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Is Grok Better Than ChatGPT? Grok vs ChatGPT Compared

Run grok-4.7 and gpt-5 head-to-head on your own prompt, with your own API keys. Real responses, cost, and latency side by side. Free, no signup.

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Give Grok and ChatGPT the same question and the same “keep it short” instruction, and in our run they read that instruction completely differently. Grok answered in 157 tokens. ChatGPT answered in 941. That is roughly a six times difference in length for the same question, and it is the clearest signal of how differently two models treat “be concise.”

The run

The whole setup behind the numbers:

  • Prompt: one everyday question (below), with an “under 200 words” limit.
  • Models: Grok grok-4.7 and ChatGPT gpt-5.
  • Settings: each model’s default, temperature 0.7, no system prompt, no extra context.
  • Keys: our own, calling each provider directly. One real run.

Prompt

A small bakery owner asks: “A customer wants to return a custom birthday cake they already picked up, saying it was ’too sweet.’ They’ve eaten half of it. How should I handle this professionally while protecting my small business?” Give practical, specific advice in under 200 words.

The result, side by side

Grok (grok-4.7)

  • Cost: $0.0035
  • Speed: 8.0 seconds
  • Length: 157 tokens
  • Read of “concise”: one tight paragraph, nothing extra

ChatGPT (gpt-5)

  • Cost: $0.0095
  • Speed: 12.9 seconds
  • Length: 941 tokens
  • Read of “concise”: a script plus a full checklist, about 6x longer

The actual answers:

Grok (grok-4.7)
Stay polite but firm. A half-eaten custom cake returned for being “too sweet” is a taste preference, not a defect. Thank them, note that custom orders are non-refundable once picked up, and that partial consumption means the product was accepted. A small future-order discount is optional, not owed. Document the conversation and post a clear custom-order policy on orders, receipts, and your site.
ChatGPT (gpt-5)
Triage the complaint first, and if it is a true defect, remake or refund; if preference, handle as goodwill. Then a professional script offering store credit, followed by a longer checklist: post a clear policy, use an order form and pickup sign-off, offer “less sweet” options and tastings, keep batch photos to fight chargebacks, and reply to public reviews once, politely.

Both give the same core advice. The measurable difference is reading the instruction: Grok gave you the short answer you asked for, ChatGPT gave you a fuller playbook that ignored the length limit.

Insight: “Concise” is not a fixed quantity. Two capable models can differ sixfold on the same instruction. If your app has a token budget or a UI that shows the whole answer, that gap is not cosmetic, it decides whether the output fits. Test the models on your own length expectations before you wire one in.

These results come from a specific run on 2026-11-02 on one defined task, using real models through a real pipeline. They show how each model performed on that task, not a general ranking of model quality, which depends entirely on your task and data. Run your own to see your numbers.

Run it on your own question

The free tool below opens with Grok and ChatGPT ready to go:

  1. Click Launch to open the notebook.
  2. Paste your own question and add your own API keys.
  3. Read both answers side by side with their cost and speed, in about a minute.

Nothing is sent to our servers, and your keys stay on your machine.

Want to go further? At llmprover.pysolvr.com you can score which answer is actually best for your task, compare up to 20 models at once, and see which part of your setup caused a weak answer.

Run as of 2026-11-02. Models and their behavior change often, so run a fresh comparison to see today’s result on your own question.

This free tool is a slice of the full product. With a paid plan you also get:

  • compare up to 20 models at once
  • score which answer is best
  • see which part of your setup caused a weak answer
  • save benchmarks and track changes over time
  • let your AI agent run it for you
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Free tool, provided as-is, no warranty. Uses your own API key. You are responsible for your usage and costs. Keys never leave your machine and are never sent to pysolvr. Outputs are informational, not advice. pysolvr is not liable for decisions made from these results.