LLM ComparisonGPT-5.2 CodexGPT-4 Turbo

GPT-5.2 Codex vs GPT-4 Turbo

Compare GPT-5.2 Codex and GPT-4 Turbo. Build AI products powered by either model on Appaca.

Model Comparison

FeatureGPT-5.2 CodexGPT-4 Turbo
ProviderOpenAIOpenAI
Model Typetexttext
Context Window400,000 tokens128,000 tokens
Input Cost
$1.75/ 1M tokens
$10.00/ 1M tokens
Output Cost
$14.00/ 1M tokens
$30.00/ 1M tokens

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Strengths & Best Use Cases

GPT-5.2 Codex

OpenAI

1. Optimized for Long-Horizon Coding Tasks

  • OpenAI describes GPT-5.2 Codex as a highly intelligent coding model built for long-horizon, agentic coding work.
  • Well suited to planning, refactoring, debugging, and multi-step implementation flows inside real codebases.

2. Adjustable Reasoning for Coding Work

  • Supports configurable reasoning effort from low to xhigh depending on speed and quality needs.
  • Accepts both text and image inputs while producing text output.

3. Large Context + Long Output

  • 400 k token context window supports broad repository understanding and larger working sets.
  • Allows up to 128 k output tokens for longer patches, code generation, and technical explanations.

4. Up-to-Date Model Snapshot

  • Knowledge cut-off of Aug 31 2025 keeps it current with newer tools and frameworks.
  • Supports streaming, function calling, and structured outputs for tool-driven coding workflows.

GPT-4 Turbo

OpenAI

1. Strong reasoning for its generation

  • Next-gen version of GPT-4 designed to be cheaper and faster than the original.
  • Good for analytical tasks, structured writing, coding guidance, and multi-step reasoning.

2. Image input support

  • Accepts images and provides text-only outputs.
  • Useful for OCR, visual Q&A, document extraction, UI analysis, and design interpretation.

3. Stable performance

  • Predictable model behavior suitable for legacy systems still built on GPT-4.
  • Works reliably for established pipelines and enterprise workloads.

4. Large 128K context window

  • Handles long documents, multi-file inputs, or extended conversational sessions.
  • Allows complex prompt chaining and large instruction sets.

5. Broad endpoint compatibility

  • Works with Chat Completions, Responses API, Realtime API, Assistants, Batch, Fine-tuning, Embeddings, and more.
  • Supports streaming and function calling.

6. Good choice for cost-controlled GPT-4-class workloads

  • Although older, still useful for teams who want GPT-4-level reasoning without upgrading immediately.
  • A midpoint between legacy GPT-4 and modern GPT-4o/5.1 models.

7. Text-only output simplifies downstream use

  • Ensures deterministic outputs for applications that need reliable text generation.
  • Good for RAG, data pipelines, automation tools, and enterprise systems.

8. Recommended migration path

  • OpenAI now recommends using GPT-4o or GPT-5.1 for improved speed, cost, reasoning, and multimodal capability.
  • GPT-4 Turbo remains available for backward compatibility and stability.

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