Best AI Model for OpenClaw: Claude vs GPT vs DeepSeek vs Gemini (2026)
Comparisons · 12 min read
Best AI Model for OpenClaw: Claude vs GPT vs DeepSeek vs Gemini (2026)
Last updated: February 2026 · Reading time: 12 minutes
Every OpenClaw user has to make this decision, and most people overthink it. You configure a model in one line of your config file. You can change it anytime. You can even run different models for different tasks.
But the choice still matters because it determines three things: how smart your assistant is, how fast it responds, and how much you spend per month. The gap between the cheapest and most expensive option is roughly 60x.
Here's the short version: Claude Sonnet 4.5 is the right choice for most people. It's what the majority of the community uses, it handles everything from email automation to web browsing reliably, and it costs $5–15/month for typical use. If you want more detail — or if you want to save money, maximize quality, or run models for free — keep reading.
The Models That Matter for OpenClaw
OpenClaw supports dozens of models through direct API access and OpenRouter. But in practice, the community has converged on a handful that work well for agentic tasks. Here's what you need to know about each one.
Claude Sonnet 4.5 (Anthropic) — The Default Pick
Cost: $3/M input tokens, $15/M output tokens Typical monthly cost: $5–15 for moderate use (~50 messages/day)
This is the most popular model in the OpenClaw community, and for good reason. Sonnet handles the full range of assistant tasks — managing your calendar, drafting emails, browsing the web, running multi-step automations — with consistent reliability. It rarely breaks tool chains, follows instructions well, and has a 200K token context window that handles long conversations without degrading.
If you're setting up OpenClaw for the first time and just want something that works, pick Sonnet and don't look back.
{
"agent": {
"model": "anthropic/claude-sonnet-4-5"
}
}
Claude Opus 4.6 (Anthropic) — Maximum Intelligence
Cost: $15/M input tokens, $75/M output tokens Typical monthly cost: $15–60 depending on usage
Peter Steinberger, OpenClaw's creator, explicitly recommends Opus for users who want the best possible experience. It has the strongest reasoning, the best prompt-injection resistance (important for an agent that processes messages from others), and handles complex multi-step tasks with the least hand-holding.
The catch is obvious: it's roughly 5x more expensive than Sonnet. For most personal assistant tasks — "what's on my calendar?" or "send a reply to that email" — you won't notice a quality difference. Where Opus shines is complex reasoning, long research chains, and situations where getting it right the first time saves you from costly retries.
{
"agent": {
"model": "anthropic/claude-opus-4-6"
}
}
Claude Haiku 4.5 (Anthropic) — Budget Claude
Cost: $0.80/M input tokens, $4/M output tokens Typical monthly cost: $1–5
Haiku is Claude's smallest model, and it's surprisingly capable for simple tasks. It handles basic commands, quick lookups, and straightforward automations well. Where it falls short is complex reasoning, multi-step tool chains, and tasks that require the model to maintain context across a long sequence of actions.
Good for: a secondary model for simple tasks, a fallback when you hit rate limits on Sonnet, or a budget setup where you're okay with occasional failures on complex requests.
{
"agent": {
"model": "anthropic/claude-haiku-4-5"
}
}
GPT-4o (OpenAI) — The Alternative
Cost: $2.50/M input tokens, $10/M output tokens Typical monthly cost: $5–15
GPT-4o sits between Sonnet and Haiku on price. It's fast, strong at code generation, and handles simple assistant tasks well. The main drawback for OpenClaw is a shorter effective context window (128K vs Claude's 200K, with quality degrading faster at the edges) and less reliable tool use in complex multi-step chains.
Community benchmarks consistently show Sonnet outperforming GPT-4o on agent-specific tasks — the kind of multi-step, tool-using workflows that OpenClaw does all day. But if you already have OpenAI credits or prefer OpenAI's ecosystem, GPT-4o is a solid option.
{
"agent": {
"model": "openai/gpt-4o"
}
}
DeepSeek V3.2 — The Budget King
Cost: $0.27/M input tokens, $1.10/M output tokens Typical monthly cost: $1–5
DeepSeek has become the go-to budget model for OpenClaw users who want to minimize costs. At roughly 10–50x cheaper than Claude Opus, it handles basic tasks reasonably well: simple commands, routine automation, basic email processing.
