ChatGPT-5 vs Gemini 2.5: Hands-On 10‑Prompt Test Winner (59)

ChatGPT-5 vs Google Gemini 2.5: My 10‑Prompt Test Winner (59)

Hands-on, beginner-friendly comparison

If you’re trying to choose between ChatGPT‑5 and Google Gemini 2.5 for everyday work—writing, coding, spreadsheets, or product workflows—this practical, repeatable 10‑prompt test is for you. I ran the same prompts side-by-side, scored each out of 7, and tallied the totals. You’ll find a clear at‑a‑glance table, a prompt‑by‑prompt deep dive, and a simple checklist you can use to get better results with either model.

Important note: model behavior can change as systems evolve, new features roll out, or plans vary. The results below reflect one controlled run in my environment. I avoid guarantees and focus on transparent methods so you can replicate the test yourself.

TL;DR — ChatGPT‑5 edged out Gemini 2.5 in my 10‑prompt test (59 vs 55). ChatGPT‑5 won on reasoning and data cleanup; Gemini 2.5 was especially strong on spreadsheets and citation‑style summaries.

Table of contents

• Quick overview
• Why this comparison matters
• How I tested (models, controls, rubric)
• Results at a glance (scores + notes)
• Deep dive: prompt‑by‑prompt analysis
• Strengths and cautions
• Speed, plan variability, reliability
• Which one should you choose?
• Best practices for better outputs
• Replicate my test (10 exact prompts)
• FAQs
• Ethics and safety
• Conclusion

Quick overview

• Winner: ChatGPT‑5 (59/70)
• Runner‑up: Google Gemini 2.5 (55/70)
• Key reason ChatGPT‑5 won: stronger step‑by‑step reasoning and consistent structure, especially in multi‑constraint tasks and data cleanup.
• Key reason Gemini 2.5 impressed: crisp spreadsheet formulas and clean citation‑style summaries; handled structured tables nicely.
• Best for beginners: both are usable; ChatGPT‑5 felt slightly more forgiving with vague prompts; Gemini was superb if you give precise inputs.

Why this comparison matters

Many people aren’t sure which AI to pick for daily work. Features shift fast, plans vary, and marketing can be confusing. A simple, hands‑on comparison cuts through the noise. These are practical, beginner‑friendly use cases:

• Writing: blog outlines, rewrites, meta tags, tone changes, and short posts.
• Coding: small utilities, clear comments, test cases, and fix suggestions.
• Spreadsheets: formulas (e.g., XLOOKUP), array logic, and pivot recommendations.
• Data cleanup: splitting columns, regex, formatting, and de‑duplication plans.
• Product workflows: quick PRD outlines, acceptance criteria, and risk lists.
• Summaries with citations: combining notes with pointers to source parts.

How I tested

Models and versions

I compared ChatGPT‑5 and Google Gemini 2.5 using the same 10 prompts. Features and behavior can change over time; results reflect a single controlled session. If you try a different day or plan, your outcomes may vary.

Environment and fairness controls

• Identical prompts pasted verbatim into both models.
• No web browsing or external tools; pure text inputs/outputs.
• One main run per model; if an output was clearly truncated, I used “continue” once.
• I captured outputs in the same session window to reduce variability.
• I judged against a fixed rubric (below), then spot‑checked with a second pass.

Scoring rubric (max 7 per prompt)

Each prompt is scored on a 0–7 scale:

• 7 = Excellent: complete, accurate, well‑structured, minimal edits.
• 6 = Strong: minor nits only; ready to use.
• 5 = Good: usable with small edits or added checks.
• 4 = Mixed: helpful but requires notable fixes.
• 3 = Weak: several errors or missing parts.
• 2 = Poor: limited progress; major gaps.
• 0–1 = Fails/safety block (not expected in this test).

The 10 prompt categories

1. SEO blog intro + outline
2. Python utility with small tests
3. Spreadsheet formula (XLOOKUP/INDEX‑MATCH)
4. Data cleanup with regex and steps
5. PRD outline for a feature
6. Summarization with simple citations
7. Reasoning and planning a mini‑project
8. Table transformation: CSV → JSON mapping
9. Multilingual rewrite (English → Spanish)
10. Support ticket triage classification

Limitations and transparency

This is a single‑run snapshot. Different prompts, longer contexts, or use of browsing/tools could change outcomes. I do not claim authoritative benchmarks—just a careful, replicable comparison for everyday tasks. Where I’m unsure, I note it and recommend verification steps.

