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LLM ComparisonGPT-5 CodexClaude 3.5 Haiku

GPT-5 Codex vs Claude 3.5 Haiku

Compare GPT-5 Codex and Claude 3.5 Haiku. Build AI products powered by either model on Appaca.

Model Comparison

FeatureGPT-5 CodexClaude 3.5 Haiku
ProviderOpenAIAnthropic
Model Typetexttext
Context Window400,000 tokens200,000 tokens
Input Cost
$1.25/ 1M tokens
$0.80/ 1M tokens
Output Cost
$10.00/ 1M tokens
$4.00/ 1M tokens

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Strengths & Best Use Cases

GPT-5 Codex

OpenAI

1. Purpose-Built for Agentic Coding

  • Optimized specifically for scenarios where the model must act as an autonomous or semi-autonomous coding agent.
  • Tailored for Codex workflows such as planning, editing, debugging, and multi-step tool-driven code tasks.

2. Advanced Coding Reasoning

  • Extends GPT-5's higher reasoning mode to better handle complex software logic and multi-file dependencies.
  • Produces more accurate, structured, and maintainable code across modern programming languages.

3. Strong Tool Use in Developer-Like Environments

  • Designed for Codex's agent environment, enabling the model to:
    • Read and modify files
    • Follow function signatures and API contracts
    • Navigate codebases with awareness of context and structure

4. Large Context Window for Full-Project Understanding

  • 400,000-token context allows ingestion of:
    • Entire repositories
    • Multiple files at once
    • Architectural descriptions
  • Enables long-range reasoning across codebases rather than isolated snippets.

5. Multimodal Capability for Development Tasks

  • Accepts text and image as input (great for screenshots of error logs, UI mocks, whiteboards).
  • Outputs text only, focusing its output precision on code, reasoning, and documentation.

6. Continuous Snapshot Updates

  • The underlying model version is regularly upgraded behind the scenes.
  • Ensures developers always use the best coding-enhanced GPT-5 variant without changing model names.

7. Reliable Instruction Following

  • Very strong adherence to constraints like:
    • File/folder structure requirements
    • Framework conventions
    • Naming patterns
    • Linting rules
  • Makes it suitable for production coding agents.

8. Broad API Integration

  • Available only in the Responses API, giving you:
    • Streaming
    • Structured outputs
    • Function calling
  • Allows creation of interactive coding tools and agent workflows with tight model control.

Claude 3.5 Haiku

Anthropic

1. Intelligence & Benchmark Performance

  • Matches Claude 3 Opus (previous largest model) on many intelligence tasks.
  • Surpasses Claude 3 Opus on multiple evaluations despite being a smaller, faster model.
  • Major improvements across every skill category vs previous Haiku.

2. Coding Strength

  • Scores 40.6% on SWE-bench Verified, outperforming:

    • Claude 3.5 Sonnet (original version)
    • GPT-4o
    • Many agent-driven systems
  • Excellent for engineering assistants, agent coding tasks, and bug fixing.

3. Speed & Latency

  • Same speed class as Claude 3 Haiku (ultra-fast).
  • Ideal for real-time interactions, high request volumes, and UI responsiveness.

4. Tool Use & Instruction Following

  • Better at following instructions than previous Haiku.
  • Stronger at tool use accuracy, making it reliable for agents and workflows.

5. Best Use Cases

  • High-volume, low-latency tasks
  • User-facing products
  • Sub-agent tasks in larger workflows
  • Processing large structured datasets (pricing, inventory, purchase history)
  • Rapid content or code generation where speed matters