GoldieBench Blog · 6 min read
Grok Bot vs Cursor: Which AI Models Each One Lets You Use, And What The GoldieBench Scores Mean For Each
Cursor gives you a model menu. Grok Bot gives you none. Here is where benchmark scores help, and where they do not.
Grok Bot vs Cursor splits cleanly on models: Cursor lets you choose the model for each task, while Grok Bot manages model selection itself and shows you no picker.
That changes what a benchmark is worth for each one.
In Cursor, a GoldieBench score can help you pick what to run.
In Grok Bot, it can't, because you have no way to steer the choice.
Below are the scores I read on live GoldieBench pages on 6 November 2026, each quoted with its page.
Want help choosing models for your own stack? Book a free SEO strategy session.
Cursor: you pick the model
Cursor's Agent docs list three building blocks: instructions, tools, and the model you pick for the task.
The models page says Cursor supports frontier models from OpenAI, Anthropic, Google, SpaceXSI and more.
Cursor's own models are Grok 4.7, Grok 4.6, Grok 4.5 and Composer 2.5.
Third-party models such as Claude, GPT and Gemini sit outside the included usage pool.
That usage pool is shared across Agent in the editor, the CLI, cloud agents, Grok Bot and the Grok apps.
Grok Bot: no picker at all
The Grok Bot security page says there is no customer-facing model picker, and the serving mix can change over time.
Each request goes to a first-party SpaceXSI model or a third-party model from a provider on Cursor's sub-processor list.
Usage shows up as Grok Bot usage, not by model.
So no benchmark tells you which model handled a given Bot task.
What it can do is guide the models you choose for the Cursor side of the work.
Judge the Bot side on what you can control instead: the approvals you require, the apps you connect and the routines you set.
How Grok Bot and Cursor fit together
Grok Bot runs on Cursor's infrastructure: you sign in with your Cursor account, per the Grok Bot FAQ, and the Bot computers run in Cursor's cloud.
When a Bot meets a coding task, the Teams and Enterprise docs say it can hand it to a Cursor cloud agent under your existing Cloud Agent controls.
That cloud agent is where your model choice comes back into play.
So the benchmark question for this pair is really: which model should your Cursor agents run when Grok Bot hands them code?
The GoldieBench scores that map to Cursor's menu
| Model | GoldieBench average | Tasks | Page read |
|---|---|---|---|
| Claude Fable 5 | 8.10/10 | 47 | /models/fable-5 |
| Claude Opus 5.5 | 7.57/10 | 50 | /models/opus55 |
| Grok 4.7 | 7.15/10 | 20 | /models/grok47 |
All three appear in Cursor's model list, which also names the newer Claude Fable 5.1 that GoldieBench hasn't scored yet.
Composer 2.5 has no GoldieBench page yet, so I give it no score.
What these scores measure
The all-models page says every model gets the same fixed prompts, one shot each, scored 0 to 10.
Most tasks are single-file builds such as games, so a high score shows strength at one-shot creative coding.
It doesn't measure inbox triage, browsing or calendar work, which is what Grok Bot mostly does.
Read the numbers as a guide for Cursor agents, not as a ranking of Grok Bot.
Each score is one person's judgement on a fixed rubric, so a gap of a few tenths between two models is a hint, not a verdict.
Watch the task count too, because an average over 20 builds moves more with one bad result than an average over 50.
Reading the Grok 4.7 page
The Grok 4.7 page lists 20 tasks with a 7.15/10 average and medals of 0 gold, 2 silver and 3 bronze.
Its best one-shots were neoncity (8.7), racing (8.7) and arcade (8.6).
The same page notes that 2 of its 20 builds died on load or never moved when played.
Because Grok 4.7 is one of Cursor's own models, it's the natural default for routine Cursor agent work.
Reading the Fable 5 and Opus 5.5 pages
The Claude Fable 5 page shows 47 tasks, an 8.10/10 average and medals of 4 gold, 2 silver and 1 bronze.