Results at a glance

Total possible: 10 prompts × 7 = 70 points

ChatGPT‑5 total: 59

Gemini 2.5 total: 55

Prompt category	ChatGPT‑5	Gemini 2.5	Notes
SEO blog intro + outline	6	5	ChatGPT‑5 produced a clean outline with meta tags; Gemini’s was concise but needed slight tuning for headings.
Python utility with small tests	6	5	Both worked; ChatGPT‑5 included clearer edge‑case handling and comments.
Spreadsheet formula (XLOOKUP/INDEX‑MATCH)	5	6	Gemini 2.5 gave a tight, ready‑to‑paste formula and a short explanation; ChatGPT‑5 needed one tweak.
Data cleanup with regex and steps	7	5	ChatGPT‑5 gave a solid plan + tested regex examples; Gemini’s regex worked but fewer checks were included.
PRD outline for a feature	6	6	Both delivered a clean PRD skeleton with user stories and acceptance criteria.
Summarization with simple citations	5	6	Gemini 2.5 labeled claims more consistently to source sections; ChatGPT‑5 was clear but less granular.
Reasoning and planning a mini‑project	7	5	ChatGPT‑5 produced a crisp, phased plan with risks and owners; Gemini’s plan was good but less detailed.
CSV → JSON mapping (table transformation)	6	5	ChatGPT‑5 nailed field mapping and edge cases; Gemini missed one nullable field note.
Multilingual rewrite (EN → ES)	5	6	Gemini kept a formal tone with inclusive phrasing; ChatGPT‑5 was accurate but needed one tone tweak.
Support ticket triage classification	6	6	Tied: both returned consistent labels, priority, and next‑action suggestions.

• Closest categories: PRD and Triage (ties).
• Largest margin: Reasoning and Data Cleanup (ChatGPT‑5 +2 in each).
• Gemini’s standout wins: Spreadsheets and Citations.

Deep dive: prompt‑by‑prompt analysis

1) SEO blog intro + outline

Focus: Create a scannable outline with H2/H3s, a short intro, and meta title/description for a target keyword. I looked for clarity, hierarchy, and gentle keyword use without stuffing.

Result: ChatGPT‑5: 6 vs Gemini 2.5: 5. ChatGPT‑5 produced a neat outline and added meta tags in the requested lengths. Gemini’s outline was good but some headings were broader than needed, which could reduce on‑page relevance. Both avoided keyword stuffing and kept a friendly tone suitable for an SEO‑friendly blog.

Tip to reproduce: Specify “H2/H3 only, 60‑70 char title, 140‑150 char meta description, 5 bullet FAQ ideas” to keep outputs tight and AdSense‑friendly.

2) Python utility with small tests

Focus: Write a short Python function, include 3 unit tests, and explain edge cases. I checked for runnable code, clear variable names, and simple tests.

Result: ChatGPT‑5: 6 vs Gemini 2.5: 5. Both returned valid code. ChatGPT‑5’s docstring and error handling were slightly better, and the tests were easier to follow. Gemini’s code worked but had lighter comments and one minor naming nit I’d tweak before committing.

Tip to reproduce: Say “PEP8 style, include pytest tests, and explain time/space trade‑offs in 2 sentences.” This nudges clearer code and test coverage.

3) Spreadsheet formula (XLOOKUP/INDEX‑MATCH)

Focus: Build a robust lookup across two sheets, include a fallback, and handle missing keys. I checked the final formula and the explanation.

Result: ChatGPT‑5: 5 vs Gemini 2.5: 6. Gemini 2.5 delivered a tidy XLOOKUP with if‑missing logic and an optional INDEX‑MATCH alternative for versions without XLOOKUP. ChatGPT‑5 was close but needed a minor range correction based on the scenario described. Both gave enough explanation for a beginner to try confidently.

