GPT-4 Turbo
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.
The go-to model for large-codebase engineering tasks, but expensive output costs limit its appeal for high-throughput pipelines.
Professional software engineers who need a high-capacity model for large codebase analysis, complex refactoring, and multi-file code generation.
You need fast, high-volume code completions on a tight budget or require multimodal capabilities like image understanding or generation.
Compare every model's knowledge cutoff, max output, and context window.
Asymmetric pricing ($1.25 input / $10 output) rewards read-heavy workflows like code review and repo analysis over generation-heavy tasks. The 400K context window is among the largest in the balanced price tier. No image input/output support confirmed at launch.
Exceptional multi-file and large codebase understanding across its 400K context window
Stronger code generation accuracy than GPT-4o, particularly in Python, TypeScript, and systems languages
Solid reasoning over complex software architecture and debugging chains
Competitive asymmetric pricing — cheap input cost makes ingesting large repos affordable
Output cost of $10/1M tokens is steep for high-volume code generation pipelines compared to Claude Sonnet 4.6 or Gemini 3.1 Pro
Not a general-purpose creative or writing model — prose quality lags behind Claude Sonnet 4.6
No native image generation or multimodal output capabilities
What people actually use GPT-5.1-Codex for.
Ingesting an entire Node.js monorepo and generating a refactoring plan with dependency impact analysis
Debugging a complex async race condition across 15+ interconnected files in a single prompt
Generating comprehensive unit test suites for legacy Python codebases with full context retention
The nearest models people weigh against it, and what actually separates them.
vs GPT-4 Turbo — Against GPT-4 Turbo (OpenAI), GPT-5.1-Codex runs about 72% cheaper per token and takes 3.1x the context. Take GPT-5.1-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-5.1-Codex runs about 72% cheaper per token and takes 3.1x the context. Take GPT-5.1-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-5.1-Codex runs about 72% cheaper per token and takes 3.1x the context. Take GPT-5.1-Codex unless you specifically need what GPT-4 Turbo Preview does better.
Price History
→0% since May 30
90 data points · tracked daily since May 30, 2026
Professional software engineers who need a high-capacity model for large codebase analysis, complex refactoring, and multi-file code generation.. 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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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.
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.
Pricing moves, ranking shifts, and capability updates.
OpenAI: GPT-5.1-Codex (OpenAI) is now indexed. It supersedes GPT-4o. The go-to model for large-codebase engineering tasks, but expensive output costs limit its appeal for high-throughput pipelines.
View modelGPT-5.1-Codex costs $1.25 per million input tokens and $10 per million output tokens on the API, with cached input at $0.13 per million. A month of 10M input and 2M output tokens runs about $32.50 at list price, before any batch or caching discounts.
GPT-5.1-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.
GPT-5.1-Codex's training data runs through September 30, 2024, and the model was released on November 12, 2025. For anything after that date it needs web search or documents in the prompt.
GPT-5.1-Codex is best for professional software engineers who need a high-capacity model for large codebase analysis, complex refactoring, and multi-file code generation.. It is a strong fit when that workflow matters more than the tradeoffs around balanced pricing and balanced speed.
You need fast, high-volume code completions on a tight budget or require multimodal capabilities like image understanding or generation.
GPT-5.1-Codex-Max (OpenAI) at $1.25/1M/1M input against GPT-5.1-Codex's $1.25/1M/1M. The strongest choice for serious software engineering work, provided you can absorb the output-side pricing. Compare it first if GPT-5.1-Codex's pricing is the thing stopping you.
GPT-4 Turbo — balanced against GPT-5.1-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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