---
title: "O4 Mini for OpenClaw: Pricing, Setup, and What It's Good At"
description: "Everything you need to know about using O4 Mini with OpenClaw. Costs $1.10/M input, $4.40/M output. 200K 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: "o4 mini openclaw, o4 mini pricing, o4 mini review, openai openclaw, o4 mini api"
category: model-guide
modelData:
  provider: "OpenAI"
  provider_slug: "openai"
  full_id: "openai/o4-mini"
  input_cost_per_1m: 1.1
  output_cost_per_1m: 4.4
  max_input_tokens: 200000
  max_output_tokens: 100000
  features: ["function_calling", "vision", "reasoning"]
  parameter_count: null
  architecture: null
  license: null
faq:
  - question: "What is the token limit for O4 Mini?"
    answer: "It features a 200K token context window and can generate up to 100K tokens in a single output."
  - question: "How much does it cost to run?"
    answer: "Input tokens are priced at $1.1 per million, and output tokens cost $4.4 per million."
---

Current as of March 2026. O4 Mini has the same pricing as O3 Mini but adds vision — $1.10/M input, $4.40/M output, 200K context, 100K output. For agents that need to both reason and see, this is currently the most capable option in that price tier.

## Specs

| | |
|---|---|
| **Provider** | OpenAI |
| **Input cost** | $1.10 / M tokens |
| **Output cost** | $4.40 / M tokens |
| **Context window** | 200K tokens |
| **Max output** | 100K tokens |
| **Parameters** | N/A |
| **Features** | function_calling, vision, reasoning |

## What it's good at

#### Reasoning Plus Vision

Most reasoning models drop vision support. O4 Mini keeps it, which opens up workflows where the agent needs to look at a UI, diagram, or chart and then reason about what to do next.

#### Output Ceiling

100K max output combined with reasoning capability is genuinely useful for tasks like rewriting large files or generating comprehensive technical specs while keeping logical consistency.

#### Multi-step Planning

Chain-of-thought reasoning reduces planning errors in OpenClaw loops. The agent thinks through tool dependencies before executing, which means fewer mid-workflow failures.

## Where it falls short

#### Latency

The reasoning chain adds noticeable delay before first token. 7x the input cost of GPT-4o-mini combined with slower responses means you should be clear on why you need it before using it.

#### Cost for Simple Tasks

At $1.10/M input, it's expensive for anything that doesn't need reasoning. Extracting JSON from a predictable string, basic classification, high-volume routing — none of that benefits from chain-of-thought.

## Best use cases with OpenClaw

- **Agentic Planning** — Works through tool dependencies before executing, which reduces loop errors on complex multi-step workflows.
- **Complex Refactoring** — The reasoning plus 100K output limit means it can rewrite large files while tracking logical consistency across the code.

## Not ideal for

- **Simple Extraction** — Paying the reasoning premium for basic field extraction is wasteful. GPT-4o-mini handles that at $0.15/M.
- **Real-time Chat** — Time-to-first-token is too high for interactive UIs. Users will notice the thinking pause.

## Run it through Haimaker

Skip juggling API keys. One Haimaker key gives you access to every model on the platform. Tell OpenClaw:

```
Add Haimaker as a custom provider to my OpenClaw config. Use these details:

- Provider name: haimaker
- Base URL: https://api.haimaker.ai/v1
- API key: [PASTE YOUR HAIMAKER API KEY HERE]
- API type: openai-completions

Add the auto-router model:
- haimaker/auto (reasoning: false, context: 128000, max tokens: 32000)

Create an alias "auto" for easy switching. Apply the config when done.
```

Or skip model selection entirely — Haimaker's [auto-router](/blog/openclaw-auto-router-setup/) picks the best model for each task so you don't have to.

## OpenClaw setup

Set OPENAI_API_KEY and point to `openai/o4-mini`.

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

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

## How it compares

- **vs Claude 3.5 Haiku** — Haiku is faster and cheaper for straightforward tasks; O4 Mini wins on reasoning depth and context size.
- **vs GPT-4o-mini** — GPT-4o-mini is the right call for high-volume work without reasoning requirements. O4 Mini is for when logic depth actually matters.

## Bottom line

O4 Mini is the best option when your OpenClaw agent needs to reason through a problem and look at images — that specific combination isn't widely available at this price point.

<a href="https://app.haimaker.ai/sign-up?utm_source=model_guide&utm_medium=cta&utm_campaign=o4-mini-openclaw" class="cta-button">TRY O4 MINI 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).*