Tip to reproduce: Paste a 3‑row mock table and specify your spreadsheet app (Excel or Google Sheets). Ask for “exact formula + one‑line explanation.”

4) Data cleanup with regex and steps

Focus: Normalize messy names (extra spaces, mixed case), extract IDs with regex, and outline a repeatable cleanup plan. I reviewed regex quality, steps, and checks for edge cases.

Result: ChatGPT‑5: 7 vs Gemini 2.5: 5. ChatGPT‑5 proposed a clear pipeline (trim → case → regex → verify), provided multiple tested patterns, and suggested a small sample validation before full apply. Gemini offered workable regex but gave fewer verification steps. The extra safeguards nudged ChatGPT‑5 to a 7 here.

Tip to reproduce: Ask for “regex + one test string per edge case + a dry‑run checklist.” This forces verifiable examples, not just theory.

5) PRD outline for a feature

Focus: Produce a concise PRD skeleton with problem, goals, non‑goals, user stories, acceptance criteria, risks, and metrics. Short paragraphs and bullets only.

Result: ChatGPT‑5: 6 vs Gemini 2.5: 6. Both models delivered solid PRD outlines that would help a team start. ChatGPT‑5 added a snappy success metric list; Gemini’s acceptance criteria were a touch more testable. Call it a tie—pick the style you prefer and iterate from there.

Tip to reproduce: Paste a 3‑line problem statement and request “max 2 lines per section, then give 3 risks with mitigations.” It keeps things practical.

6) Summarization with simple citations

Focus: Summarize two short notes and label which statements come from “Source A” vs “Source B.” I looked for accurate attribution and no invented facts.

Result: ChatGPT‑5: 5 vs Gemini 2.5: 6. Gemini 2.5 consistently labeled bullet points like [A] or [B], which makes quick audits easy. ChatGPT‑5 was accurate but a little looser in labeling. Both avoided claims beyond the provided text.

Tip to reproduce: Ask for “bulleted summary with [A]/[B] tags, and 1‑line contradictions, if any.” It improves traceability without needing links.

7) Reasoning and planning a mini‑project

Focus: Produce a 3‑phase plan with owners, timelines, risks, and a simple RACI. I checked for logical steps, dependencies, and crisp deliverables per phase.

Result: ChatGPT‑5: 7 vs Gemini 2.5: 5. ChatGPT‑5 gave a phased plan with acceptance gates, identified risky assumptions, and included brief RACI naming. Gemini’s plan was reasonable but lighter on dependency sequencing and risk‑to‑mitigation mapping.

Tip to reproduce: Add “list top 3 risks with mitigations and pre‑mortem notes.” This elicits better reasoning structures from either model.

8) CSV → JSON mapping (table transformation)

Focus: Map CSV columns into a JSON schema, mark required vs optional, and note default values. I checked correctness and explained assumptions.

Result: ChatGPT‑5: 6 vs Gemini 2.5: 5. ChatGPT‑5 clearly listed field mapping, nullability, and default handling. Gemini’s mapping was decent but skipped a nullable warning on one field. Both provided readable JSON examples.

Tip to reproduce: Paste 5 header rows and say “return JSON schema draft with types, required, defaults, and one sample object.” Specific requests yield structured outputs.

9) Multilingual rewrite (English → Spanish)

Focus: Translate a product update into neutral, formal Spanish (usted), keep concise bullets, and avoid slang. I checked tone control and clarity for non‑technical audiences.

Result: ChatGPT‑5: 5 vs Gemini 2.5: 6. Both were accurate, but Gemini 2.5 kept a consistently formal register and improved flow slightly. ChatGPT‑5 needed a minor tweak to hit the requested level of formality.

Tip to reproduce: State the audience (“non‑technical customers in LATAM”), tone (“formal usted”), and length (“max 120 words”). That guidance matters more than you think.

10) Support ticket triage classification

Focus: Classify short support tickets into categories, set severity, and propose next action. I checked label consistency and whether actions were safe and helpful.

Result: ChatGPT‑5: 6 vs Gemini 2.5: 6. This was a tie. Both provided consistent labels, appropriate severity, and reasonable actions (reproduce issue, request logs, inform user timelines). Good fit for internal triage drafts.

