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LLM ComparisonGPT-5.3 CodexClaude 3 Opus

GPT-5.3 Codex vs Claude 3 Opus

Compare GPT-5.3 Codex and Claude 3 Opus. Build AI products powered by either model on Appaca.

Model Comparison

FeatureGPT-5.3 CodexClaude 3 Opus
ProviderOpenAIAnthropic
Model Typetexttext
Context Window400,000 tokens200,000 tokens
Input Cost
$1.75/ 1M tokens
$15.00/ 1M tokens
Output Cost
$14.00/ 1M tokens
$75.00/ 1M tokens

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Strengths & Best Use Cases

GPT-5.3 Codex

OpenAI

1. Strongest Codex Model for Agentic Engineering

  • OpenAI positions GPT-5.3 Codex as its most capable agentic coding model to date.
  • Built for long-horizon software engineering tasks that require planning, iteration, and reliable code transformation across files.

2. Configurable Reasoning + Multimodal Input

  • Supports configurable reasoning effort from low to xhigh so teams can trade off depth against latency.
  • Accepts both text and image inputs while producing text output.

3. Large Context for Real Codebases

  • 400 k token context window helps it work across larger repositories, implementation plans, and supporting documentation.
  • Allows up to 128 k output tokens for longer code generations, patches, and technical write-ups.

4. Current Knowledge for Modern Dev Workflows

  • Knowledge cut-off of Aug 31 2025 keeps it aligned with newer frameworks, libraries, and tooling.
  • Supports streaming, function calling, and structured outputs for agent-style coding workflows.

Claude 3 Opus

Anthropic

1. Intelligence & Reasoning

  • Highest capability in the Claude 3 family
  • Near-human comprehension and fluency
  • Excels at MMLU, GPQA, GSM8K, advanced reasoning tasks

2. Complex Problem Solving

  • Best for research, strategy, multi-step planning
  • Handles ambiguous, open-ended tasks with ease

3. Vision & Multimodal Capabilities

  • Strong chart/graph understanding
  • Processes documents, technical diagrams, and dense visual data

4. Recall & Long-Context Reasoning

  • Near-perfect recall (>99% on NIAH benchmark)
  • Handles very large documents and multi-file workflows

5. Enterprise-Grade Accuracy

  • Significantly reduced hallucinations
  • High correctness rate for factual queries

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