---
title: "Free Models for OpenClaw: What Actually Costs Nothing (2026)"
description: "Run OpenClaw without an API bill. Local models via Ollama are truly free. Gemini Flash and GPT-4o-mini cost pennies. Here's how to set them up."
date: 2026-03-12
updatedDate: 2026-07-23
location: San Francisco, CA – Mar 12th, 2026
image: /images/best-free-models-for-openclaw-hero.jpg
keywords: "free openclaw models, openclaw free tier, free ai coding agent, openclaw ollama free, cheap llm models"
faq:
  - question: "Can I use OpenClaw for free?"
    answer: "Yes, with local models through Ollama. Install Ollama, pull a model like Qwen3.6 27B, and point OpenClaw at localhost:11434. Zero API costs. You can also use Gemini Flash's free tier (15 requests/minute) or a sub-dollar model like DeepSeek V4 Flash for pennies per million tokens."
  - question: "What's the best free model for OpenClaw coding tasks?"
    answer: "For local/free models, Qwen3.6 27B handles code generation and debugging well on hardware with 18GB+ VRAM — it scores 77.2% on SWE-bench Verified, rivaling paid cloud models. For cloud free tiers, Gemini Flash offers free usage at 15 RPM with a 1M+ token context window."
  - question: "How do I set up a free local model with OpenClaw?"
    answer: "Install Ollama (ollama.com), run 'ollama pull qwen3.6:27b', then add Ollama as a provider in ~/.openclaw/openclaw.json with baseUrl 'http://localhost:11434/v1'. Set the model as your primary in agents.defaults.model."
---

"Free" gets thrown around a lot in the AI model space. Let me be specific about what that actually means for OpenClaw users.

There are three categories: models that cost literally nothing (local), models with free tiers that eventually run out, and models so cheap they round to zero on most invoices. I'll cover all three.

## Actually free: local models

The only models that cost nothing per-token are the ones running on your own hardware. Ollama makes this straightforward.

Install it, pull a model, point OpenClaw at it:

```bash
# Install Ollama
curl -fsSL https://ollama.com/install.sh | sh

# Pull a coding model
ollama pull qwen3.6:27b
```

Then add Ollama as a provider in `~/.openclaw/openclaw.json`:

```json5
{
  models: {
    providers: {
      ollama: {
        baseUrl: "http://localhost:11434/v1",
        api: "openai-completions",
        models: [
          { id: "qwen3.6:27b", name: "Qwen3.6 27B" }
        ]
      }
    }
  },
  agents: {
    defaults: {
      model: { primary: "ollama/qwen3.6:27b" }
    }
  }
}
```

#### Which local models work well

**Qwen3.6 27B** is the current sweet spot — the community still calls it the "peak of the pyramid" for local coding. It scores 77.2% on SWE-bench Verified, handles code generation, debugging, and multi-file edits well for day-to-day work, and needs only ~18GB VRAM (an RTX 5090, or an M-series Mac with 32GB+ unified memory).

**Qwen3 Coder 30B** is the agent-tuned alternative — 256K context and reliable tool calling, which matters for OpenClaw's tool loop.

**gpt-oss 20B** and **Gemma 4** run on 16GB machines. gpt-oss 20B has become the default small pick since its release — it activates only ~3.6B parameters per token and lets you adjust reasoning effort. Quality still drops on complex tasks; I wouldn't trust either with multi-file refactors.

#### The honest tradeoff

Local models are free but not fast. Response times are 3-10x slower than cloud APIs, depending on your hardware. And even the best consumer-sized open models still trail frontier Claude models on the hardest debugging and multi-file work.

If your work involves mostly reading files, generating boilerplate, and simple edits, local works well. If you're doing complex debugging or architectural work, you'll want a cloud model for those tasks.

## Free tiers from cloud providers

A few providers offer genuinely free usage up to a limit.

**Gemini Flash** is the best free option for cloud inference. Google's free tier gives you 15 requests per minute with up to 1M token context. That's enough for casual coding sessions.

```json5
// Add to ~/.openclaw/openclaw.json
{
  models: {
    providers: {
      google: {
        models: [
          { id: "gemini-3-flash", name: "Gemini 3 Flash" }
        ]
      }
    }
  }
}
```

The catch: the free tier has stricter rate limits and your data may be used for training. For side projects and learning, that's probably fine. For proprietary code, use the paid API or run local.

## Almost free: sub-dollar models

Some models cost so little per token that a full day of heavy OpenClaw usage stays under $1.

| Model | Input cost | Output cost | Daily cost estimate |
|-------|-----------|-------------|-------------------|
| DeepSeek V4 Flash | ~$0.10/M | ~$0.28/M | ~$0.15 |
| GLM-4.7 Flash | $0.07/M | $0.28/M | ~$0.15 |
| GPT-4o-mini | $0.15/M | $0.60/M | ~$0.50 |
| MiniMax M3 | $0.30/M | — | ~$0.50 |

*Daily estimates based on ~500K input + 200K output tokens, which is a busy coding day.*

**MiniMax M3** deserves a special note: at $0.30/M input with a 1M-token context window it's the current value pick of the budget tier — running it around the clock for an agent costs roughly $7–15 a month. **DeepSeek V4 Flash** is the absolute floor: cheap enough that 24/7 agent use stays under $5 a month.

These models handle the boring parts of a coding session well: file reads, simple edits, documentation, test runs. Route the 20% of hard problems to a better model and your total bill stays under $5/day.

You can access all of these through [Haimaker](https://app.haimaker.ai/sign-up?utm_source=openclaw_blog&utm_medium=cta&utm_campaign=best-free-models) with a single API key, or set them up individually with each provider.

Once your Haimaker key is in `HAIMAKER_API_KEY`, [the connect CLI](/connect) (`npx -y @haimaker/connect --openclaw`) drops the provider config into OpenClaw for you, so you can route those sub-dollar models without touching JSON.

## The practical setup: hybrid free + cheap

Most people who care about costs end up here:

1. **Local model for simple tasks** (Qwen3.6 27B via Ollama, free)
2. **Cheap cloud model for medium tasks** (DeepSeek V4 Flash or MiniMax M3, pennies)
3. **Premium model for hard problems** (Claude Sonnet or Opus, pay-per-use)

```json5
{
  agents: {
    defaults: {
      model: {
        primary: "ollama/qwen3.6:27b",
        thinking: "anthropic/claude-sonnet-4-6"
      }
    }
  }
}
```

The local model handles 60-70% of requests (reading files, simple code). Sonnet kicks in for the rest. Your daily API bill drops to $2-5 instead of $30-50.

For more on model routing, see our guide on [multi-agent workflows](/blog/multi-agent-workflows-openclaw).

<a href="https://app.haimaker.ai/sign-up?utm_source=openclaw_blog&utm_medium=cta&utm_campaign=best-free-models" class="cta-button">GET $10 FREE CREDITS ON HAIMAKER</a>

---

*For a full model comparison, see [best models for OpenClaw](/blog/best-models-for-openclaw). For cost optimization strategies, see [cutting token costs by 96%](/blog/cutting-ai-agent-token-costs-qmd).*