Current as of March 2026. O3 Mini is the cheaper entry into OpenAI’s reasoning lineup — $1.10/M input vs O3’s $2.00/M — while keeping the 200K context and 100K output. The tradeoff is reasoning depth. It’s good enough for most complex tasks, and the price difference matters at scale.
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, reasoning |
What it’s good at
Function Calling With Reasoning
A lot of reasoning models fall down on structured outputs. O3 Mini doesn’t — it follows tool schemas reliably within OpenClaw workflows, which is the main thing you care about for agentic use.
Reasoning at a Lower Price
Chain-of-thought reasoning here outperforms standard models like GPT-4o on complex logic, while coming in at roughly half the input cost of full O3.
Where it falls short
Latency
The thinking phase adds several seconds before the first token. That’s acceptable for batch agent steps, not for interfaces where users are waiting.
Output-to-Input Price Ratio
$4.40/M output vs $1.10/M input is a 4:1 ratio. Long reasoning chains with verbose responses can inflate costs faster than expected.
Best use cases with OpenClaw
- Complex Debugging — Tracing logic errors across multiple files is where reasoning models earn their latency cost. O3 Mini handles this better than non-reasoning alternatives.
- Agentic Planning — Breaking a vague user goal into a specific, ordered sequence of tool calls. The chain-of-thought reduces planning errors meaningfully.
Not ideal for
- Simple Classification or Extraction — You’re paying for reasoning you don’t need. GPT-4o-mini is an order of magnitude cheaper for this.
- Streaming Chat UIs — The thinking delay makes the interface feel unresponsive. Users notice.
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 picks the best model for each task so you don’t have to.
OpenClaw setup
Set OPENAI_API_KEY and OpenClaw manages the reasoning tokens automatically.
export OPENAI_API_KEY="your-key-here"
That’s it. OpenClaw picks up OpenAI models automatically.
How it compares
- vs DeepSeek-R1 — R1 is cheaper, but O3 Mini’s function calling and structured output support is more reliable for OpenClaw workflows.
- vs GPT-4o-mini — GPT-4o-mini is faster and cheaper ($0.15/$0.60) but lacks reasoning. Use O3 Mini when logic depth actually matters.
Bottom line
O3 Mini is the practical reasoning choice for OpenClaw — it thinks through problems and still follows tool-calling schemas, without the full O3 price tag.
For setup instructions, see our API key guide. For all available models, see the complete models guide.