The go-to model for large-codebase reasoning, but its output pricing makes it a considered rather than casual choice.
Professional developers tackling large-scale coding tasks, refactoring legacy codebases, or working across multi-file projects where deep context retention is critical.
400K context window enables full repository ingestion and multi-file code reasoning in a single prompt
Specialized Codex training produces more accurate, idiomatic code generation across Python, TypeScript, Rust, and Go compared to general-purpose GPT-5 variants
Strong at debugging complex stacktraces and proposing minimal, targeted diffs rather than rewriting entire functions
Reliable instruction-following for structured outputs like JSON schemas, API specs, and test suites
See what OpenAI: GPT-5.3-Codex actually costs at your usage level
Based on OpenAI: GPT-5.3-Codex API pricing: $1.75/1M input · $14/1M output. Real costs vary by provider discounts and caching. Check the provider for exact current rates.
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4 data points · tracked daily since May 9, 2026
Professional developers tackling large-scale coding tasks, refactoring legacy codebases, or working across multi-file projects where deep context retention is critical.. Start free — no card required.
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OpenAI's latest agentic flagship for coding, research, computer-use workflows, and long multi-step knowledge work.
Pricing moves, ranking shifts, and capability updates.
OpenAI: GPT-5.3-Codex (OpenAI) is now indexed. It supersedes GPT-5.2. The go-to model for large-codebase reasoning, but its output pricing makes it a considered rather than casual choice.
View modelOpenAI: GPT-5.3-Codex is best for professional developers tackling large-scale coding tasks, refactoring legacy codebases, or working across multi-file projects where deep context retention is critical.. It is a strong fit when that workflow matters more than the tradeoffs around balanced pricing and balanced speed.
You need fast, cheap, iterative code completions at high volume — a smaller model like GPT-5 Mini or Claude Haiku will be significantly more cost-effective for autocomplete-style tasks.
Meta: Llama 3.1 8B Instruct is the lower-cost option to compare first when you want a similar workflow fit with less token spend.
GPT-5.5 is the better pick when response time matters more than maximum depth or premium quality.
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You need fast, cheap, iterative code completions at high volume — a smaller model like GPT-5 Mini or Claude Haiku will be significantly more cost-effective for autocomplete-style tasks.
Output cost of $14/1M tokens makes iterative coding sessions expensive compared to Claude Sonnet 4.6 ($15 output) or Gemini 3.1 Pro, but the asymmetric input/output pricing penalizes verbose code generation specifically
Not a general-purpose creative writing or multimodal model — performance degrades noticeably outside technical domains
No native image input or output support, limiting its use for UI/UX tasks requiring visual context
GPT-4 Turbo is OpenAI's high-capability flagship model featuring a 128K context window, trained on data up to April 2024. It delivers strong reasoning, coding, and instruction-following across complex tasks.
GPT-4 Turbo (v1106) is an older snapshot of OpenAI's flagship GPT-4 Turbo model released in November 2023, offering a 128K context window with strong general-purpose reasoning and instruction-following capabilities. It predates later GPT-4 Turbo updates and GPT-4o, making it a legacy choice for workflows locked to this specific version.
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