The Claude Opus 5.5 page shows all 50 tasks benched, a 7.57/10 average and a single bronze.
Opus 5.5 has the bigger sample, while Fable 5 has the higher average and more medals.
For a cloud agent building something new from a description, that higher one-shot average is the number I would weigh most.
Pairing models by job inside Cursor
- Big one-shot builds, such as a live app from a description: start with Claude Fable 5, the top scorer of the three at 8.10/10 on GoldieBench.
- Long multi-file work: Claude Opus 5.5 at 7.57/10, from a 50-task sample, the largest of the three here.
- Everyday fixes and small changes: Grok 4.7 at 7.15/10, from Cursor's own model set.
Where to set the model
In the editor, you choose the model for each Agent task, so you can switch per job.
For larger work, Plan Mode lets the agent research the codebase and write a plan before any model starts editing files.
For repeat jobs, Cursor Automations run as cloud agents, and the docs note they use each model's maximum supported context window.
None of these settings reach Grok Bot, which keeps its own model choice for every Bot task.
If you want the model settings I use for each job, they are inside the AI Profit Boardroom.
Two examples, step by step
A design agency
- A client asks for a booking microsite.
- The account lead messages the agency's Grok Bot, which drafts the brief from the client's email.
- The Bot hands the build to a Cursor cloud agent, and the developer has set it to Claude Opus 5.5.
- Bugbot reviews the pull request, and the Bot attaches the agent's screenshots to its reply.
An estate agent
- A Bot reads new viewing requests each morning and drafts replies for staff to approve.
- When the listings page needs a filter fixed, the office's web contractor runs a Cursor agent on Grok 4.7.
- No benchmark changes the Bot side, because it picks its own model.
In both cases the benchmark decision sits with whoever runs the Cursor agent, while the Bot is judged on whether its drafts are right.
For the same model question against Anthropic's coding agent, read Grok Bot vs Claude Code on GoldieBench.
The verdict for model choice
If model choice matters to you, Cursor is the only side of this pair where GoldieBench scores change anything.
Grok Bot is the right tool for business errands, and you judge it on its approvals, routines and connected apps, not on a model score.
Use the scores to set your Cursor agents, and let the Bot hand them the code.
Also On Our Network
- Agent Operatorsthe seven-step order for setting up Cursor and Grok Bot on one login
- AI Income Deskwhich tool a salon, plumber, shop or agency should start with
- AI Tool Verdictan eight-criterion scorecard rating Cursor and Grok Bot from the docs
- agentos.guidefive copy-paste prompts that route work between Cursor and Grok Bot
- aiprofitboardroom.comthe complete Grok Bot vs Cursor guide on the AI Profit Boardroom blog
Set your Cursor model from the scores above, then book a free strategy session if you want help pairing models with grok bot vs cursor.
FAQ
Which model does Grok Bot use?
xAI does not say. The docs state there is no customer-facing model picker and the serving mix can change over time.
Which model scores highest of the ones listed here?
Claude Fable 5, at 8.10/10 across 47 tasks on its GoldieBench page. Cursor also lists the newer Fable 5.1, which GoldieBench has not scored.
Is Grok 4.7 a good default in Cursor?
It is one of Cursor's own models and averages 7.15/10 across 20 GoldieBench tasks, with 2 of 20 builds failing on load or play.
Do GoldieBench scores apply to Grok Bot tasks?
Not directly. The bench scores one-shot coding builds, while Grok Bot mostly does app and browser work on a model it picks itself.
Keep reading
Hermes vs Cursor: Which AI Models To Run In Each Tool, What The GoldieBench Scores Say, And How To Pair Them
Grok Bot vs Codex: Which AI Models Each One Runs, What The GoldieBench Scores Say, And How To Pair Them
Grok Bot Computer Use: Which AI Models To Pair With It, And What The GoldieBench Scores Mean When You Can't Pick The Model🌐 Sister-site take: read this on agentos.guide