---
title: "Claude Haiku 4.5 for OpenClaw: Pricing, Setup, and What It's Good At"
description: "Everything you need to know about using Claude Haiku 4.5 with OpenClaw. Costs $1.00/M input, $5.00/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-anthropic-hero.jpg
keywords: "claude haiku 4.5 openclaw, claude haiku 4.5 pricing, claude haiku 4.5 review, anthropic openclaw, claude haiku 4.5 api"
category: model-guide
modelData:
  provider: "Anthropic"
  provider_slug: "anthropic"
  full_id: "anthropic/claude-haiku-4-5"
  input_cost_per_1m: 1
  output_cost_per_1m: 5
  max_input_tokens: 200000
  max_output_tokens: 64000
  features: ["function_calling", "vision", "reasoning"]
  parameter_count: null
  architecture: null
  license: null
faq:
  - question: "What are the exact costs for Haiku 4.5?"
    answer: "Input tokens cost $1 per million and output tokens cost $5 per million."
  - question: "What is the maximum output length?"
    answer: "The model can generate up to 64,000 tokens in a single response, which is significantly higher than many competitors."
  - question: "Does it support image inputs?"
    answer: "Yes, it has full vision capabilities for processing images and documents within the 200K context window."
---

Current as of March 2026. Haiku 4.5 is the model I use for the boring parts of an agent pipeline — log parsing, triage, routing, anything that runs at volume and doesn't need deep reasoning. Fast, cheap enough for high-frequency calls, and better at following tool schemas than most models at this price.

## Specs

| | |
|---|---|
| **Provider** | Anthropic |
| **Input cost** | $1.00 / M tokens |
| **Output cost** | $5.00 / M tokens |
| **Context window** | 200K tokens |
| **Max output** | 64K tokens |
| **Parameters** | N/A |
| **Features** | function_calling, vision, reasoning |

## What it's good at

#### Context Window

200K tokens means you can drop entire repositories or large log files into a single prompt. No RAG pipeline needed for most tasks, which simplifies your architecture.

#### Tool Calling Reliability

For a budget model, it follows function schemas better than expected. Arguments match the schema, JSON blocks close cleanly — that's the baseline you need for any agent tool to work.

#### Vision Integration

It processes UI screenshots and diagrams without needing Sonnet-tier pricing. Useful for automated testing pipelines or document analysis where you're running hundreds of images through.

## Where it falls short

#### Price vs. Alternatives

$1/M input is reasonable, but GPT-4o-mini is $0.15/M for similar use cases. If you're purely cost-driven and Anthropic's instruction following isn't a requirement, that gap is hard to ignore.

#### Deep Logic Gaps

Multi-step architectural reasoning is where it falls apart. Give it a complex feature to implement from scratch and it'll miss edge cases, produce incorrect assumptions, or just lose the thread partway through.

## Best use cases with OpenClaw

- **High-Volume Log Parsing** — 200K context and low latency for scanning large log files to find specific patterns. This is its sweet spot.
- **Initial PR Triage** — Boilerplate code review, syntax checks, labeling issues. Fast enough to run on every commit without breaking your budget.

## Not ideal for

- **Greenfield Feature Development** — It misses subtle edge cases in complex business logic. You'll spend more time fixing bugs than you saved in API costs.
- **Extreme Budget Constraints** — If cost is the top priority above all else, GPT-4o-mini and Gemini 1.5 Flash undercut Haiku on price with comparable output quality for simple tasks.

## 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 your API key and you're done.

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

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

## How it compares

- **vs GPT-4o-mini** — GPT-4o-mini is about 6x cheaper on input and has a 128K context window. For simple tasks, it often works fine. Haiku 4.5 wins on instruction following — worth it if your agent is prone to breaking on schema violations.
- **vs Gemini 1.5 Flash** — Gemini offers a 1M context window and lower pricing. I find Haiku more concise and consistent on system prompt adherence, but Gemini is competitive if the giant context window matters to your use case.

## Bottom line

The right pick for high-volume, lower-complexity tasks where you want Anthropic's tool-calling reliability without Sonnet pricing. If your primary goal is raw cost minimization and the task is simple, look at GPT-4o-mini first.

<a href="https://app.haimaker.ai/sign-up?utm_source=model_guide&utm_medium=cta&utm_campaign=claude-haiku-4-5-openclaw" class="cta-button">TRY CLAUDE HAIKU 4.5 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).*