Where it struggles: complex multi-step reasoning, reliable tool calling, and tasks that require maintaining context over long conversations. If your assistant mostly does simple things ("check the weather," "remind me at 5pm," "what's on my calendar"), DeepSeek is fine. If you need it to research a topic across multiple websites, synthesize information, and draft a report — you'll notice the quality gap.
{
"agent": {
"model": "deepseek/deepseek-chat"
}
}
Gemini 2.5 Flash (Google) — The Free Option
Cost: Free tier available (1,500 requests/day via Google AI Studio). Paid: $0.15/M input, $0.60/M output Typical monthly cost: $0–3
Gemini Flash is the standout free option. Google's free tier through AI Studio gives you 1,500 requests per day with no credit card required. That's enough for moderate personal use. The model has excellent tool-calling ability and a massive 1M token context window.
The free tier has rate limits that can interrupt your assistant mid-task during heavy use. But for getting started, testing OpenClaw, or running a low-volume personal setup, it's hard to beat free.
{
"agent": {
"model": "google/gemini-2.5-flash"
}
}
Local Models via Ollama — The Privacy Option
Cost: Free (your hardware) Typical monthly cost: $0 (plus electricity) Requirements: 16GB+ RAM for 8B parameter models
You can run completely local models through Ollama or LM Studio. Models like Llama 3.3, Mistral, and Hermes 2 Pro work with OpenClaw's tool-calling system. Your data never leaves your machine.
The trade-off is significant: local models lack the reasoning quality, context length, and safety features of cloud models. They work for experimentation, privacy-first setups, and simple tasks — but they're not recommended for production workflows where you need reliability.
# Install Ollama
curl -fsSL https://ollama.com/install.sh | sh
# Pull a model
ollama pull hermes-2-pro
{
"agent": {
"model": "ollama/hermes-2-pro"
}
}
The Comparison Table
| Model | Input cost (per M tokens) | Output cost (per M tokens) | Context window | Tool calling | Agent quality | Best for |
|---|---|---|---|---|---|---|
| Claude Opus 4.6 | $15.00 | $75.00 | 200K | Excellent | Best | Complex tasks, security-critical |
| Claude Sonnet 4.5 | $3.00 | $15.00 | 200K | Excellent | Great | Daily driver (recommended) |
| Claude Haiku 4.5 | $0.80 | $4.00 | 200K | Good | Good | Simple tasks, fallback |
| GPT-4o | $2.50 | $10.00 | 128K | Good | Good | Code-heavy, OpenAI users |
| DeepSeek V3.2 | $0.27 | $1.10 | 128K | Fair | Fair | Budget setups |
| Gemini 2.5 Flash | $0.15 | $0.60 | 1M | Good | Good | Free tier, high-volume |
| Local (Ollama 8B) | Free | Free | 8–32K | Basic | Basic | Privacy, experimentation |
"Agent quality" reflects how reliably the model handles multi-step, tool-using tasks — the core of what OpenClaw does. Raw benchmark scores don't capture this well. A model can score high on coding benchmarks but still break tool chains in agentic workflows.
Which Model Should You Pick?
Rather than ranking models in the abstract, here's what to pick based on your situation.
"I just want it to work"
Pick: Claude Sonnet 4.5
Don't overthink it. Sonnet is the community default for a reason. Sign up for an Anthropic API key, paste it in during onboarding, and you're done. You'll spend $5–15/month for typical personal use.
"I want the best possible assistant"
Pick: Claude Opus 4.6 for primary, Sonnet 4.5 for sub-agents
Use Opus for your main tasks and set Sonnet as the fallback. This gives you maximum intelligence where it matters while keeping costs manageable for background operations. Expect $20–40/month.
"I want to spend as little as possible"
Pick: Gemini 2.5 Flash (free tier) with DeepSeek V3.2 as backup
Google's free tier covers moderate personal use. When you hit rate limits, fall back to DeepSeek at pennies per conversation. Total cost: $0–5/month. Quality won't match Claude, but for basic assistant tasks it works.
"I want to try before I commit"
Pick: Gemini 2.5 Flash (free tier)
Zero cost, no credit card. Enough to test whether OpenClaw fits your workflow before spending anything. If you like it, upgrade to Sonnet later.
