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GoldieBench Blog · 7 min read

Grok Bot vs OpenClaw: Which AI Models To Run, With Real GoldieBench Scores

One tool routes models for you, the other hands you the dial. Here is how to use the board when you hold it.

A dark navy benchmark leaderboard with glowing gold bars, a closed cloud box on one side and an open dial of model choices on the other

Grok Bot vs OpenClaw splits cleanly on models: Grok Bot picks the model for you and never shows it, while OpenClaw lets you choose, swap and fall back between models yourself.

That makes GoldieBench scores useless for one side and very useful for the other.

Below are the scores I read on live GoldieBench pages on 4 November 2026, what they measure, and how I'd pair models in an OpenClaw setup.

The tool comparison itself is my reading of xAI's and OpenClaw's docs, since neither vendor compares the two.

If you'd like my team to map models to your workflows, grab a free SEO strategy session.

The model question, side by side

Model questionGrok BotOpenClaw
Can you choose the model?No pickerYes, as provider/model
Can you see which model ran?NoYes, it's your config
FallbacksNot user-configurableYour ordered list
Local modelsNot offeredSupported
Grok modelsHidden per taskBundled xAI plugin, curated default xai/grok-4.7
Can GoldieBench guide the choice?NoYes, for build-style work

Why GoldieBench can't score Grok Bot

xAI's Grok Bot FAQ says it chooses the backend model most likely to do each task well, and the choice can change from one request to the next.

It doesn't show the model, and users can't be routed to or away from one.

So there's no single model to benchmark, and the GoldieBench page called Grok covers the Grok model, not Grok Bot.

For Grok Bot, judge the product on its workflow features instead: the shared cloud computer, routines, Vault and Auto Review.

What GoldieBench scores actually measure

The methodology page says every model gets the same fixed prompt, one shot, with no help and no best-of-N.

Each result must be a single self-contained HTML file that runs in a browser, and the tasks are games, visuals, simulations and pages.

That's a strong signal for building things: landing pages, small tools and demos.

The ranking is each model's average 0 to 10 score across the tasks it was scored on, and medals go to the top three per task.

It isn't a test of inbox triage, tool calls or approvals, so treat it as one input when you pick a model for an assistant.

The scores I read for models OpenClaw can run

ModelGoldieBench scorePage readOpenClaw model ref
Claude Opus 58.27 avg over 50 tasks, rank #2Leaderboard, goldiebench.comanthropic/claude-opus-5
GPT-5.6 Sol8.16 avg over 50 tasks, rank #4Leaderboard, goldiebench.comopenai/gpt-5.6-sol
Claude Fable 58.10 avg over 47 tasks, rank #5Leaderboard, goldiebench.comanthropic/claude-fable-5
Grok8.09 avg, 43 of 47 tasks scoredLeaderboard and /benchmarks/grokGrok models via the xAI plugin
Grok 4.77.15 avg over 20 scored tasks, rank #18 of 26/models/grok47 and /benchmarks/grok47xai/grok-4.7

The model refs come from OpenClaw's Anthropic provider, Models and xAI provider docs.

One conflict to flag: the leaderboard lists Grok at rank #7, while the Grok deep dive says rank #8 of 26 ranked models.

The Grok model page also still carries an older note calling it unranked, beside the same 8.09 average.

Grok inside OpenClaw: the grok-4.7 default

To use Grok inside OpenClaw, you log in to the bundled xAI provider through Grok OAuth, which works with a qualifying SuperGrok or X Premium plan.

Your Gateway, config and tools stay local; xAI receives just the Grok calls.

With no primary model set, that login picks xai/grok-4.7 as the curated default.

On GoldieBench, Grok 4.7 averages 7.15 across 20 scored one-shot tasks, all games, with a 500,000-token context listed on its page.

Its best showings there are Neoncity and Racing at 8.7 each, per the Grok 4.7 deep dive.

If your OpenClaw job is building pages or demos, the board points to a higher-scoring model as the primary.

