---
title: "GPT 5 Nano for OpenClaw: Pricing, Setup, and What It's Good At"
description: "Everything you need to know about using GPT 5 Nano with OpenClaw. Costs $0.05/M input, $0.40/M output. 272K 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 5 nano openclaw, gpt 5 nano pricing, gpt 5 nano review, openai openclaw, gpt 5 nano api"
category: model-guide
modelData:
  provider: "OpenAI"
  provider_slug: "openai"
  full_id: "openai/gpt-5-nano"
  input_cost_per_1m: 0.05
  output_cost_per_1m: 0.4
  max_input_tokens: 272000
  max_output_tokens: 128000
  features: ["function_calling", "vision", "reasoning"]
  parameter_count: null
  architecture: null
  license: null
faq:
  - question: "What is the exact cost per million tokens?"
    answer: "Input tokens cost $0.05 per million and output tokens cost $0.4 per million."
  - question: "How much text can I fit in one request?"
    answer: "The model supports a context window of 272K tokens, with a maximum output of 128K tokens."
  - question: "Does it support vision tasks?"
    answer: "Yes, it includes vision capabilities for processing image inputs alongside text."
---

Current as of March 2026. GPT-5 Nano is OpenAI's cheapest option right now — $0.05/M input with a 272K context window and 128K output. The specs look almost too good for the price, and in some ways they are, but for specific tasks it genuinely earns its place.

## Specs

| | |
|---|---|
| **Provider** | OpenAI |
| **Input cost** | $0.05 / M tokens |
| **Output cost** | $0.40 / M tokens |
| **Context window** | 272K tokens |
| **Max output** | 128K tokens |
| **Parameters** | N/A |
| **Features** | function_calling, vision, reasoning |

## What it's good at

#### Price

$0.05/M input is cheap enough to throw at problems you'd normally skip due to cost. High-volume batch jobs, log scanning, bulk tagging — the economics work out at this tier.

#### Output Buffer

128K max output at this price is legitimately unusual. Long-form generation tasks that require expensive models elsewhere can sometimes run here instead.

#### Basic Function Calling

Handles structured tool calls well enough for straightforward API integrations without the overhead of heavier models.

## Where it falls short

#### Reasoning Quality

The reasoning feature is scaled down significantly. Multi-step logical deduction — the kind the o-series handles well — falls apart here. Don't expect GPT-5-level thinking.

#### Rate Limiting

OpenAI often throttles Nano tier more aggressively than larger models. During heavy agent bursts, 429 errors are a real operational concern worth planning for.

## Best use cases with OpenClaw

- **Document Routing** — Scan large amounts of text cheaply to decide which specialized agent handles a task. The 272K window means you can fit substantial inputs.
- **Simple Function Calling** — Works reliably for basic API integrations where the schema is predictable and the logic isn't complex.

## Not ideal for

- **Cross-File Code Analysis** — It loses the thread on complex inter-dependency tracking across large codebases.
- **Mathematical Reasoning** — The model hallucinates logic steps on anything beyond straightforward arithmetic. Don't trust it with proofs.

## 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

Export OPENAI_API_KEY and pass `openai/gpt-5-nano` as the model ID.

```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 faster for short prompts; Nano wins on context depth and input cost.
- **vs Gemini 1.5 Flash** — Flash has a 1M context window (larger than Nano), but Nano integrates more cleanly with OpenClaw's tool-calling logic.

## Bottom line

GPT-5 Nano is the right call for high-volume, low-complexity tasks where you'd otherwise overpay. Just stay realistic about what the reasoning feature can actually do.

<a href="https://app.haimaker.ai/sign-up?utm_source=model_guide&utm_medium=cta&utm_campaign=gpt-5-nano-openclaw" class="cta-button">TRY GPT 5 NANO 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).*