"Privacy matters most"
Pick: Ollama with Hermes 2 Pro or Mistral 7B
Everything stays on your machine. You sacrifice quality and reliability, but your conversations never touch a third-party server. Requires decent hardware (16GB+ RAM).
"I run a business on this"
Pick: Claude Opus 4.6 with multi-model routing
Use Opus for client-facing or business-critical tasks, Sonnet for routine operations, and a cheap model for heartbeats and background checks. Set spending alerts on your Anthropic account. See the multi-model routing section below.
Multi-Model Routing: The Power Move
This is the feature most people don't know about. OpenClaw lets you assign different models to different types of tasks. Instead of running Opus for everything (expensive) or Sonnet for everything (sometimes not enough), you route each task to the appropriate model.
The concept is simple: heartbeat checks (periodic "are you alive?" pings) don't need a $30/M token model. Neither do simple calendar lookups. But a complex research task absolutely benefits from Opus-level reasoning.
Here's a practical config:
{
"agents": {
"defaults": {
"model": {
"primary": "anthropic/claude-sonnet-4-5",
"heartbeat": "google/gemini-2.5-flash-lite",
"subAgents": "deepseek/deepseek-chat",
"fallback": [
"openai/gpt-4o",
"google/gemini-2.5-flash"
]
}
}
}
}
What this does:
- Primary tasks (your main conversations): Claude Sonnet — great quality, reasonable cost
- Heartbeats (background pings every 30 minutes): Gemini Flash-Lite — nearly free
- Sub-agents (parallel workers spawned for subtasks): DeepSeek — cheap, good enough for simple operations
- Fallback chain: If Anthropic is down or rate-limited, try OpenAI, then Gemini
This kind of routing can cut your monthly costs by 50–80% compared to running Opus for everything, without meaningful quality loss on the tasks that matter.
Tips for Saving Money
A few things the community has learned the hard way.
Keep your SOUL.md short. Your system prompt is sent with every single message. Every word costs tokens. Keep it under 1,000 words and strip out anything unnecessary.
Use /compact regularly. Long conversation histories balloon your token usage. Compacting summarizes and trims the context, keeping costs down and responses fast.
Disable extended thinking for routine tasks. Claude's "think" mode (deep reasoning) consumes 3–10x more tokens. Great for complex problems, wasteful for "what's the weather?" Use /think off for daily tasks and /think high only when you need it.
Set spending alerts. Both Anthropic and OpenRouter let you set monthly spending limits. Do this before you forget. One runaway automation can burn through $50 in an afternoon.
Check for free credits. Anthropic, Google, and various programs offer free API credits for new users and developers. Search for current offers before paying full price — some programs give hundreds of dollars in free credits.
Use the right model for the right job. This is the single biggest cost lever. Multi-model routing (above) is the most effective way to reduce costs without reducing quality.
Frequently Asked Questions
Can I use my Claude Pro or ChatGPT Plus subscription instead of API keys?
Yes. OpenClaw can bridge to your existing subscription instead of using separate API keys. Check the authentication docs for setup instructions. This is a good option if you already pay $20/month for Claude Pro or ChatGPT Plus and don't want a separate bill.
Which model has the best tool calling?
Claude (Sonnet and Opus) leads on tool calling reliability in agentic contexts. GPT-4o is close behind. DeepSeek and local models have noticeably worse tool calling, which means more failures in multi-step workflows.
Does the model affect response speed?
Significantly. Gemini Flash returns responses in 1–2 seconds. Sonnet typically takes 3–5 seconds. Opus can take 5–15 seconds for complex responses. DeepSeek varies depending on server load. For an assistant you're chatting with on WhatsApp, a few seconds doesn't matter much. For automated workflows with many sequential steps, faster models complete tasks sooner.
Can I use different models for different channels?
Yes. You can configure your Telegram bot to use Sonnet while your WhatsApp connection uses Haiku, for example. This is useful if one channel handles complex tasks while another is just for quick checks.
Is running a local model worth the effort?
For most people, no. The quality gap between a local 7B model and Claude Sonnet is enormous — like comparing a calculator to a physicist. Local models make sense if privacy is your absolute top priority and you accept significant capability limitations, or if you want to experiment with self-hosted AI without API costs.
New to OpenClaw? Start with our setup guide. Need a server to run it on? See our hosting comparison. Want to know the full cost picture? Check our cost breakdown.