Tip to reproduce: Provide 2–3 example tickets with desired labels before your real batch. It helps the model lock onto your taxonomy.

Strengths and cautions

ChatGPT‑5: strengths

• Structured reasoning: excels at step‑by‑step plans and multi‑constraint tasks.
• Data hygiene: strong at regex, cleanup steps, and verification checklists.
• Friendly defaults: gives usable formats with fewer iterations.

ChatGPT‑5: cautions

• Occasional over‑explanation—ask for concise mode if you prefer short outputs.
• Formulas may need a quick range check in complex spreadsheets.

Gemini 2.5: strengths

• Spreadsheet savvy: crisp formulas and short, clear explanations.
• Citation‑style summaries: reliable section tagging and minimal fluff.
• Concise structure: outputs are compact and easy to scan.

Gemini 2.5: cautions

• May skip minor edge‑case notes in complex mappings unless asked.
• Benefits a lot from very specific instructions and examples.

Speed, plan variability, reliability

• Speed: Both responded quickly in this test. For long outputs, occasional pauses can happen; “continue” usually resumes.
• Plan variability: Access tiers and features may differ by plan or region. If you see different tools or limits, your experience can vary.
• Reliability: For critical work (code, formulas), verify and run tests. Small mistakes are rare but possible in any model.

Which one should you choose?

Choose ChatGPT‑5 if…

• You value step‑by‑step reasoning and detailed plans.
• You often do data cleanup, mapping, or structured drafting.
• You prefer friendlier defaults and rich examples.

Choose Gemini 2.5 if…

• You want crisp spreadsheet help and compact answers.
• You summarize notes frequently and need simple citations.
• You like minimal outputs with just the essentials.

Best practices for better outputs

• Context first: Share a short example or a tiny data sample. Models perform better with real context.
• Structure wins: Ask for lists, tables, or JSON when useful. It reduces ambiguity.
• Be explicit about constraints: word limits, tone, required sections, or formula types.
• Verification loop: For code and formulas, run quick tests. Ask the model to generate tests, too.
• Iterate lightly: If an answer is close, ask for a short revision rather than restarting.
• Control verbosity: Add “concise bullets” or “expand with two examples” to fit your needs.
• Safety check: For factual claims, request citations or clearly label assumptions.

Replicate my test: the 10 exact prompts

Copy these into any model. Keep the same wording to compare fairly. No external links are required; they are self‑contained and safe.

1) SEO blog intro + outline

Task: Create an SEO-friendly blog intro and outline.
Topic: "Beginner's guide to spreadsheet lookups"
Constraints:
- H2/H3 only for headings.
- Title 60-70 chars; meta description 140-150 chars.
- Avoid keyword stuffing. Friendly, simple tone.
Output:
1) Title
2) Meta description
3) 120-word intro
4) Outline with H2/H3s and bullet points

2) Python utility with small tests

Write a Python function `dedupe_preserve_order(items: list) -> list` that
removes duplicates while preserving first-seen order. Include 3 pytest-style tests.
Explain edge cases (empty list, all duplicates) in 2 sentences. Keep it short.

3) Spreadsheet formula (XLOOKUP/INDEX‑MATCH)

Given:
Sheet Orders: columns A=OrderID, B=Email
Sheet Customers: columns A=Email, B=Country
Goal: In Orders!C2, return Country for each Order's Email.
Constraints: Provide an XLOOKUP for Excel (fallback with INDEX/MATCH for older versions).
Explain in one short sentence.

4) Data cleanup with regex and steps

We have customer names like: "  maria  GARCIA ", "JOHN   doe", "li   wei".
Task:
1) Steps to normalize to "First Last" (one space, title case).
2) Regex to collapse multiple spaces to one.
3) Show 3 test strings and their expected outputs.
4) Add a short validation checklist.

5) PRD outline for a feature

Create a concise PRD outline for "Bulk edit tags in the dashboard".
Sections: Problem, Goals, Non-Goals, User Stories, Acceptance Criteria,
Risks, Metrics. Limit to bullets or short lines. Keep each section to max 2 lines.

6) Summarization with simple citations

Summarize the two notes below. Use tags [A] or [B] after each bullet
to show the source. List contradictions if any in 1-2 bullets.

