The go-to model for large-codebase reasoning, but its output pricing makes it a considered rather than casual choice.
93
Coding
45
Writing
62
Research
0
Images
42
Value
88
Long Context
Use this when
Professional developers tackling large-scale coding tasks, refactoring legacy codebases, or working across multi-file projects where deep context retention is critical.
Skip this if
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.
Pricing
$1.75/1M in
$14.00/1M out
→0%since May 2026
Context
400k tokens
Speed
Balanced
Priced asymmetrically with low input cost ($1.75/1M) and high output cost ($14/1M), which rewards concise prompting but penalizes verbose code generation. The 400K context window is one of the largest available at this price tier. Supersedes GPT-5.2 with improved multi-file coherence; users on GPT-5.2 should migrate. No multimodal input support confirmed at launch.
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
Weaknesses
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
Real-world use cases
What people actually use OpenAI: GPT-5.3-Codex for.
Ingesting an entire Node.js monorepo (200K tokens) and generating a migration plan to TypeScript with annotated file-by-file changes
Debugging a complex Rust async runtime issue by analyzing full call stacks, dependency source code, and test logs in a single context window
Generating a comprehensive OpenAPI 3.1 spec and matching integration test suite from a plain-English product requirements document
Price History
OpenAI: GPT-5.3-Codex pricing over time
→0% since May 9
48 data points · tracked daily since May 9, 2026
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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.
Recommendations are made independently based on real-world use and public benchmarks. See our disclosures for details.
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Pricing moves, ranking shifts, and capability updates.
New ModelMar 27, 2026
OpenAI: GPT-5.3-Codex — added to UseRightAI
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.
OpenAI: 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.
When should I avoid OpenAI: GPT-5.3-Codex?
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.
What is a cheaper alternative to OpenAI: GPT-5.3-Codex?
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.
What is a faster alternative to OpenAI: GPT-5.3-Codex?
GPT-5.5 is the better pick when response time matters more than maximum depth or premium quality.
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