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
GPT-5.3-Codexspecs & pricing
Verified Sep 4, 2026 against the AI Gateway catalog
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 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
How GPT-5.3-Codex compares
The nearest models people weigh against it, and what actually separates them.
vs GPT-4 Turbo — Against GPT-4 Turbo (OpenAI), GPT-5.3-Codex runs about 61% cheaper per token and takes 3.1x the context. Take GPT-5.3-Codex unless you specifically need what GPT-4 Turbo does better.
vs GPT-4 Turbo (older v1106) — Against GPT-4 Turbo (older v1106) (OpenAI), GPT-5.3-Codex runs about 61% cheaper per token and takes 3.1x the context. Take GPT-5.3-Codex unless you specifically need what GPT-4 Turbo (older v1106) does better.
vs GPT-4 Turbo Preview — Against GPT-4 Turbo Preview (OpenAI), GPT-5.3-Codex runs about 61% cheaper per token and takes 3.1x the context. Take GPT-5.3-Codex unless you specifically need what GPT-4 Turbo Preview does better.
Price History
GPT-5.3-Codex pricing over time
→0% since May 30
90 data points · tracked daily since May 30, 2026
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Start using GPT-5.3-Codex
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.
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.
Verdict
A capable but aging flagship that has been outpaced by cheaper, faster successors in OpenAI's own lineup.
Quality score
75%
Pricing
$10.00/1M in
$30.00/1M out
Speed
Balanced
3/5 speed
Context
128k tokens
GPT-4 Turbo is available via the OpenAI API. It has largely been succeeded by GPT-4o, which is faster, supports vision natively, and is cheaper. Organizations should evaluate whether migrating to GPT-4o or o3 makes more sense before building new workflows on this model.
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.
Verdict
A reliable but outdated GPT-4 snapshot that only makes sense when version pinning is a hard requirement.
Quality score
66%
Pricing
$10.00/1M in
$30.00/1M out
Speed
Balanced
3/5 speed
Context
128k tokens
This is a pinned model snapshot (v1106) and will not receive capability updates. OpenAI may deprecate older snapshots over time. Knowledge cutoff is April 2023. Not recommended for new deployments given the superior cost-performance of GPT-4o and GPT-4.1.
Legacy128K ContextPinned SnapshotGPT-4Premium
Best for
Teams requiring a pinned, stable version of GPT-4 Turbo for reproducible outputs in long-document analysis or complex instruction pipelines.
GPT-4 Turbo Preview is an early access version of GPT-4 Turbo, OpenAI's then-flagship model featuring a 128K context window and knowledge improvements over the original GPT-4. It was designed to deliver GPT-4-class reasoning at reduced cost compared to the original GPT-4.
Verdict
A once-capable flagship now overshadowed by faster, cheaper, and smarter successors.
Quality score
67%
Pricing
$10.00/1M in
$30.00/1M out
Speed
Balanced
3/5 speed
Context
128k tokens
This is a 'preview' variant that OpenAI has largely deprecated in favor of gpt-4-turbo and gpt-4o. The endpoint may be retired or redirected by OpenAI without notice. Check the OpenAI model deprecation schedule before building production applications on this model.
GPT-4Long ContextLegacyPremiumOpenAI
Best for
Complex multi-step reasoning, long-document analysis, and professional writing tasks requiring strong instruction-following.
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.
GPT-5.3-Codex costs $1.75 per million input tokens and $14 per million output tokens on the API, with cached input at $0.175 per million. A month of 10M input and 2M output tokens runs about $45.50 at list price, before any batch or caching discounts.
What is the context window of GPT-5.3-Codex?
GPT-5.3-Codex has a 400k tokens context window, with up to 128k tokens of output per response. That is the total of prompt plus response the model can hold in one request.
What is the knowledge cutoff of GPT-5.3-Codex?
GPT-5.3-Codex's training data runs through August 31, 2025, and the model was released on February 5, 2026. For anything after that date it needs web search or documents in the prompt.
What is GPT-5.3-Codex best for?
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 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 GPT-5.3-Codex?
GPT-5.1-Codex-Max (OpenAI) at $1.25/1M/1M input against GPT-5.3-Codex's $1.75/1M/1M — roughly 29% less per token all in. The strongest choice for serious software engineering work, provided you can absorb the output-side pricing. Compare it first if GPT-5.3-Codex's pricing is the thing stopping you.
What is a faster alternative to GPT-5.3-Codex?
GPT-4 Turbo — balanced against GPT-5.3-Codex's balanced, with 128k tokens of context. Worth the swap when response time is what your users notice rather than the last few points of reasoning depth.
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