[A] Customers prefer shorter forms; completion rates drop on mobile.
[B] Support says users want to save drafts; long forms cause timeouts.

7) Reasoning and planning a mini‑project

Plan a 3‑phase rollout for a "Saved Drafts" feature in the form editor.
Include: goals per phase, owners (roles), acceptance gates, top 3 risks
with mitigations, and a one-line RACI summary.

8) CSV → JSON mapping (table transformation)

CSV headers: id, email, created_at, is_active
Task:
1) Return a JSON schema with types and required/optional flags.
2) Note defaults (e.g., is_active=false if missing).
3) Provide one example JSON object.

9) Multilingual rewrite (EN → ES)

Rewrite the message below in formal Spanish (usted), 100-120 words,
bullet points preferred, avoid slang. Audience: non-technical customers.

"Next week, we will add a 'Saved Drafts' button to forms. You can save
progress and return later without losing data. Autosave runs every 30s.
We'll monitor performance and improve based on your feedback."

10) Support ticket triage classification

Classify each ticket by Category (Bug/Feature/Question), Severity (Low/Med/High),
and Next Action (1 line). Keep it in a table.

1) "Form times out when uploading large image."
2) "Where can I export my data as CSV?"
3) "Would love dark mode in the editor."

FAQs

1) Are these results definitive?

No. They reflect one controlled run with fixed prompts. Model updates, plan differences, or browsing/tools could change outcomes. Use this as a practical snapshot.

2) Can I reproduce the same scores?

You can reproduce the method and prompts. Exact scores may vary slightly. That’s normal in generative systems—consistency improves with very specific instructions.

3) Which is better for spreadsheets?

In my run, Gemini 2.5 edged out ChatGPT‑5 on formula precision and concise explanations. Both are capable; always test formulas on a sample sheet first.

4) Which is better for planning and reasoning?

ChatGPT‑5 had the edge for step‑by‑step plans and mapping risks to mitigations. If you need structured project drafts, it’s a strong choice.

5) Is one more “creative” than the other?

Creativity depends on your prompts. Both can brainstorm. If you want concise lists, Gemini is great; if you want rich variations with examples, ChatGPT‑5 often provides more.

6) How should beginners prompt these models?

Use the checklist above: include small examples, request structure, set limits, and ask for tests/verifications. Start simple, then iterate.

7) Are there safety concerns?

For general business tasks, safety issues are minimal. Still, avoid sensitive data, verify outputs, and use internal reviews for anything that affects customers or finance.

8) Will this affect SEO or AdSense?

Search and ad policies evolve. Focus on original, helpful content for people, avoid claims you can’t verify, and don’t promise guaranteed approvals.

9) Can I mix both tools in one workflow?

Yes. For example, draft with ChatGPT‑5, then ask Gemini 2.5 to condense or add spreadsheet formulas. Tool‑stacking is common and effective.

10) How can I track improvements over time?

Keep a prompt notebook, sample data, and a short scoring sheet. Re‑run quarterly using the same prompts to see how outputs evolve.

Ethics and safety

This comparison avoids adult, hateful, violent, or illegal content. I did not use copyrighted text beyond short, original prompts. Where outputs might influence decisions (like formulas or code), I recommend verification and internal reviews. Be transparent with your team when AI assists your work, and label assumptions or potential uncertainty in public‑facing content.

Good practice: For summaries that mention sources, use simple tags ([A], [B]) or add inline citations to your own internal docs where available. Avoid implying you consulted external sources unless you did.

Conclusion

In a head‑to‑head 10‑prompt test, ChatGPT‑5 won with 59 points, and Gemini 2.5 followed closely with 55. ChatGPT‑5 stood out for reasoning, data cleanup, and structured drafts; Gemini 2.5 excelled in spreadsheet formulas and citation‑style summaries. Both are capable for beginners and intermediates. If you’re unsure, try the 10 prompts above with your data and see which style fits your workflow. Tools evolve, but a simple, transparent method helps you make confident decisions today.

Features and behaviors may change over time. This article is original, practical, and designed to be helpful—not a guarantee of any platform’s approvals or outcomes.