding models. They support function calling, JSON mode, and multimodal input, making them ideal for code generation, debugging, refactoring, and code review. GPT-4.1 improves on instruction following and has better performance on complex coding tasks.
The o-series reasoning models use chain-of-thought to tackle complex algorithms, multi-step debugging, and architectural decisions. o3 is the latest and most capable, while o1 offers strong reasoning at a lower cost. These models are best for tasks requiring deep logical reasoning rather than simple code generation.
GPT-4o Mini offers coding capabilities at a fraction of the cost. While it scores lower on complex benchmarks, it handles straightforward code generation, autocompletion, and simple debugging efficiently. Ideal for high-volume use cases like CI/CD pipelines and automated code review.
The original Codex model (code-davinci-002) was deprecated in March 2023. All Codex capabilities have been absorbed into the GPT-4 family, which significantly outperforms the original Codex on every coding benchmark. Developers should use GPT-4o or GPT-4.1 as direct Codex replacements.
For most coding tasks, GPT-4o and GPT-4.1 offer the best balance of code quality and cost. For complex algorithmic or multi-step reasoning problems, o3 and o1 excel due to their chain-of-thought reasoning capabilities. GPT-4o Mini is ideal for high-volume code generation where cost efficiency is the priority.
The original OpenAI Codex model has been deprecated and replaced by the GPT-4 family. Current coding-capable models range from free (GPT-4o Mini in some tiers) to $60/M output tokens (o3-pro). A typical coding request (2,000 input + 1,000 output tokens) costs between $0.0003 and $0.06 depending on the model.
Yes. GPT-4o is one of the best models for coding. It supports function calling, JSON mode, and has strong performance on coding benchmarks like HumanEval and SWE-bench. It offers multimodal input (you can share screenshots of errors), a large context window, and competitive pricing for production coding workflows.
Both are excellent for coding. OpenAI's o3 and GPT-4.1 lead on certain benchmarks, while Anthropic's Claude 3.5 Sonnet and Claude 4 Opus excel in agentic coding tasks and long-context understanding. Claude tends to follow instructions more precisely, while OpenAI models often have broader tool ecosystem support. The best choice depends on your specific use case, budget, and tooling requirements.