A pairing plan for an OpenClaw build

OpenClaw lets you set a primary model, fallbacks tried in order, and an optional cheaper utility model for short internal tasks.

openclaw models set anthropic/claude-opus-5

// openclaw.json (json5)
{
  agents: {
    defaults: {
      model: {
        primary: "anthropic/claude-opus-5",
        fallbacks: ["openai/gpt-5.6-sol", "xai/grok-4.7"],
      },
    },
  },
}

The order follows the board: Opus 5 at 8.27, then GPT-5.6 Sol at 8.16, with Grok 4.7 as the last resort.

Use the /model chat command to switch a single conversation without touching the default.

Re-check the board when a new model lands, because rankings move as models are added and scored.

If you want the pairing done with you on a live call, the AI Profit Boardroom runs four coaching calls a week.

Why model strength matters more once tools are on

OpenClaw is built for one trusted operator per Gateway, sandboxing is off by default, and host commands run without prompts in that default.

Its security FAQ adds a model point: smaller tiers are more open to instruction hijacking, so keep them for chat-only agents with trusted input.

For tool-enabled agents, use a strong model, apply the cautious exec preset and turn on a sandbox.

Grok Bot handles this layer for you, with Auto Review on by default and Ask first rules, per its approvals page.

The rest of the comparison, briefly

  • Where it runs: Grok Bot on a shared cloud computer per user; OpenClaw on your machine, with state and memory kept there.
  • Channels: OpenClaw reaches 20+ chat apps; Grok Bot uses its apps, X Chat and Slack shared Bots.
  • Memory: OpenClaw writes Markdown files; a Grok Bot saves memory you check by asking, per the Bots page.
  • Triggers: Grok Bot routines run on schedules and events; OpenClaw automations add webhooks, Gmail Pub/Sub and MCP events.
  • Browser: a persistent cloud browser with Vault, versus an isolated agent profile.
  • Setup: sign in and go, versus installer, wizard and policy.

What v2026.10.10 adds for model users

OpenClaw v2026.10.10 shipped on 3 November 2026.

Its experimental Advisor can review ongoing work and offer a short correction when it finds a clear wrong turn.

Alongside it come a Chat Details side panel, a split voice mode for Talk in the browser, sessions that open folders on a paired device, an opt-in relay for driving OpenClaw from ChatGPT or Claude, and automations started by MCP events.

None of these change which models you can run, but the Advisor gives a second check on a cheaper primary.

Grok Bot's latest changelog entry is V0.78.1, dated 27 October.

Small-business pairings, step by step

A web design studio on OpenClaw

  1. Set Claude Opus 5 as the primary, since build-style tasks are what GoldieBench measures.
  2. Add GPT-5.6 Sol and Grok 4.7 as fallbacks.
  3. Clients send briefs in Slack; the assistant drafts a one-page mock-up for the designer to review.

A bakery's order inbox on Grok Bot

  1. Skip the model question, because Grok Bot routes it.
  2. Forward order emails to the Bot's own address to start a routine.
  3. The Bot drafts confirmations, which wait as drafts until the owner sends them.

Verdict by job type

  • You want to pick and test models: OpenClaw, guided by the board.
  • You never want to think about models: Grok Bot.
  • You build pages and tools: OpenClaw with a top-scoring primary.
  • You run office admin across web apps: Grok Bot, where approvals come built in.

Also On Our Network

Check the leaderboard, set your primary and fallbacks, and join the AI Profit Boardroom or book a free strategy session to pick the right models for grok bot vs openclaw.

FAQ

Which model does Grok Bot use?

Grok Bot does not say. It picks a model per task, has no picker and does not show which model handled a request.

What is the highest-scoring model I can run in OpenClaw?

Among the models in this guide, Claude Opus 5 leads the GoldieBench leaderboard at 8.27 over 50 tasks, and OpenClaw lists it as anthropic/claude-opus-5.

Is Grok 4.7 a good primary model for OpenClaw?

It is the curated default when you sign in with xAI, and it scores 7.15 over 20 tasks on GoldieBench, so for build-style work a higher-scoring model makes a stronger primary.

Do GoldieBench scores test agent tool use?

No. They score one-shot single-file builds such as games, visuals, simulations and pages, so treat them as one input for an assistant.

The same stack Julian uses

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