---
title: "GPT 4.1 Mini for OpenClaw: Pricing, Setup, and What It's Good At"
description: "Everything you need to know about using GPT 4.1 Mini with OpenClaw. Costs $0.40/M input, $1.60/M output. 1.0M 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 4.1 mini openclaw, gpt 4.1 mini pricing, gpt 4.1 mini review, openai openclaw, gpt 4.1 mini api"
category: model-guide
modelData:
  provider: "OpenAI"
  provider_slug: "openai"
  full_id: "openai/gpt-4.1-mini"
  input_cost_per_1m: 0.4
  output_cost_per_1m: 1.6
  max_input_tokens: 1047576
  max_output_tokens: 32768
  features: ["function_calling", "vision"]
  parameter_count: null
  architecture: null
  license: null
faq:
  - question: "What is the token limit?"
    answer: "The model supports a 1.0M token context window and a maximum output of 33K tokens per request."
  - question: "How much does it cost?"
    answer: "Inputs are priced at $0.4 per million tokens and outputs at $1.6 per million tokens."
---

Current as of March 2026. GPT-4.1 Mini takes the 1M context window from its full-size sibling and drops the price to $0.40/M input. That's a significant reduction. The trade-offs are real but manageable for the right use cases.

## Specs

| | |
|---|---|
| **Provider** | OpenAI |
| **Input cost** | $0.40 / M tokens |
| **Output cost** | $1.60 / M tokens |
| **Context window** | 1.0M tokens |
| **Max output** | 33K tokens |
| **Parameters** | N/A |
| **Features** | function_calling, vision |

## What it's good at

#### Context Window

Same 1M token window as GPT-4.1 at a fifth of the input cost. For use cases where you're mostly feeding in large documents and want simple answers back, this is the economical path.

#### Tool Use

Function calling is solid. OpenAI's schema consistency transfers down to the mini tier reasonably well.

#### Vision at a Reasonable Price

Vision support at $1.60/M output is much easier to justify than $8/M. Good for UI automation agents or document processing pipelines with image content.

## Where it falls short

#### Reasoning

Multi-step logic is the weak point. Complex, layered prompts that require the model to track multiple constraints can fail in non-obvious ways.

#### Latency at Max Output

When you push against the 33K output limit, latency gets inconsistent. Not a dealbreaker for async workloads, but it's noticeable.

## Best use cases with OpenClaw

- **Large Document Analysis** — Multiple PDFs or legal documents in a single context is where the 1M window earns its keep.
- **Vision-based Automation** — Screen-reading and UI interaction agents where you need vision support but can't afford GPT-4.1's output pricing.

## Not ideal for

- **Complex Refactoring** — Deep cross-file logic analysis needs more reasoning capacity than this model has.
- **Sub-second Chat** — If you need instant responses for a conversational UI, something smaller and faster fits better.

## 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 the framework handles the rest.

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

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

## How it compares

- **vs Claude 3 Haiku** — Haiku is cheaper and faster for short prompts; 4.1 Mini's 1M context window dwarfs Haiku's 200K limit for document-heavy work.
- **vs Gemini 1.5 Flash** — Flash matches the context window, but OpenAI's function calling is more consistent and easier to debug within OpenClaw.

## Bottom line

GPT-4.1 Mini is the practical choice for high-context agents that need vision and reliable tool calling without the full GPT-4.1 price tag.

<a href="https://app.haimaker.ai/sign-up?utm_source=model_guide&utm_medium=cta&utm_campaign=gpt-4.1-mini-openclaw" class="cta-button">TRY GPT 4.1 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).*