---
title: "GPT-5.2-Codex for Hermes Agent: Pricing, Setup, and What It's Good At"
description: "Everything you need to know about using GPT-5.2-Codex with Hermes Agent. Costs $1.75/M input, $14/M output. 400K context window. Here's when to use it and when to pick something else."
date: 2026-04-17
updatedDate: 2026-09-08
image: /images/models/provider-openai-hero.jpg
keywords: "gpt-5.2-codex hermes, gpt-5.2-codex pricing, gpt-5.2-codex review, openai hermes, gpt-5.2-codex api"
category: model-guide
modelData:
  provider: "OpenAI"
  provider_slug: "openai"
  full_id: "openai/gpt-5.2-codex"
  input_cost_per_1m: 1.75
  output_cost_per_1m: 14
  max_input_tokens: 400000
  max_output_tokens: 128000
  features: ["function_calling", "vision", "reasoning", "web_search"]
  parameter_count: null
  architecture: null
  license: null
faq:
  - question: "What is the exact pricing for GPT-5.2-Codex?"
    answer: "Input tokens cost $1.75 per million and output tokens cost $14 per million."
  - question: "How much data can it remember in a single session?"
    answer: "It features a 400K token context window, allowing it to process approximately 300,000 words of history."
  - question: "Does it support vision for multi-platform tasks?"
    answer: "Yes, it has native vision capabilities, enabling Hermes to analyze screenshots or images sent via platforms like WhatsApp or Slack."
---

Current as of April 2026. GPT-5.2-Codex is OpenAI's top-tier reasoning model designed for complex tool orchestration and massive context retention. It is the gold standard for Hermes Agent users who need reliable autonomous behavior across high-stakes multi-platform workflows.

## Specs

| | |
|---|---|
| **Provider** | OpenAI |
| **Input cost** | $1.75 / M tokens |
| **Output cost** | $14 / M tokens |
| **Context window** | 400K tokens |
| **Max output** | 128K tokens |
| **Parameters** | N/A |
| **Features** | function_calling, vision, reasoning, web_search |

## What it's good at

#### Massive Context Retention

The 400K context window allows Hermes to maintain a massive persistent memory, keeping track of conversations across 15+ platforms without losing historical context.

#### Superior Tool Reliability

It handles the 47 built-in Hermes tools and complex MCP protocols with surgical precision, rarely hallucinating function arguments even in deep reasoning loops.

#### Advanced Multi-Platform Reasoning

The model excels at synthesizing information from disparate sources, like monitoring a Slack channel and executing shell commands based on specific triggers.

## Where it falls short

#### Prohibitive Output Costs

At $14 per million output tokens, running this model for high-frequency messaging tasks on Telegram or Discord will get expensive very quickly.

#### Reasoning Latency

The deep reasoning features can introduce a 5-10 second delay before the agent takes action, which might feel slow for real-time chat interactions.

## Best use cases with Hermes Agent

- **Cross-Platform Enterprise Automation** — It can accurately monitor Slack, query internal databases via MCP, and generate complex reports for Discord without human intervention.
- **Persistent Identity Management** — The 400K context window and closed learning loop enable the agent to maintain a consistent persona and memory over months of operation.

## Not ideal for

- **Simple Notification Bots** — Using a reasoning-heavy model for simple message relaying is a waste of money given the $1.75/$14 token pricing.
- **High-Volume Chat Apps** — The latency and cost make it impractical for a WhatsApp bot handling thousands of simple user queries daily.

## Hermes Agent setup

Configure the OpenAI provider with your API key and set the model ID to openai/gpt-5.2-codex; ensure your account tier supports high-concurrency reasoning tokens.

Hermes makes custom endpoints easy. Run:

```bash
hermes model
```

Choose **Custom endpoint** from the menu. Enter the base URL and model identifier when prompted:

- **Base URL:** `https://api.haimaker.ai/v1`
- **Model:** `openai/gpt-5.2-codex`

Hermes stores the selection and uses it for all subsequent agent runs across whatever platforms you have wired up (Telegram, Discord, Slack, etc.). Tune `HERMES_STREAM_READ_TIMEOUT` and related env vars if you're hitting slow providers.

## How it compares

- **vs Claude 3.5 Sonnet** — Sonnet is faster and cheaper for basic tool use, but GPT-5.2-Codex's 400K context window crushes Sonnet's 200K limit for long-term memory.
- **vs GPT-4o** — GPT-4o is better for low-latency chat, but GPT-5.2-Codex is significantly more reliable when Hermes needs to sequence multiple MCP tool calls.

## Bottom line

This is the model you choose when your Hermes Agent needs to be a reliable autonomous employee rather than just a chat bot.

<a href="https://app.haimaker.ai/sign-up?utm_source=model_guide&utm_medium=cta&utm_campaign=hermes_gpt-5-2-codex" class="cta-button">TRY GPT-5.2-CODEX IN HERMES</a>

---

*For more, see our [Hermes local-LLM setup guide](https://hermes-agent.nousresearch.com/docs/guides/local-llm-on-mac).*