7 Best AI Models for OpenClaw AI in 2026

You open your OpenClaw config, type /model, and a wall of names scrolls past. 

Claude, GLM, Gemini, DeepSeek, Qwen, and a dozen others you have never heard of.

Picking wrong here is not a small mistake. 

The model behind OpenClaw decides whether your agent actually finishes tasks or just burns tokens and gets confused.

This list skips the full catalogue and narrows it to 7 best AI models for OpenClaw right now, chosen for how they actually perform inside an agent loop, not just how they score on a benchmark chart.

Three things separate a model that works well in OpenClaw from one that looks good on paper: 

Whether its tool calls return correctly formatted results, whether it retains instructions across a long session, and what it actually costs when an agent runs around the clock instead of answering one question at a time.

The Quick Answer

• Claude Sonnet 4.6:  best all-around default

• Claude Opus 4.6:  best for hard-coding and multi-step reasoning

• GLM-4.7: best budget daily driver

• GLM-4.7 Flash:  best for high-volume, low-stakes tasks

• Gemini 3.1 Pro: best for long-context and document-heavy work

• DeepSeek V3:  the best generous free tier to start with

• Gemma 4 (via Ollama):best for full privacy and zero API cost

Each one gets its own breakdown below, including what it costs and where it actually struggles.

1) Claude Sonnet 4.6: Best All-Around Default

$3 / $15 per M tokens · 200K context · Best for: daily assistant work

Sonnet 4.6 has become the model most OpenClaw users reach for first, and for a simple reason. 

Tool calls come back clean, earlier instructions from a long session remain intact, and the price sits well below Anthropic’s top-tier model.

It handles calendar management, email drafting, research, and daily automation without breaking a sweat. For anyone unsure where to start, this is the safest first pick.

Because so much of the OpenClaw community defaults to Sonnet, documentation and troubleshooting help for it is easier to find than for almost any other model on this list.

Watch out for: at roughly $3 input and $15 output per million tokens, costs still add up on a 24/7 agent loop. Track usage if you are running it around the clock.

2) Claude Opus 4.6: Best for Hard Coding and Multi-Step Reasoning

$15 / $75 per M tokens · 200K context · Best for: hard reasoning, not daily use

Opus is the model to reach for once a task gets genuinely hard: multi-file refactors, gnarly debugging, or planning that involves several competing trade-offs. 

It holds up better than anything else on this list when a task needs real reasoning.

This is not a daily driver. The premium pricing makes sense for the 10 to 20 percent of tasks that actually need it, not the routine work that fills most of an agent’s day.

Watch out for: the cost, easily four to five times Sonnet’s, adds up fast if you leave it as your default model rather than switching in only for the hard cases.

3) GLM-4.7: Best Budget Daily Driver

$0.39 / $1.75 per M tokens · 200K context · Best for: cheap, reliable daily work

Zhipu’s GLM-4.7 is one of the better-kept secrets in the OpenClaw community. 

At a fraction of Claude’s price, it handles refactoring, test writing, and boilerplate generation reliably, with tool calling that rarely fumbles a parameter.

The 200K context window comfortably covers most single-project work, and the price makes it realistic to run all day without watching the bill climb.

It is not a built-in OpenClaw provider, so wiring it in takes an extra config step, but that setup takes minutes once and then stays out of the way.

Watch out for: it is not built for the hardest reasoning tasks. Debugging a genuinely tricky bug or designing a non-trivial algorithm is where it starts to struggle.

4) GLM-4.7 Flash: Best for High-Volume, Low-Stakes Tasks

$0.06 / $0.40 per M tokens · 200K context · Best for: bulk, mechanical tasks

Flash is built for a different job entirely: mechanical, high-volume work where you are not really choosing a model, just running one.

File classification, commit messages, simple search-and-replace across a codebase.

At a tiny fraction of a cent per thousand tokens, automation becomes practical at a scale that would be reckless under a premium model.

Watch out for: do not ask it to reason. Flash is fast and cheap, not smart, and pairing it as a first-pass triage layer in front of a stronger model is where it earns its keep.

5) Gemini 3.1 Pro: Best for Long-Context and Document-Heavy Work

~$1.25 / $10 per M tokens · 1M+ context · Best for: research, long documents

Gemini’s context window is the standout feature here.

 Feeding an entire codebase, a long contract, or a stack of documents into a single prompt is where this model pulls ahead of everything else on this list.

