---
title: "GPT-5 Codex for OpenClaw: Pricing, Setup, and What It's Good At"
description: "Everything you need to know about using GPT-5 Codex with OpenClaw. Costs $1.25/M input, $10/M output. 400K context window. Here's when to use it and when to pick something else."
date: 2026-03-12
updatedDate: 2026-03-12
image: /images/models/provider-openai-hero.jpg
keywords: "gpt-5 codex openclaw, gpt-5 codex pricing, gpt-5 codex review, openai openclaw, gpt-5 codex api"
category: model-guide
modelData:
  provider: "OpenAI"
  provider_slug: "openai"
  full_id: "openai/gpt-5-codex"
  input_cost_per_1m: 1.25
  output_cost_per_1m: 10
  max_input_tokens: 400000
  max_output_tokens: 128000
  features: ["function_calling", "vision", "reasoning"]
  parameter_count: null
  architecture: null
  license: null
faq:
  - question: "What are the exact token costs?"
    answer: "Input costs $1.25 per million tokens and output costs $10 per million tokens."
  - question: "How much data can I feed it?"
    answer: "The model supports a 400K token context window, which is roughly 300,000 words of code or text."
  - question: "Can it see images?"
    answer: "Yes, it has native vision support for analyzing UI mockups, diagrams, or screenshots during the development process."
---

Current as of March 2026. GPT-5 Codex is OpenAI's specialized reasoning model designed for high-token coding tasks and complex agentic workflows. It bridges the gap between massive context ingestion and long-form code generation within the OpenClaw framework.

## Specs

| | |
|---|---|
| **Provider** | OpenAI |
| **Input cost** | $1.25 / M tokens |
| **Output cost** | $10 / M tokens |
| **Context window** | 400K tokens |
| **Max output** | 128K tokens |
| **Parameters** | N/A |
| **Features** | function_calling, vision, reasoning |

## What it's good at

#### Massive Output Buffer

The 128K max output limit allows for generating entire project modules or comprehensive test suites in a single pass without truncation.

#### Reliable Function Calling

The reasoning engine handles complex, nested tool definitions in OpenClaw with high precision, reducing the need for retry logic.

#### Context Depth

A 400K context window enables the model to ingest large portions of a codebase or documentation while maintaining focus on the specific task.

## Where it falls short

#### Expensive Output

At $10 per million tokens, output is eight times more expensive than input, making large-scale generation runs costly.

#### Inference Latency

The reasoning overhead results in a slower time-to-first-token compared to GPT-4o, which can feel sluggish in interactive loops.

## Best use cases with OpenClaw

- **Automated Refactoring** — The combination of 400K input and 128K output is ideal for analyzing legacy files and outputting modernized versions.
- **Multi-Step Agent Logic** — Its reasoning capabilities allow OpenClaw agents to plan and execute long sequences of tool calls without losing the original objective.

## Not ideal for

- **Simple Chat Interfaces** — The pricing and latency make it overkill for basic Q&A or simple text editing tasks.
- **Real-time Autocomplete** — The model is tuned for depth rather than speed, making it too slow for low-latency coding assistance.

## OpenClaw setup

OpenClaw treats this as a first-class provider. Export your OPENAI_API_KEY to your environment and the framework handles the rest without custom configuration files.

```bash
export OPENAI_API_KEY="your-key-here"
```

That's it. OpenClaw picks up OpenAI models automatically.

## How it compares

- **vs [Claude 3.5 Sonnet](/blog/claude-3-5-sonnet-openclaw)** — Sonnet is faster and cheaper for general coding, but lacks the 128K output ceiling and the 400K context of GPT-5 Codex.
- **vs Gemini 1.5 Pro** — Gemini offers a larger 2M context window, but Codex typically demonstrates more reliable function calling for complex tool chains.

## Bottom line

GPT-5 Codex is a premium tool for developers who prioritize reasoning depth and massive output capacity over speed and low cost.

<a href="https://app.haimaker.ai/sign-up?utm_source=model_guide&utm_medium=cta&utm_campaign=gpt-5-codex-openclaw" class="cta-button">TRY GPT-5 CODEX ON HAIMAKER</a>

---

*For setup instructions, see our [API key guide](/blog/openclaw-api-key-setup). For all available models, see the [complete models guide](/blog/best-models-for-openclaw).*