For OpenClaw agents doing research, document review, or anything that requires holding a large amount of information at once, Gemini 3.1 Pro is worth the setup.

Watch out for: outside of long-context tasks, it does not consistently beat Claude or GLM on tool-calling reliability, so treat it as a specialist pick rather than an everyday default.

6) DeepSeek V3 — Best Generous Free Tier to Start With

~10M tokens/month free · Best for: testing OpenClaw before you commit to a paid model

DeepSeek V3 gives new OpenClaw users a genuinely usable free tier, with quality that holds up well against far more expensive models.

 It is often the first stop for anyone testing whether OpenClaw is worth setting up.

Reasoning capability is solid for the price, and the free allowance is generous enough to run a real personal assistant on for weeks before hitting a limit.

Watch out for: reliability comes at a trade-off. Expect occasional rate limits and latency spikes during peak hours, so build in retry logic if you are relying on it for time-sensitive tasks.

7) Gemma 4 (via Ollama): Best for Full Privacy and Zero API Cost

$0, runs locally · 16GB RAM minimum · Best for: privacy-sensitive personal use

Running Gemma 4 locally through Ollama means nothing ever leaves your hardware, and there is no API bill. Any Mac with 16GB of unified memory handles it comfortably.

For code reading, simple edits, and boilerplate, it holds up well. For privacy-sensitive personal or business use, it is the only option on this list that keeps every prompt entirely offline.

Watch out for: complex, multi-step reasoning is where local models still fall behind the cloud options above. 

Most people who go this route end up pairing it with a cloud-based model for the more complex tasks.

How to Actually Decide

Do not pick one model and stop there. 

Most OpenClaw users who have been running it for a while settle on two or three: a cheap or free model as the default, and a premium model they switch to only when a task calls for it.

Start with Sonnet 4.6 or GLM-4.7 for daily work, keep Opus 4.6 in reserve for the hard cases, and test one free option before committing to a paid plan. 

Switching models later is a one-line config change, not a rebuild.

If budget is the only constraint, start free. 

If reliability under real workload matters more than saving a few cents per session, spend the money on Sonnet or GLM-4.7 from day one and skip the trial-and-error phase entirely.

The Question None of These Rankings Answer

A benchmark score tells you nothing about whether your agent is actually reachable when a scheduled job needs to fire at 3am. 

That comes down to where OpenClaw itself runs, not which model answers the prompt.

OpenClaw needs to stay online continuously to catch messages and run its background jobs.

 A laptop that sleeps, a home connection that drops, or shared hosting without root access breaks that, regardless of which model from this list you picked.

Where you are in the process changes what to do about it.

Already running OpenClaw somewhere.

If your agent is live on a laptop or a general-purpose server and you have noticed missed jobs or slow replies, the model is rarely the cause. Truehost UK’s OpenClaw Hosting moves it to a dedicated, always-on server built for this exact workload, with full root access and a UK-based data center for lower latency.

Still deciding which model to use.

Test two or three of the models above first, on whatever machine you already have. Once you know which one fits your workload, spin up a Truehost UK OpenClaw server and deploy it properly from the start, rather than migrating later once the agent is already depended on.

Common Questions

What is the cheapest OpenClaw model?

GLM-4.7 Flash is the cheapest option on this list that still handles agent tasks reliably, at roughly six cents per million input tokens. DeepSeek V3’s free tier is even cheaper, at zero cost up to its monthly limit.

Can I run OpenClaw for free?

Yes. DeepSeek V3’s free tier, or a locally hosted model like Gemma 4 via Ollama, both work with OpenClaw at no API cost. Expect more rate limits on DeepSeek and less reasoning depth on Gemma 4 than on a paid model.

Which model has the best tool calling for OpenClaw?

Claude Sonnet 4.6 and GLM-4.7 both stand out for consistently returning correctly formatted tool calls, which matters more for OpenClaw than raw benchmark scores.

Do I need a powerful computer to run these models?

Only for the local option. Gemma 4 needs a machine with at least 16GB of memory. Every other model on this list runs through an API, so your OpenClaw server just needs to stay online, not run the model itself.

The Bottom Line

There is no single best model for OpenClaw. There is the right model for what you are actually doing, and often that means running two or three side by side.

Start with a default that matches your daily work, keep a premium option in reserve for the hard cases, and give the whole setup a reliable place to run.

When you are ready, see Truehost UK’s OpenClaw Hosting plans and get your agent running on a server built for the job.